Helen Hamilton* Natural England Sarah Ross* Paul Silcock† Towards an Understanding of the Sue Steer† Perceived Increase in Juncus *Penny Anderson Associates Ltd (Rush) Species in Species-Rich †3D Rural Upland Hay Meadows March 2018
______
NATURAL ENGLAND
TOWARDS AN UNDERSTANDING OF THE PERCEIVED INCREASE IN JUNCUS (RUSH) SPECIES IN SPECIES-RICH UPLAND HAY MEADOWS ______
Penny Anderson Associates Limited ‘Park Lea’ 60 Park Road Buxton Derbyshire SK17 6SN
Project Manager Helen Hamilton BSc (Hons), MSc, MCIEEM, CEnv
Authors Helen Hamilton BSc (Hons), MSc, MCIEEM, CEnv Sarah Ross BSc (Hons), PhD, MCIEEM, CEnv Paul Silcock MA (Hons), MRICS, FAAV, CEnv, PIEMA Sue Steer MRAC, FRICS, FAAV
March 2018
This project has been undertaken in accordance with PAA policies and procedures on quality assurance.
Signed:______
180136 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
CONTENTS
Page
1. SUMMARY...... 1 2. INTRODUCTION...... 3 Background ...... 3 Project Objectives...... 5 3. METHODS ...... 6 Literature Review...... 6 Site Selection...... 6 O’Reilly 2010...... 6 AEMA Database ...... 7 Hamilton et al. 2014...... 7 Starr-Keddle 2014...... 7 Field Survey...... 7 Access ...... 8 Site Overview...... 8 Mapping ...... 8 Botanical Recording...... 9 Soils ...... 10 Farm Management Questionnaire...... 12 Agronomic Assessment...... 12 Data Entry and Checking...... 13 Data Analysis...... 13 Selecting a Baseline ...... 13 Data Collation ...... 13 Characterising the Dataset ...... 13 Initial Processing...... 13 All Species...... 14 Positive and Negative Indicators ...... 14 National Vegetation Classification...... 15 Ellenberg Indicators and Competitors, Stress-tolerators and Ruderal Species...... 16 Statistical Analysis ...... 16 Correspondence Analysis...... 16
180136 i Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Data Management...... 17 4. RESULTS ...... 18 Literature Review...... 18 Site Selection...... 22 Summary of 2017 Botanical Data...... 24 Quadrat 1x1m with Percent Cover...... 24 Quadrat 2x2m with DAFOR ...... 26 Whole Site W-walk DAFOR ...... 27 Summary of Other Sward Variables 2017 ...... 28 Summary of 2017 Soil Analyses...... 29 Geographic Information ...... 32 Summary of 2017 Derived Vegetation Data ...... 33 Combined Datasets ...... 34 Farm Management Questionnaire...... 37 Statistical Analysis...... 53 Competitor Stress-tolerator Ruderal...... 56 Ellenberg Indicator Values...... 56 Positive Indicators...... 57 Negative Indicators ...... 58 Soils ...... 59 Correspondence Analysis...... 60 Agronomic Assessment...... 71 Hay Yield...... 71 Hay Quality ...... 72 Other Impacts ...... 75 5. LIMITATIONS ...... 78 Literature Review...... 78 Site Selection...... 78 Field Survey...... 78 Farm Management Questionnaire...... 79 Statistical Analyses...... 79 Quadrat Size...... 79 Quadrat Location ...... 80 Methods...... 80 Dates ...... 80
180136 ii Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
6. DISCUSSION AND CONCLUSIONS...... 81 Species-rich Upland Hay Meadow ...... 81 Quantifying the Extent and Spread of Rushes ...... 81 Hydrological Conditions and Management Factors ...... 82 Impact of Rushes on Forage Production and Quality ...... 84 Recommendations...... 90 7. REFERENCES...... 92 8. ABBREVIATIONS...... 95
TABLES
1 Positive and Negative Indicators for MG3 (◊) and MG8 (♦) Upland Hay Meadow (JNCC 2004)...... 15 2 Ecological Characteristics of Juncus acutiflorus, J. conglomeratus and J. effusus ... 20 3 Selected Sites with Rush and Availability of Past Botanical Data (n=51) ...... 22 4 Most Frequent Vascular Species in 1x1m Quadrats (n=153) ...... 24 5 Most Frequent Vascular Species in 2x2m Quadrats...... 25 6 Most Frequent Vascular Species in Whole Site DAFOR Data...... 27 7 Sward Variables at 2x2m Quadrat Level...... 29 8 Soil Field Observations from 2x2m Quadrats (n=153) in 2017 ...... 30 9 Soil Chemical and Textural Analysis by Site (n=51) in 2017 ...... 30 10 Gradient and Elevation Summary for All Sites (n=51)...... 23 11 NVC Coefficients, Ellenberg and CSR Values for Quadrats (percent cover) in 2017 23 12 Average Number of Species Per Sample for Three Data Subsets in Year 1 (Baseline) and Year 2 (2017) ...... 34 13 Average Values for Measured Variables at Quadrat and Site Level for Year 1 and Year 2 ...... 35 14 Average Coefficients of Fit to Selected NVC Communities for Year 1 and Year 2 (1x1m quadrats) ...... 36 15 Average Ellenberg and CSR Values for Year 1 and Year 2 (1x1m Quadrats) ...... 37 16 Lime Application Rates as Reported for 11 Sites...... 47 17 Farmer Opinions from the Questionnaire Reponses on Rush Management ...... 49 18 Farm Management Question Responses on Drainage...... 50 19 Summary of Abundance of the Target Rush Species in Each Dataset in Years 1 and 2...... 54 20 Ordination Results for Samples and Species for 1x1m Quadrats with Percent Cover Data Log-transformed...... 63 21 Ordination Results for All Samples and Species for 1x1m Quadrats with % Cover Data Not Transformed...... 63
180136 iii Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
22 Ordination Results for All Samples, Species and Environmental Variables ...... 63 23 Change in Rush % Cover between Year 1 and Year 2...... 69 24 Additional Information Provided by Farmers ...... 77 25 Summary of Agronomic and Related Farm Business Impacts Arising from Rush Presence in Upland Hay Meadows ...... 88 26 Estimated Average Loss for Reduced Hay Yield, Hay Quality and Wastage Due to Rushes...... 89
FIGURES
1 Botanical Quadrat Set Up (arrow points North, inner = 1m x 1m, outer = 2m x 2m). GPS was Recorded for Bottom Left (south west) Corner ...... 10 2 Soil Corer - Open Drive Sampler, 2.5cm width x 33cm depth...... 11 3 Site Location Overview 4 Chart showing Soil Texture Categories...... 32 5 Main Crop Type Harvested Over the Past Ten Years (n=43) ...... 38 6 Usual Hay Meadow Shutting Up Dates (n=43) ...... 39 7 Usual Hay Meadow Cutting Dates (n=43)...... 40 8 Spring Grazing Livestock Breed Types (n=42) ...... 41 9 Autumn Grazing Breeds of Sheep and Cattle ...... 42 10 Supplementary Feed Types and Proportion of Sites Where Used (n=43)...... 44 11 Inorganic Fertiliser and Farmyard Manure Applications (n=43) ...... 45 12a/b Application Rates for Farmyard Manure and Frequency (n=43)...... 46 13 Increases in Rushes Reported by Farmers in Past 10 Years (n=41)...... 48 14 Summary of Field Drainage Types in Upland Hay Meadows (n=32)...... 53 15 Average Rush DAFOR from Whole Site Dataset for Year 1 and Year 2 ...... 56 16 Change in Site Percent Cover of Combined Positive Indicators between Years 1 and 2 (n=28) ...... 58 17a/b Soil Phosphorus (P), Potassium (K) and Magnesium (Mg) in Baseline (Year 1) and 2017 (Year 2) for Whole Site DAFOR Data...... 60 18 DCA Plot of Species Data Over Time (1x1m quadrats with % cover) with Species Data Log-transformed. RED = baseline GREEN = 2017 ...... 62 19 DCA Plot of Species Data Over Time (1x1m Quadrats with Percent Cover) Not Transformed RED = baseline GREEN = 2017...... 64 20 CCA Plot Of Species and Environmental Variables...... 66 21 CCA Plot Of Samples and Environmental Variables, where Juncus acutiflorus and Total Rush Increased ...... 67 22 Juncus acutiflorus Percent Cover in Year 1 and Year 2 (n=28)...... 68 23 All Juncus Percent Cover in Year 1 and Year 2 (n=28) ...... 69
180136 iv Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
24 CCA Plot of Samples and Environmental Variables, where Juncus acutiflorus and Total Rush Decreased...... 70 25 Estimated Hay Yield (t/ha) Based on Farmer Responses and Recorded Area of Hay Meadow (n=40) ...... 71 26 Estimated Difference in Hay Yield Compared with Similar Field on Farm without Rushes (n=20)...... 72 27 Description of Current Hay Quality from Field (n=41) ...... 73 28 Impact of Rush Presence on Hay Quality in Terms of Reduced Feed Value (n=42). 73 29 Impact of Rush Presence in Terms of Wastage of Hay by Livestock (n=39)...... 74 30 Other Impacts of Rush Presence on Hay Quality (n=40)...... 75 31 Other Agronomic or Knock-on Impacts Arising from Rushes in Hay Meadows (n=41) ...... 76 32 Relationship between Juncus as a % of Site Area and Estimated Hay Yield (n=40) 85 33 Relationship between Juncus as a % of Site Area and Estimated Reduction in Hay Yield Compared to a Similar Field without Rushes (n=20) ...... 86 34 Relationship between Juncus as a % of Site Area and Hay Quality (n=39) ...... 87
APPENDICES 1 Field Proformas 2 Farm Management Questionnaire Proforma 3 Full Botanical Species List with Common Names, 2017 4 Full 2017 Species List and Occurrence by Dataset 5 2017 Field Data (CD) 6 Best Three Fits to NVC Communities/sub-communities over Two Years 7 Combined Botanical and Environmental Data (CD) 8 Statistical Analysis Summary 9 Canoco Species Codes 10 Canoco Quadrat Sample Numbers by Year 11 Canoco Environmental Variables Gazetteer
180136 v Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
1. SUMMARY
Specific objectives of this study were to accurately quantify the extent and spread of rushes in upland hay meadows (UHM), to identify potential farming practices and/or physical conditions associated with increasing rush, and to estimate the agronomic impact of rushes in UHM.
Upland hay meadows are one of the rarest grassland habitats in the country. Their species-rich plant communities are principally allied to the National Vegetation Classification (NVC) types MG3 Anthoxanthum odoratum-Geranium sylvaticum (sweet vernal-grass and wood crane’s-bill) grassland and MG8 Cynosurus cristatus-Caltha palustris (crested dog’s-tail – marsh marigold) grassland. They occur on the in-bye land of valley bottoms and lower slopes of pastoral hill farms in northern England, and provide an important link to the socio-economic and cultural past of these areas, reliant upon traditional farming methods for their very existence but vulnerable to change. The community is a UK Biodiversity Framework Priority Habitat, with sites included within the North Pennine Dales Meadows Special Area of Conservation (SAC) as examples of mountain hay meadow (an Annex 1 habitat under the European Union Habitats and Species Directive).
The study focused upon three rush species (Juncus acutiflorus (sharp-flowered rush), J. conglomeratus (compact rush) and J. effusus (soft-rush)) within UHM in the North Pennines. The target rush species are native, natural components of UHM and have value for livestock and wildlife. Nonetheless, ecologists and farmers have expressed concern about gradual ingress into hill grasslands, but evidence and causes for this are little understood. The study aimed to advance understanding of this perceived increase in rush (Juncus) species in UHM through a desk study of available literature on rushes in the habitat, a botanical field study of rush increases at sites for which there was previous data, and a Farm Management Questionnaire.
The literature review collated general information for all three species of rush, but found little available evidence on rushes in species-rich grasslands and no studies relating to their control within UHM. Fifty- one survey sites were selected from several previous studies, with botanical and soil data collection at 1x1m and 2x2m fixed quadrats and for each whole site. Field surveys were completed over two weeks from 3rd to 13th July 2017, covering 115ha of UHM, of which 36ha was mapped as containing rushes. New datasets collected were assessed against the existing older datasets to detect any change over time. These two datasets (tagged Year 1 and Year 2) spanned at least five years, often much longer. Forty-three field-specific Farm Management Questionnaires were completed between September and December 2017 via telephone interviews.
A significant increase in rush extent was detected within the whole site DAFOR data for all rush species combined over time. However, the finding was not matched for Juncus acutiflorus or J. effusus or in the more robust quadrat data (% cover and DAFOR) where no significant changes in individual rush species or all rush species were seen over time. Many individual sites did show small insignificant increases. A positive correlation (r=0.48) was found between % cover of J. acutiflorus in Year 1 and Year 2, indicating that sites which had high rush in Year 1 had higher rush in Year 2, but the variability was high and several outliers had to be removed to obtain the result, meaning it did not fully represent the dataset. Surveyors noted that positive indicator species seemed to occur where J. acutiflorus was present, but quadrats containing J. acutiflorus were not found to have significantly greater species or positive indicator diversity. Nonetheless, average numbers of positive species were consistently higher where J. acutiflorus was present, highlighting the role of rush as a natural component of upland hay meadows and the importance of site-specific (rush) management to conserve valuable features of UHM.
More general change in vegetation community and soil parameters was explored, and no significant change in competitor/stress-tolerator/ruderal classes (Grime 1979), Ellenberg values for light, moisture, pH and fertility (Hill et al. 2004) or for positive or negative indicators (JNCC 2004) over time were found. A highly significant decrease in soil phosphorus was found but declines in soil potassium, magnesium
180136 1 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
and pH were not significant. Detrended Correspondence Analysis (DCA) showed little evidence of change in community composition between years. Canonical Correspondence Analysis (CCA) did not reveal any clear relationships between samples and environmental variables over time, even when only samples with rushes present were included.
Overall, the statistical results did not show conclusive evidence for an increase in rush cover in the UHM studies, although some results may hint at change. Data was difficult to analyse because it had to be sub-divided by collection method, within sub-set variability was high and quadrats, located and fixed as part of a pre-existing monitoring programme, did not always contain rush. Small sample number (e.g. whole-site DAFOR), small quadrat size and low sampling intensity versus large field size, high variability and wide ranging baseline dates were also considered to influence the study and affect confidence in results.
Key findings from the Farm Management Questionnaire related to the age of drains, the low use of inorganic fertiliser, the robust perception of an increase in extent of rush and the efficacy of herbicide as a management tool. The agronomic assessment of the potential impact of rush upon farms found that estimated average hay yield across the sample sites was slightly lower than recent DEFRA averages, and may relate to the presence of rushes. A negative relationship was detected between whole field cover of rush and estimated hay yield, with a very approximate average estimated reduction of 17% reported. However, increases in rush over the past decade were not linked directly to changing hay yields for 69% of farmers. The data suggested a relationship between increasing rush cover and declining hay quality, with rushes considered to influence feed value, wastage and spoilage of bales. Analysis of individual farmer responses suggests that the financial losses due to rushes could range from £0/ha to £338/ha, but the estimates include impacts that are hard to value with the evidence available.
The results of this study indicate that change in rush extent in UHM is difficult to quantify using existing botanical data, but has a potentially very significant impact upon farm income. It is also clear that there is little information on rush ecology and management within species-rich grasslands, limiting the development of appropriate and effective approaches for UHM management. To address these knowledge gaps, the following recommendations are made: updated autecological studies for all target rush species (including Juncus articulatus); develop monitoring network based upon whole-site data (not just quadrats); use of Geographic Information Systems (GIS) mapping technology to accurately record rush-grassland interface; full collation of farm management data for each sample site; further agronomic studies; site-specific management for UHM (and rush) to account for the natural diversity of UHM vegetation; and consideration of climatic and pollution effects.
180136 2 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
2. INTRODUCTION
2.1 Penny Anderson Associates Ltd (PAA) was commissioned in June 2017 by Natural England (NE) to undertake contract referenced ecm_49764 under Lot 9 of the Environmental Stewardship Monitoring and Evaluation Framework, entitled ‘Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows’.
2.2 The project aimed to provide a pilot study to accurately quantify the extent and recent spread of three rush species (Juncus acutiflorus, J. conglomeratus, J. effusus) within upland hay meadows in the North Pennines. Factors such as location, soil, hydrology, climate and management were considered, together with available autecological information on rushes.
2.3 The study comprised a desk-based review of existing field survey and monitoring data to find suitable sites for the study, a field survey of a selection of species-rich upland hay meadows (resulting in 51 sites), completion of corresponding Farm Management Questionnaires and an assessment of the agronomic impact of different levels of rush infestation.
2.4 Outputs comprised:
Project report;
Field survey data; and
GIS data.
Background
2.5 Upland Hay Meadows (UHM) are a rare and diminishing resource in Great Britain. Recent estimates suggest that the total extent of these meadows is 870ha in England with a further 26ha in Scotland (Bullock et al. 2011). In England, meadows are largely confined to the North Pennines, Lake District and County Durham with some outliers further north. UHM are recognised as a Priority Habitat within the UK Biodiversity Framework and a number of sites are included within the North Pennine Dales Meadows Special Area of Conservation (SAC) as examples of mountain hay meadow, a habitat listed on Annex 1 of the European Union (EU) Habitats Directive.
2.6 UHM are species-rich plant communities principally allied to the National Vegetation Classification (NVC) types MG3 Anthoxanthum odoratum-Geranium sylvaticum (sweet vernal- grass and wood crane’s-bill) grassland and MG8 Cynosurus cristatus-Caltha palustris (crested dog’s-tail – marsh marigold) grassland, which typically overlie freely-draining mineral soils (Rodwell 1992). These meadows are characterised by a dense growth of grasses and broadleaved herbs reaching 60 - 80cm high prior to cutting. No single grass species is consistently dominant and a striking feature of the vegetation is the abundance and variety of broadleaved herbs. The grasses, sweet vernal-grass (Anthoxanthum odoratum), cock’s-foot (Dactylis glomerata), rough meadow-grass (Poa trivialis), red fescue (Festuca rubra), Yorkshire fog (Holcus lanatus) and common bent (Agrostis capillaris) are all constant components of the community. Sub-montane species such as wood crane’s-bill (Geranium sylvaticum), melancholy thistle (Cirsium helenioides) and globeflower (Trollius europaeus) can be locally prominent, alongside a diverse range of other broadleaved herbs including lady’s-mantles such as Alchemilla glabra and A. xanthochlora, great burnet (Sanguisorba officinalis), pignut (Conopodium majus), common sorrel (Rumex acetosa), red and white clovers (Trifolium
180136 3 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
pratense and T. repens), bulbous buttercup (Ranunculus bulbosus), meadow vetchling (Lathyrus pratensis), rough hawkbit (Leontodon hispidus) and yellow rattle (Rhinanthus minor).
2.7 Most of the variation within UHM is due to their management (Rodwell 1992, Natural England and RSPB 2014): fields are typically grazed over winter except in the worst weather - mainly by sheep; they are shut up for hay late in April to early May; mowing takes place in mid- to late- July, though may be delayed to as late as September in unfavourable seasons; and the post- cutting ‘aftermath’ is then grazed until the weather deteriorates. Traditionally, the meadows have been given a light dressing of farmyard manure (FYM) in the spring and this, together with occasional liming, may have helped maintain their distinctive floristic composition.
2.8 Upland hay meadows are confined to areas where non-intensive hay meadow management has been applied in a sub-montane climate, on level to moderately sloping sites between 200m and 400m altitude. They are most characteristic of brown earth soils, with poor to impeded drainage throughout the year (Rodwell 1992). Stands are typically less than 2ha in extent and are usually isolated fields or groups of fields, where hay meadow management methods have persisted, but they are also recorded on river banks, road verges, and in woodland clearings.
2.9 Whilst rushes are a typical component of damper upland hay meadows, ecologists and farmers have expressed concern about the gradual ingress of the sharp-flowered and soft-rushes (Juncus acutiflorus and J. effusus) and to a lesser extent compact rush (J. conglomeratus) over the hill grasslands, pastures and meadows of upland areas. Pinches et al. (2013) states:
‘Data from Countryside Survey (Lindsey Maskell, pers. comm.) indicate that between 1998 and 2007 there was an increase in soft rush Juncus effusus nationally, alongside increases in the frequency of plant species with higher Ellenberg moisture requirements. In certain areas, notably Teesdale, rush species in particular soft rush, J. effusus and sharp-flowered rush J. acutiflorus, are reported to have increased noticeably in the last 10 years to an extent that the area of grassland (grazing) is viewed by landowners and botanists to be severely reduced in pastures and on hill- sides, and the quality of resulting hay crops compromised. O’Reilly (2010) reports that rushes have increased alongside creeping buttercup Ranunculus repens, meadowsweet Filipendula ulmaria and creeping bent Agrostis stolonifera all species that do well in damp conditions.’
2.10 Within land management schemes rushes are recognised as a component of upland and lowland wet pastures, and Higher Level Stewardship (HLS), and now Countryside Stewardship (CS) indicators of success include ranges of rush cover for different vegetation types and target bird species. Rush cutting to achieve and maintain these targets is expected as part of the management under such schemes. Until relatively recently there was little concern over rush encroachment in meadows, with the assumption that the typical annual cutting and aftermath grazing regime would keep rushes in check. In certain areas, notably Teesdale, the increase is judged by landowners to have been so great in some fields that the quality of hay crops has been compromised. There may be a disincentive to enter meadows into agri-environment schemes, due to more stringent restrictions on rush control using herbicide.
2.11 At the present time, reasons for any increase in abundance of sharp-flowered and soft-rushes are not well understood, and there has been little quantifiable evidence of change in rush cover in meadow habitats. The development of strategies to manage rushes would benefit from better information on cover and extent of the different species, and the occurrence of environmental and management factors that may influence them in different habitats including upland hay meadows. This would allow more informed and targeted rush management and control,
180136 4 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
address the policy objective of achieving a balance between environmental and production outcomes at a farm level, and lead to improved CS guidance.
Project Objectives
2.12 The objectives of the contract are:
To more accurately quantify the extent and recent spread of rushes within UHM, with a particular focus on the North Pennines, and to assess the extent to which current farming practice is contributing to the spread of rushes within hay meadows, including the contribution of agri-environment measures;
To identify soil and hydrological conditions and management factors that increase the risk of rush infestations; and
To provide an economic assessment of the impact of rushes on forage production and quality.
180136 5 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
3. METHODS
Literature Review
3.1 A brief review of scientific literature on rush ecology and management was completed to help target the field-based study upon known key factors affecting rush abundance in comparable habitats. Species information was summarised for each species; Juncus acutiflorus, J. conglomeratus and J. effusus.
Site Selection
3.2 Site selection was achieved through a desk-based review of existing data. Key data sources were associated with the following studies:
O’Reilly 2010;
Starr-Keddle 2014;
Hamilton et al. 2014; and
Natural England’s Agri-Environment Monitoring Archive (AEMA) database.
3.3 The process for selecting study sites was iterative because the initial criteria, as outlined below, did not provide sufficient sites (c.50) to meet the study objectives. Key criteria for initial selection of sites were:
Presence of UHM vegetation (broadly referable to MG3 or MG8);
Occurrence of Juncus effusus, J. conglomeratus or J. acutiflorus in the (preferably quadrat) dataset;
Existence of data from two previous surveys (so trends in rush could be identified);
Usefulness of data (i.e. quadrats, comparable across datasets); and
HLS options were not considered to be important to site selection for this study.
3.4 Since these initial criteria did not deliver sufficient sites, the threshold for inclusion was lowered to sites with rush and only one previous dataset, e.g. ‘new’ sites from Hamilton 2014. These data sources are described below.
O’Reilly 2010
3.5 O’Reilly (2010) compiled a data review examining the reasons for the declining condition of UHM. The study collated old botanical survey data and identified 281 highest quality sites which were mapped in GIS and referred to as ‘grade 4 sites’. O’Reilly highlighted sites with data that were collected with good parity in methods between datasets, and sites were prioritised for inclusion in this current study if they included a minimum of one past survey date and contained rushes.
180136 6 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
3.6 Because the baseline dataset was collected from fixed quadrats, new data could, in theory, be compared directly on a quadrat basis. However, concerns over accurately relocating the exact 2x2m quadrats should be considered in the interpretation of results.
3.7 The original data used by O’Reilly came from the larger AEMA database held by Natural England, which has not been updated since 2010, so does not include Hamilton et al. (2014), collected in 2012.
AEMA Database
3.8 Natural England’s AEMA database holds data for grasslands managed as both hay meadows and pastures. Of the 562 sites present within the dataset (meadows and pastures), 162 contained records of the three rush species. However, the O’Reilly (2010) study would contain the best examples of hay meadows most suited for inclusion in this current study, so the AEMA dataset was used to generate a longer list of additional sites which contained the target Juncus species, but for which details of previous surveys was not readily known.
Hamilton et al. 2014
3.9 This study, carried out in 2012, examined the long-term effectiveness of environmental stewardship in conserving UHM in the Pennine Dales. The study included a field survey of 103 UHM. The study aimed to assess and compare ecological condition, and evaluate and explain any change in communities since previous surveys. The survey focused upon sites with previous survey data, but also included some new sites. Sites were prioritised for inclusion in the 2017 study if they included a minimum of one past survey date and contained rushes.
3.10 Because the baseline dataset was collected from fixed quadrats, new data could be compared directly on a quadrat basis. The 2012 quadrats were marked using differential Global Position System (GPS) with sub-centimetre accuracy so could be exactly (or close-to exactly) re-located using similar equipment, imposing fewer limitations on the analysis.
Starr-Keddle 2014
3.11 A study was carried out and reported by Starr-Keddle (2014) looking at changes in UHM vegetation over the past 20 - 30 years in Upper Teesdale. In preparing this database, past surveys were reviewed and sites were selected that had good quality comparable data for a baseline year and a later date (‘matched pairs’). Sites were prioritised for inclusion in the current study where the target Juncus species were present in the data, and data collection was based on full species lists (i.e. not indicator species only).
3.12 Baseline data were in the form of a species list for the site with abundances represented on a scale of 1 to 5 (where 5=dominant, 4=abundant, 3=frequent, 2=occasional, 1=rare). These data were presented for the whole site and details of whether it was collected for each field as whole or just the UHM feature was unclear, so results should be viewed with this in mind when comparing with the current dataset.
Field Survey
3.13 The field survey was completed over two weeks from 3rd to 13th July 2017.
3.14 The field survey methods aimed to:
180136 7 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Collect data that was directly comparable to previous data as far as possible, either at the quadrat (1m2, 2m2) or whole site level;
Be repeatable in the future; and
Provide a baseline for future studies.
3.15 Field proformas are presented in Appendix 1.
Access
3.16 Contact details for all sites were provided by Natural England for all selected survey sites. Initially all farmers were sent a letter introducing the project, identifying potential survey fields and asking for their cooperation in the field survey and subsequent questionnaire. Farmers were then called in advance of survey to confirm permission and approximate date and time of survey and any special instructions. In some cases information on who was farming the land was found to be out-of-date, but enquiries locally enabled all the contacts to be made.
Site Overview
3.17 The site overview aimed to gather general site information to support botanical and soil data analysis, such as:
topography, slope, aspect, elevation;
positive and negative indicator species present;
management;
drainage features evident; and
general comments on Juncus, plus additional details for three target Juncus species of total percent cover, height (from four representative measurements taken across the site), habit types (e.g. tussock, occasional shoots, continuous shoots), and specific rush management measures (e.g. extra cutting, grazing, etc.) which were in addition to annual hay management cuts and grazing.
3.18 A representative photograph was taken of the site, with Global Position System (GPS) location and direction noted (and marked on the map).
Mapping
3.19 At each site, as part of the site overview recording, the UHM feature boundary was mapped onto a printed aerial map of the site, together with the general location and extent of the target Juncus species, differentiated where possible.
3.20 The location of a representative photograph for each site was marked on the map, with direction.
180136 8 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Botanical Recording
3.21 A full species list for the upland hay meadow feature was compiled at each site by following a ‘w-walk’ route across the field, as follows:
At 20 equidistant stops, percent cover of Juncus acutiflorus, J. effusus and J. conglomeratus were recorded and presence/absence of positive and negative indicators was recorded at 20 stops; and
DAFOR1 of all species across the whole feature.
3.22 The ‘w-walk’ route was selected to best cover the variability of the field and was constrained to the UHM feature.
3.23 One key criterion for site selection in this study was the pre-existence of botanical data. For sites in the Hamilton et al. (2014) dataset, accurate GIS information was used to re-locate quadrats, separate from the W-walk, previously surveyed in 2012. For other sites originating in the AEMA dataset, maps were available showing bearings and paces to re-locate the approximate location of quadrats. For the remaining sites, new quadrat locations had to be established. In order to avoid subjectivity, surveyors defined exact quadrat locations before going on site, usually along a transect or ‘v’ across the field within the UHM feature. At all sites a bottom left (or southwest) corner was established for each quadrat using differential GPS for accurate re-location in any future studies.
3.24 At all sites, three botanical quadrats were surveyed providing a full vascular and bryophyte species list with percent cover and DOMIN2 for an inner, nested 1x1m quadrat. The north-south oriented y-axis provided the origin for an outer 2x2m quadrat within which only DAFOR was recorded. Figure 1 shows the set up of each botanical quadrat.
1 The DAFOR scale is used for semi-quantitative sampling, to provide a quick estimate of the relative abundance of plants in a given area, where D-dominant (50-100%), A=abundant (30-50%), F=frequent (15-30%), O=occasional (5-15%), R-rare (<5%). Generally considered extremely subjective, especially to recorder bias.
2 DOMIN is the scoring system used for the NVC, where 10 (91-100%); 9 (76-91%); 8 (75-51%); 7 (34-50%); 6 (26-33%); 5 (11- 25%); 4 (4-10%); 3 (<4% many); 2 (<4% several); 1 (<4% few).
180136 9 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 1 Botanical Quadrat Set Up (arrow points North, inner = 1m x 1m, outer = 2m x 2m). GPS was Recorded for Bottom Left (south west) Corner
3.25 Within each quadrat a photograph was taken if any of the target Juncus species were present. Also recorded within the 2x2m quadrat were:
vegetation height (cm) at each corner;
percent cover bare ground and litter; and
for Juncus acutiflorus, J. conglomeratus, J. effusus only:
o percent cover;
o height (cm);
o habit (tussock, occasional and continuous shoots); and
o Whether cut, grazed or other specific treatment applied.
3.26 It was difficult to standardise recording of tussock, occasional and continuous shoots, but the following general definitions were used to guide the surveyors:
Tussocks – distinct tufts of rush stems separated by vegetation with no rush;
Occasional shoots – sparsely apparent as individual leaves/shoots within sward; and
Continuous shoots – more or less densely and continuously spread through sward.
Soils
3.27 A single bulked soil sample was compiled from 20 x 10cm plugs collected using a pot auger (after Natural England 2008a). The samples were taken across the UHM feature during the W- walk whilst completing the DAFOR list. The plugs were bagged, labelled and refrigerated for despatch to Natural England’s contractor who completed a standard analysis package as follows:
180136 10 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Texture;
pH;
Available P;
Available K; and
Available Mg.
3.28 In addition, at each quadrat location, a soil core was extracted using an open drive sampler (Figure 2) (Standard Soil Sampler 1" from www.pitchcare.com, producing a sample size of 2.5cm width by 33cm depth).
Figure 2 Soil Corer - Open Drive Sampler, 2.5cm width x 33cm depth
3.29 Based upon this core, a soil description was completed at each botanical quadrat location, making a record of:
A horizon – depth to bottom (cm);
B horizon – depth to bottom (cm);
Total core depth (cm);
Rooting depth (cm);
Soil texture by hand;
Presence of soil mottling3, gleying4 and podzol5; and
3 Mottling indicates where the soil column is seasonally waterlogged and delineates the zone where the water table rises and falls. It can often show as distinctive red or grey mottles.
4 Gleying results from permanent or prolonged saturation, often showing as bluish or greyish saturated soils.
5 A podzol is a soil formation especially typical of humid regions where leaching of the upper layers results in an accumulation of minerals in lower layers which are distinctly visible. Typical of acidic uplands on free-draining soils.
180136 11 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Compaction (using a nail test6, and with 30% calibrated using an ELE International Soil penetrometer).
3.30 A photograph of the soil core was also taken as a secondary record, should this be needed. Soil cores were discarded after description, and inserted back into the extraction hole to minimise damage to turf.
Farm Management Questionnaire
3.31 The Farm Management Questionnaire proforma is presented in Appendix 2. The questions were developed to investigate:
Hay management and cutting dates;
Grazing management;
Supplementary feeding;
Fertiliser, manure and lime application;
Rushes and rush management;
Botanical restoration;
Drainage;
Hay yield;
Hay quality; and
Other relevant information.
3.32 The latter three topics were especially aimed at gaining a better understanding of the economic impact of rushes in UHM via an agronomic assessment which also forms part of this study.
Agronomic Assessment
3.33 The agronomic assessment, set out in Chapter 4 and discussed in Chapter 6, explores the agronomic, farm business and farm economic impacts of rushes in upland hay meadows. It considers the impacts of rushes on hay yield, hay quality (including feed value and wastage), knock-on impacts in terms of livestock numbers, liveweight gain, livestock health and condition, forage/feed costs, available grazing etc., and the cost of rush management. The agronomic assessment is based predominantly on an analysis of responses to the Farm Management Questionnaire. This analysis draws on relevant price and cost data to provide an assessment of economic impact, and puts this in the context of Farm Business Incomes for the farm type
6 In which a 150mm x 6 mm nail is inserted into the soil using a single finger and ‘reasonable force’ and the distance it penetrates measured.
180136 12 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
concerned. Relevant evidence from a literature review and comments from the farmers themselves are also included.
Data Entry and Checking
3.34 Data entry of botanical information, field notes and Farm Management Questionnaires was undertaken manually, with a minimum of 10% of entered data checked for accuracy prior to any analysis (which in turn is very effective at data cleaning). Maps and Geographical Information Systems (GIS) data were collated in the same way with all data being re-checked by the lead surveyor for that site.
Data Analysis
Selecting a Baseline
3.35 Because the study was enquiring about ‘recent spread’ of rushes, the most recent previous dataset was selected to provide the ‘baseline’ for the analysis.
3.36 One benefit of this choice was that it allowed for the inclusion of many sites from the 2012 datasets which were considered to be more complete in terms of soil and quadrat location information as well as to have good parity in terms of survey method and personnel. However, because the dataset was only five years old, there was concern that some longer-term changes in rushes might not yet be apparent.
Data Collation
3.37 Once the 2017 data were digitised and checked for accuracy and completeness, the dataset had to be sub-divided so that each site from 2017 could be matched up with a baseline from at least one of the sources of baseline data. Data was subdivided as follows:
1x1m quadrats with percent cover (28 sites);
2x2m quadrats with DAFOR (35 sites); and
whole site data with DAFOR (19 sites).
3.38 Some sites had data in more than one analysis subset.
3.39 Current and baseline datasets were also matched up with any associated environmental and derived variables for: vegetation height; percent bare ground; percent litter; percent rush cover; soils information; gradient; aspect; elevation; presence of mottling and gleying; plant species traits; and NVC coefficients of fit.
Characterising the Dataset
Initial Processing
3.40 All botanical species nomenclature follows Stace (2010) for vascular plants and Atherton et al. (2010) for mosses and liverworts (bryophytes).
180136 13 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
All Species
3.41 A total overall species list was devised for all the 2017 data from all three survey methods (1x1m quadrat, 2x2m quadrat and whole site w-walk).
3.42 Total species lists were derived for each analysis type including baseline and 2017 data.
3.43 These lists were analysed for vascular and bryophyte diversity, most frequent species and other general characteristics.
Positive and Negative Indicators
3.44 Positive and negative indicators were defined after JNCC 2004, as summarised in Table 1, for the NVC communities of UHM MG3b Anthoxanthum odoratum-Geranium sylvaticum grassland, Briza media sub-community and MG8 Cynosurus cristatus-Caltha palustris grassland. The list contains a total of 41 species. Counts of indicators for each dataset were calculated.
180136 14 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Table 1 Positive and Negative Indicators for MG3 (◊) and MG8 (♦) Upland Hay Meadow (JNCC 2004)
Species Negative Positive Species Negative Positive Achillea ptarmica ♦ Geum rivale ◊♦ Ajuga reptans ♦ Lathyrus pratensis ◊ Leontodon Alchemilla agg. (NOT mollis) ◊ ◊♦ autumnalis Alchemilla filicaulis vestita ◊ Leontodon hispidus ◊♦ Alchemilla glabra ◊ Lotus corniculatus ◊ Alchemilla xanthochlora ◊ Lychnis flos-cuculi ♦ Anemone nemorosa ◊ Orchidaceae ♦ Anthriscus sylvestris ◊♦ Persicaria bistorta ◊ Caltha palustris ♦ Potentilla erecta ♦ Carex flacca ♦ Rhinanthus minor ◊♦ Carex nigra ♦ Rumex crispus ◊♦ Carex panicea ♦ Rumex obtusifolius ◊♦ Sanguisorba Centaurea nigra ◊ ◊♦ officinalis Cirsium arvense ◊♦ Senecio jacobaea ◊ Cirsium heterophyllum ◊ Serratula tinctoria ♦ Cirsium vulgare ◊♦ Succisa pratensis ◊♦ Conopodium majus ◊ Trollius europaeus ◊♦ Crepis paludosa ♦ Urtica dioica ◊♦ Euphrasia officinalis agg. ◊♦ Valeriana dioica ♦ Filipendula ulmaria ◊♦ Trees and scrub ◊ Geranium sylvaticum ◊
National Vegetation Classification
3.45 Species quadrat data were processed using the MATCH software (Thompson 2004) to derive coefficients of fit to target UHM NVC communities and sub-communities (Rodwell 1992). The analysis was undertaken for 2017 data and all previous years. The typical UHM communities MG3b and MG8 were considered key, but fits were also generated for closely related hay meadow communities such as MG3a and MG6b. Fits at the site level were calculated where possible using 1x1m data with percent cover where available, or 2x2m with DAFOR, calculating constancy tables using all three samples (quadrats).
180136 15 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Ellenberg Indicators and Competitors, Stress-tolerators and Ruderal Species
3.46 The Modular Analysis of Vegetation Information Systems (MAVIS) software (Smart et al. 2016) enables links to be made between botanical field data and a number of widely used classifications of plant species. Because the classifications remain static and only the field data changes, many different sorts of plant community can all be expressed in the same standard language allowing comparison from site to site. The classification systems used for this study were as follows:
Ellenberg scores for Light, Fertility, Wetness and pH (Hill et al. 1999, Hill et al. 2004); and
Grime (1979) developed a triangular Competitor, Stress-tolerator and Ruderal species (CSR) model classifying British vegetation in terms of three established strategies: Competitors; Stress-tolerators; and Ruderal species.
3.47 The analyses were undertaken for 2017 and the equivalent baseline data from previous years. Calculations were made individually for each dataset, e.g. separate calculations were made for (i) 1x1 m quadrats with percent cover, (ii) 2x2 m quadrats with DAFOR and (iii) whole site data with DAFOR.
Statistical Analysis
3.48 Key objectives were to accurately quantify the extent and recent spread of rushes within UHM and to assess the extent to which current farming practice may be contributing to this.
3.49 The three Juncus species were J. acutiflorus, J conglomeratus and J. effusus.
3.50 To this end, the following questions were asked of the data:
Does rush increase in any of the datasets?
Can any causes (environmental/management etc) be linked to any change indicated?
Correspondence Analysis
3.51 Correspondence analysis (CA), or reciprocal averaging, is a multivariate statistical technique which applies to categorical rather than continuous data. Certain CA methods such as Detrended Correspondence Analysis (DCA) and Canonical Correspondence Analysis (CCA) can be useful when comparing site-based botanical (and environmental) data from site to site and/or over time. It provides a means of displaying or summarising data in a two-dimensional graphical form which can be useful for interpretation and comprehension. All data must be non- negative and on the same scale. The method treats rows and columns (e.g. sites and species) equivalently. The CANOCO software package (Ter Braak and Smilauer 2002) is the standard software used to conduct such multivariate analyses, and was used in this study to investigate the possible complex relations between community composition and environmental factors in the selected upland hay meadows.
3.52 In particular, changes in composition over time were explored using DCA. The older data was used as the ‘active’ sample to represent a baseline, and the 2017 data were used as ‘passive’ samples. Thus change over time could be evaluated. The DCA was run for species data with
180136 16 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
and without log-transformation. In all analyses, rare species were down-weighted to reduce their influence.
3.53 Relationships between species composition and environmental variables were examined using CCA, in which the environmental variables can be directly correlated with the main axes of the ordination diagram. In this analysis only the 2012 and 2017 data could be used, as older data did not have sufficient environmental data for the analysis to run. In the analysis, species data were not log-transformed but rare species were down-weighted.
3.54 In both analyses, the software (CANOCO) generates axes based upon the data being used and each site or species is placed relative to all others in the dataset. Similar sites or species in terms of their composition and ecological needs would be expected to occur together and conversely for dissimilar sites or species. Eigenvalues provide a measure of the explanatory power of each axis and are constructed so as to be independent of the previous axes. On the graphs, the axes represent the variation in the dataset, not specific variables, and the strength of the axes is defined by the eigenvalues. Higher eigenvalues indicate that the axis explains more of the variation in the data. Being multivariate techniques, more than two axes are generated, and the eigenvalues present the axes in declining order of the amount of variation explained, with the strongest association always placed on the x-axis. Usually, only eigenvalues for the first four axes are presented.
Data Management
3.55 A GIS database has been prepared containing GPS location of all quadrats and mapped extent of the UHM feature at each site. This, combined with MS excel spreadsheets and photo files, makes up a database encompassing all data collected for the project. Specifically, the database contains the following components which will be supplied to Natural England at the end of the project:
GPS location of all quadrats – GIS files;
Area of field, UHM feature (cut area), rush (all species) – GIS files;
Soil data – MS excel spreadsheet; and
Botanical data – MS excel spreadsheets;
o All 2017 data;
o Quadrat percent cover data baseline and 2017; and
o Quadrat DAFOR data baseline and 2017.
Whole site DAFOR data baseline and 2017;
Management questionnaire data – MS excel spreadsheet; and
Site photos – JPEG files.
180136 17 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
4. RESULTS
Literature Review
4.1 A literature review of available material on rush ecology and management was completed by searching on the internet (using Google and Google Scholar) and within the PAA library. Relevant search terms were used individually and in relevant combinations, such as: Juncus, effusus, acutiflorus, conglomeratus, rush, ecology, autecology, characteristics, management, grazing, cutting, drainage, fertility, soil, meadow, grassland, agriculture and farming. Papers specifically relevant to upland hay meadow were sought.
4.2 Table 2 collates ecological characteristics for the three target rush species, and provides some general comments on responses to management, based upon Richards and Clapham (1941a and b) and other sources as cited below.
4.3 Juncus effusus is a densely tussock-forming perennial (Stace 2010, Hill et al. 2004), with a densely branching rhizome system with ability for lateral spread (Richards and Clapham 1941b). It is a perennial which flowers in late June to August and has a prolific and persistent seed bank (Grime 2001, Richards and Clapham 1941b). It is tolerant of a wide range of conditions and is a stress tolerant competitor, indicating that it has a lower maximum potential growth rate than competitors (Grime 2001). It is reported to have moderate resistance to trampling, to make unfavourable grazing for cattle and sheep and to be resistant to cutting (Richards and Clapham 1941b). Drainage is reported to reduce its cover, as is high inorganic fertiliser application (Richards and Clapham 1941b). J. effusus generally occurs in well-lit places, on constantly moist or damp but not wet ground and is an indicator of moderately to acid soils (Hill et al. 2004). Its water level tolerances are from -55cm to +30cm (Newbold and Mountford 1997).
4.4 Juncus conglomeratus is generally reported to be very similar to J. effusus in most aspects. It is a tussock-forming perennial (Stace 2010, Hill et al. 2004), with less dense and smaller tufts but still having a densely branching rhizome system with an ability for lateral spread (Richards and Clapham 1941a). A perennial, it flowers from May through summer and the seed bank is prolific and persistent (Richards and Clapham 1941a). J. conglomeratus is considered more tolerant of drier conditions than J. effusus, less palatable to cattle and sheep and also more tolerant of trampling (Richards and Clapham 1941a). It occurs in well-lit places, on constantly moist or damp but not wet soils and is an indicator of moderately acid to acid soils and of slightly less fertile sites than J. effusus (Hill et al. 2004). Its water level tolerances are from -100 to 0cm with a ‘preferred’ -5cm (Newbold and Mountford 1997).
4.5 Both species are considered unpalatable to cattle and sheep (Wolton 2000). Conflicting evidence exists on the efficacy of cutting (timing and frequency) on suppressing Juncus effusus vigour, and this only from pastures (Merchant 1993, Merchant 1995). Wolton (2000) reports that multiple cuts to ground level reduces vigour of tussocks, that topping may hinder shoot growth and that if only a single cut is possible then after mid-summer is best. Repeated cuts would be difficult to achieve in UHM, but a single post-mid-summer cut already occurs under current hay regimes.
4.6 Wolton (2003) also reports that Juncus effusus cover reduces with high inorganic fertiliser application, but this method of management is also unlikely to be suitable for UHM sites where maintenance of botanical diversity (and particularly forbs) is a target outcome. However, Lazenby (1995) found that soil fertility conditions themselves had no effect on initial establishment of J. effusus seedlings. Seed germination in J. effusus is inhibited by darkness in
180136 18 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
the soil (Grime 2001) leading to a large persistent seed bank. Bare ground created by poaching may encourage germination of dormant J. effusus seeds (Farming Connect 2014).
4.7 Juncus acutiflorus is a rhizomatous patch-former (Stace 2010, Biological Records Centre 2017), spreading vegetatively via far-creeping rhizomes (Hill et al. 2004). It also has a prolific and persistent seed bank (Wolton 2003). Flowering occurs from July to September, and the plant is characteristic of damp to wet conditions (Hill et al. 2004) being a stronger indicator of site wetness than J. effusus or J. conglomeratus (Hill et al. 2004). Its reported water level tolerances are from -60cm to +10cm (Newbold and Mountford 1997). J. acutiflorus prefers open situations and moderately acid to acid soils (Hill et al. 2004). It is reportedly readily eaten by sheep and cattle (Wolton 2000, Burke and Wolton 2003), and more readily controlled by cutting. J. acutiflorus has been found to be sensitive to high nitrate levels in wet habitats (Smolders et al. 1997).
4.8 In general terms for rushes, it has been indicated that infestations may be reduced by drainage (Burke and Wolton 2003). These authors also report that applications of farmyard manure may encourage rushes and that pulling of clumped species (e.g. J. effusus/J.conglomeratus) may be effective where plants are young and widely dispersed. Herbicide application via weed wiping was also found to be effective (and efficient) on rushes even when in flower or seed, but only where they were taller than the non-target vegetation.
4.9 Cutting of rushes should be as low as possible for the best results and removing cuttings from the field is desirable, since cuttings can mulch down to create new niches for rush regeneration (RSPB 2007). Cutting rushes again around four to eight weeks after the first cut will help reduce rush cover in the following year (RSPB 2007, Merchant 1995). One cut should be in August (Merchant 1995). Rush re-growth after cutting is reported to be more sensitive to herbicide (RSPB 2007).
4.10 In terms of management, the recent Natural England Evidence Review (NERR05) on the maintenance of UHM (Pinches et al. 2013) revealed little available evidence on rush control on species-rich habitats and a lack of studies relating to their control within UHM. The findings of this review were similar in that while some information was available, none related specifically to UHM or to meadows generally.
4.11 A three-year study by Natural England is currently under way in upper Teesdale considering the cover of rushes within two UHM and two upland pastures under eight different rush management ‘treatments’ including cutting, mulching, weed-wiping, and lime and fertiliser application. The final results of this study are due to be reported in 2019, and may provide more detailed insight into management factors affecting rush growth.
180136 19 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Table 2 Ecological Characteristics of Juncus acutiflorus, J. conglomeratus and J. effusus
Attribute Juncus acutiflorus Juncus conglomeratus Juncus effusus Wind-pollinated (possibly occasionally by Pollination Wind-pollinated Wind-pollinated (possibly occasionally by insects) insects) Seed germination Spring (April-May) Spring Flowering July – September Earlier – begins in May Later – June-August Reproduction Vegetative (rhizomatous), and by seed Vegetative (rhizomatous), and by seed Vegetative (rhizomatous), and by seed Mychorrhiza None None None Tufted – less dense and smaller tufts than Habit Creeping roots – forming large patches Densely tufted Juncus effusus Rhizomatous - densely branching rhizome system Rhizomatous - densely branching rhizome forming dense, below-surface mat, and ability for Vegetative Growth PLANTATT – rhizomes far-creeping system forming dense, below-surface lateral spread. Growth mostly at edge of tussock. mat, and ability for lateral spread Slow radial growth. Hemicryptophyte (wintering buds at soil Hemicryptophyte (wintering buds at soil Hemicryptophyte (wintering buds at soil surface) Life Form surface) surface) Perennial Perennial Perennial Seeds Prolific. Persistent seed bank Prolific. Persistent seed bank Prolific. Persistent seed bank Damp. More tolerant of drier conditions Habitats Wet Damp. Less tolerant of dry conditions than Juncus effusus Moderate resistance (possibly slightly Trampling Moderate resistance greater resistance than Juncus effusus) Unfavourable to cattle and sheep. Unfavourable to cattle and sheep. Avoided by Grazing Readily eaten by cattle and sheep Possibly less heavily grazed than Juncus sheep. Nutritionally poor effusus Resistant to cutting. Requires several cuts to Cutting Readily controlled by cutting reduce vigour. Cutting at ground level, after mid- summer best Drainage Cover reduced by drainage
180136 20 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Attribute Juncus acutiflorus Juncus conglomeratus Juncus effusus Higher (both Juncus effusus and J. conglomeratus Lower (both can reach higher altitudes Altitude can reach higher altitudes where soils not base- where soils not base-poor) poor) Reduced cover with high inorganic fertiliser Nitrates Sensitive to nitrate levels (Wikipedia) application. Effect of Shade 8 - ‘light-loving plant rarely found where 7 - ‘generally in well lit places but also in partial 7 Ellenberg L Score relative illumination in summer is < 40%’ shade’ Effect of moisture 7 - ‘mainly on constantly moist or damp, but not 8 - ‘between 7, and 9 – a wet-site indicator’ 7 Ellenberg F score on wet soils’ pH (soil/water) 4 - ‘between 3 – mainly on acid soils, and 5 – ‘indicator of moderately acid soils, only occasionally found on v acid or neutral-basic soils’ Ellenberg R Score Soil Fertility 2 - ‘between 1 – extremely infertile sites, and 3 - ‘indicator of more or less infertile sites’ 4 - ‘between 3, and 5 – intermediate fertility’ Ellenberg N Score 3 - more or less infertile sites’ CSR Strategy None None Stress-tolerant competitor
180136 21 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Site Selection
4.12 The iterative site selection process resulted in a total of 51 sites being chosen for survey, with previous data in several formats necessitating sub-division into three separate datasets based upon this. Table 3 summarises the selected sites and the data formats to be used in the each separate analysis. Figure 3 provides an overview of the survey site locations.
Table 3 Selected Sites with Rush and Availability of Past Botanical Data (n=51)
Dataset 2x2m Quadrats with Whole site 1x1m Quadrats with %cover Site DAFOR with DAFOR Reference Number of Year 1 Number of Year 1 Year 1 Quadrat (Baseline) Quadrat Pairs (Baseline) (Baseline) Pairs J008 1995 3 J014 1995 3 J022 1995 3 J053 1995 3 J075 1993 3 J101 2002 2 1995 2 J107 2002 3 1995 3 J120 2012 3 2012 3 J128 2002 2 1995 3 J166 2007 J167 2007 J202 2012 3 2012 3 J203 2012 3 2012 3 J204 2012 3 2012 3 J205 2012 3 2012 3 J206 2012 3 2012 3 J207 2012 3 2012 3 J208 2012 3 2012 3 J209 2012 3 2012 3 J212 2012 3 2012 3 J214 2012 3 2012 3 J216 2012 3 2012 3 J217 2012 3 2012 3 J218 2012 3 2012 3 J219 2012 3 2012 3 J220 2012 3 2012 3
180036 22 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Dataset 2x2m Quadrats with Whole site 1x1m Quadrats with %cover Site DAFOR with DAFOR Reference Number of Year 1 Number of Year 1 Year 1 Quadrat (Baseline) Quadrat Pairs (Baseline) (Baseline) Pairs J221 2012 3 2012 3 J223 2012 3 2012 3 J225 2012 3 2012 3 J226 2012 3 2012 3 J227 2012 3 2012 3 J230 2012 3 2012 3 J232 2012 3 2012 3 2010 J260 2010 J261 2010 J264 2010 J265 2007 J270 2010 J271 2010 J283 2012 3 2012 3 2010 J285 2007 J286 2010 J288 2010 J290 2010 J291 2012 3 2012 3 2010 J292 2010 J293 2010 J294 2007 J295 1992 3 J296 2007 J297 1988 1 Number of 28 35 19 Sites Number of Quadrats in 82 102 each Year Total Number 164 204 38 of Samples
180036 23 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Summary of 2017 Botanical Data
4.13 The 2017 field survey was completed in the planned timescale and full data was collected for a total of 51 sites.
4.14 Across all sites and survey methods, a total of 195 vascular plants were recorded in 2017 plus 11 bryophytes. The full botanical species list with common names for 2017 is presented in Appendix 3. Appendix 4 presents a full species list for each subset of data in 2017 and also shows species and frequency of occurrence within each data type, as follows:
Quadrat 1x1m with percent cover;
Quadrat 2x2m with DAFOR; and
Whole site W-walk with DAFOR.
4.15 Appendix 5 presents the full 2017 Field Data from all botanical surveys, soil descriptions, soil analyses results, site notes and total field, upland hay meadow and rush areas (m2) extracted from GIS (digitised from field maps).
Quadrat 1x1m with Percent Cover
4.16 A total of 113 vascular plant species and nine bryophytes were recorded within the 1x1m quadrats in 2017. The most frequently occurring vascular species are listed in Table 4. The average number of species per 1x1 m quadrat in the 2017 data was 19.1, range 7 to 28. In the table, ‘constant’ (usually occurring in 80% of samples or frequency classes V and IV) and ‘preferential’ (usually in 41-60% of samples or frequency class III) are identified for key grassland communities MG3, MG8 and MG6 Lolium perenne-Cynosurus cristata grassland (Rodwell 1992). The latter is included as it is the typical community of ecologically degraded meadows, particularly the MG6b Anthoxantum odoratum sub-community. Positive and negative indicators are also indicated (Table 1).
Table 4 Most Frequent Vascular Species in 1x1m Quadrats (n=153)
Frequency Species of % (n=153) Comment Occurrence MG3, MG6, MG8 Holcus lanatus 149 97% constant MG3, MG8 constant, Anthoxanthum odoratum 138 90% MG6b preferential MG3, MG8 constant, Rumex acetosa 129 84% MG6b preferential MG6, MG8 constant, Cynosurus cristatus 127 83% MG3b preferential Ranunculus repens 123 80% MG8 preferential MG3, MG6, MG8 Trifolium repens 123 80% constant
180036 24 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Frequency Species of % (n=153) Comment Occurrence MG3, MG8 constant, Ranunculus acris 107 70% MG6b preferential Trifolium pratense 105 69% MG3b preferential Plantago lanceolata 99 65% MG3 constant Agrostis capillaris 98 64% MG3 constant MG3, MG6, MG8 Cerastium fontanum 94 61% constant MG3, MG6, MG8 Festuca rubra 94 61% constant Lolium perenne 92 60% MG6 constant MG3b preferential, Rhinanthus minor 75 49% Positive indicator Poa trivialis 73 48% MG3, MG8 constant MG8 constant Caltha palustris 67 44% Positive indicator Euphrasia officinalis agg. 67 44% Positive indicator MG8 constant, Positive Leontodon autumnalis 64 42% indicator Prunella vulgaris 57 37% Juncus acutiflorus 49 32% Target Juncus species
4.17 Holcus lanatus and Anthoxanthum odoratum were the most frequent grasses, occurring in over 90% of quadrats. The most frequent forbs were Rumex acetosa and Ranunculus repens. The most frequent positive indicators were Rhinanthus minor, Caltha palustris, Euphrasia officinalis and Leontodon autumnalis. The target species Juncus acutiflorus was present in only 32% of quadrats - a low incidence of one of the key species for the study, thus limiting the number of samples that could be used to detect changes in frequency and abundance at the species level.
4.18 Looking at target Juncus species in the 1x1m quadrats, the most frequently occurring is J. acutiflorus, present in 49 quadrats (n=153) at an average cover of 15% in these. Where present, J. effusus occurs at 6% cover, but was recorded in just 20 quadrats. J. conglomeratus was recorded in far fewer quadrats (just six) and where present averaged a cover of 4%.
4.19 Five negative indicator species were recorded (Table 1); Anthriscus sylvestris (2 quadrats), Cirsium arvense (1), Rumex crispus (2), R. obtusifolius (1) and Senecio jacobaea (2). All were generally low in percent cover. Heracleum sphondylium, not listed as a negative species but with similar ecological niche to A. sylvestris, was present in 5 quadrats. Overall there were 13 occurrences of negative species in 13 quadrats (8%).
4.20 Across the 153 1x1m quadrats, a total of 26 positive indicator species were recorded. As noted above, the most frequent of these were Rhinanthus minor (occurring in 75), Caltha palustris (67), Euphrasia officinalis (67), Leontodon autumnalis (64) and also Carex nigra (48). Of these,
180036 25 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
C. nigra had the highest average percent cover (at 15%), with C. palustris at 7% and the others lower, indicating the overall low cover values of positive indicators in the habitat.
Quadrat 2x2m with DAFOR
4.21 A total of 135 vascular plant species and eight bryophytes were recorded within the 2x2m DAFOR quadrats in 2017 (n=153). The most frequently occurring vascular species are listed in Table 5. The average number of species per 2x2m quadrat in the 2017 data was 23.7, with a range of 8 to 36. In the table, ‘constant’ (usually in 80% of samples or frequency classes V and IV) and ‘preferential’ (usually occurring in 41-60% of samples or frequency class III) are identified for key grassland communities MG3, MG8 and MG6 (Rodwell 1992). The latter is the typical community of ecologically degraded meadows, particularly the MG6b Anthoxantum odoratum sub-community. Positive and negative indicators are also indicated (Table 1).
Table 5 Most Frequent Vascular Species in 2x2m Quadrats
Frequency Species % Comment (n=153) Holcus lanatus 148 97% MG3, MG6, MG8 constant MG3, MG8 constant, MG6b Anthoxanthum odoratum 145 95% preferential Trifolium repens 139 91% MG3, MG6, MG8 constant MG6, MG8 constant, MG3b Cynosurus cristatus 138 90% preferential MG3, MG8 constant, MG6b Rumex acetosa 136 89% preferential Cerastium fontanum 127 83% MG3, MG6, MG8 constant MG3, MG8 constant, MG6b Ranunculus acris 125 82% preferential Ranunculus repens 121 79% MG8 preferential Festuca rubra 114 75% MG3, MG6, MG8 constant Trifolium pratense 110 72% MG3b preferential Poa trivialis 110 72% MG3, MG8 constant Agrostis capillaris 107 70% MG3 constant Plantago lanceolata 104 68% MG3 constant Lolium perenne 100 65% MG6 constant MG3b preferential, Positive Rhinanthus minor 96 63% indicator Bellis perennis 86 56% Euphrasia officinalis agg. 85 56% Positive indicator MG8 constant, Positive Leontodon autumnalis 84 55% indicator
180036 26 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Frequency Species % Comment (n=153) MG8, constant, Positive Caltha palustris 74 48% indicator Myosotis discolor 66 43%
4.22 Holcus lanatus and Anthoxanthum odoratum were the most frequent grasses, occurring in over 90% of quadrats. The most frequent forbs were Trifolium repens and Rumex acetosa. The most frequent positive indicators were Rhinanthus minor, Euphrasia officinalis, Leontodon autumnalis and Caltha palustris.
4.23 Looking at target Juncus species, none occur in the top 20 most frequent species, J. acutiflorus was the most frequent species occurring in 57% of quadrats, J. effusus in 23% and J. conglomeratus in 5%.
4.24 Five negative indicators (Table 1) were recorded; Anthriscus sylvestris (1), Cirsium arvense (1), Rumex crispus (5), R. obtusifolius (2) and Senecio jacobaea (3). Heracleum sphondylium was present in 8 quadrats (5%). Therefore overall there were 20 occurrences of negative species in 19 quadrats (12%).
4.25 Across the 153 2x2m quadrats a total of 24 positive indicators were recorded, with four appearing in the top 20 most frequent species table: Rhinanthus minor, Euphrasia officinalis, Leontodon autumnalis and Caltha palustris.
Whole Site W-walk DAFOR
4.26 A total of 162 vascular plant species and 10 bryophytes were recorded in 2017 within the whole site DAFOR list collected during the W-walk (Appendix 4). The most frequently occurring vascular species in the dataset of 19 sites used for the analysis are listed in Table 6. The average number of species for a whole site in the 2017 data was 56, with a range of 34 to 84. In the table, ‘constant’ (usually in 80% of samples or frequency classes V and IV) and ‘preferential’ (usually occurring in 41-60% of samples or frequency class III) are identified for key grassland communities MG3, MG8 and MG6 (Rodwell 1992). The latter is the typical community of ecologically degraded meadows, particularly the MG6b Anthoxantum odoratum sub-community. Positive and negative indicators are also indicated (Table 1).
Table 6 Most Frequent Vascular Species in Whole Site DAFOR Data
Frequency Species % Comment (n=19) Agrostis capillaris 19 100% MG3 constant Euphrasia officinalis agg. 19 100% Positive indicator Festuca rubra 19 100% MG3, MG6, MG8 constant Prunella vulgaris 19 100% MG3, MG8 constant, MG6b Rumex acetosa 19 100% preferential
180036 27 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Frequency Species % Comment (n=19) Caltha palustris 18 95% MG8 constant, Positive indicator Cerastium fontanum 18 95% MG3, MG6, MG8 constant MG6, MG8 constant, MG3b Cynosurus cristatus 18 95% preferential Festuca pratensis 18 95% Filipendula ulmaria 18 95% Positive indicator Holcus lanatus 18 95% MG3, MG6, MG8 constant Juncus acutiflorus 18 95% Target Juncus species Juncus effusus 18 95% Target Juncus species MG3, MG8 constant, MG6b Ranunculus acris 18 95% preferential Ranunculus repens 18 95% MG8 preferential MG3b preferential, Positive Rhinanthus minor 18 95% indicator Trifolium pratense 18 95% MG3b preferential Trifolium repens 18 95% MG3, MG6, MG8 constant
4.27 The most frequently occurring grasses recorded at the whole site level were Agrostis capillaris and Festuca rubra. The most frequent forbs were Euphrasia officinalis, Prunella vulgaris and Rumex acetosa, also at 100%. Two target Juncus species were also present in the top 18: J. acutiflorus and J. effusus, both at 95%.
4.28 No negative indicator species were among the most frequently recorded species. However, a total of 8 species were recorded in 2017, namely Angelica sylvestris (9 sites), Cirsium arvense (8), C. vulgare (2), Rumex crispus (8), R. obtusifolius (10), Senecio jacobaea (5) and Urtica dioica (9). Heracleum sphondylium was also recorded (13 sites). Negative indicators were present at all 19 sites with an average of 3.4 species per site. DAFOR scores ranged from ‘rare’ to ‘abundant’.
4.29 A total of 37 positive indicator species were recorded across the 19 sites in the dataset. The most frequent positive indicators were Euphrasia officinalis, Caltha palustris, Filipendula ulmaria and Rhinanthus minor, all occurring in 95% of sites or more (n=19). Other abundant positive indicators included Leontodon autumnalis (89%) and both Carex nigra and Centaurea nigra were found in 84% of sites.
Summary of Other Sward Variables 2017
4.30 A summary of other sward variables is presented in Table 7, giving the results of a range of observations made at the 2x2m quadrat. The following applied across the whole dataset of 2x2m quadrats:
the average vegetation height was 26cm with a wide range from 6.5cm to 60.5cm;
180036 28 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
cover of bare ground was generally very low (0.5%);
litter was also low (0.8%); and
the average cover of all rush species together was 8.8%.
4.31 Percent cover was recorded at the 1x1m quadrat level. J. acutiflorus was recorded in 49 quadrats, at an average % cover of 14.7%. Similarly, J. effusus averaged 12% cover across 20 quadrats and J. conglomeratus 5% across 6 quadrats. In terms of height in the 1x1m quadrats where present, J. effusus and J. conglomeratus were tallest (average 53.2cm and 52cm respectively) and J. acutiflorus had a lower average height of 27cm. J. acutiflorus was found as either occasional or continuous shoots while J. conglomeratus and J. effusus were mainly in tussock forms. These findings fit well with known habits of the species as J. acutiflorus is described as ‘rhizomatous’ and J. conglomeratus and J. effusus as ‘densely tufted’ (Stace 2010).
Table 7 Sward Variables at 2x2m Quadrat Level
Variable No. Sites Average Maximum Minimum Vegetation height (cm) 153 26 60.5 6.5 Bare ground (% cover) 153 0.5 5 0 Litter (% cover) 153 0.8 15 0 All rushes (% cover) 153 8.8 95 0 Rush Species % Cover (1x1m quadrats) No. Sites Average Maximum Minimum Where Present Juncus acutiflorus 49 14.7 70 1 Juncus conglomeratus 6 5 15 1 Juncus effusus 20 12 50 1 Rush Species Height (cm) Where Present Juncus acutiflorus 49 27 49 10 Juncus conglomeratus 6 52 70 29 Juncus effusus 20 53 90 30 Occasional Continuous Rush Growth Habit, Where Present Tussock Shoots Shoots Juncus acutiflorus 49 0 24 25 Juncus conglomeratus 6 5 0 1 Juncus effusus 20 18 1 1
Summary of 2017 Soil Analyses
4.32 Summary tables showing the information on soils which was gathered at the quadrat (Table 8) and site (Table 9) level in 2017 are presented below. In 2017, the average depth to the bottom of the soil A horizon was 14.8cm, and average depth to the bottom of the B horizon was 18.9cm
180036 29 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
with the B horizon alone an average of 4.1cm deep. Total soil cores were on average 19cm deep and the average rooting depth was 12.8cm.
Table 8 Soil Field Observations from 2x2m Quadrats (n=153) in 2017
Variable Average Maximum Minimum Soil Measurements Depth to bottom of A horizon (cm) 14.8 47 4 Depth to bottom of B horizon (cm) 18.9 47 5 B horizon depth (B-A, cm) 4.1 19 0 Depth of core (cm) 19 47 5 Rooting depth (cm) 12.8 35 0 Compaction - depth of penetration by nail (cm) 10.0 16 0 Compaction – pentrometer reading 2.7 4.5 1 Soil Features No. Samples where Present Mottling 103 (67%) Gleying 25 (16%) Podzol 0
Table 9 Soil Chemical and Textural Analysis by Site (n=51) in 2017
Variable Average Maximum Minimum Soil - pH 5.7 6.7 5.1 Soil - available P (mg/l) (Olsen’s) 8.4 23.4 4.4 Soil - available K (mg/l) (Ammonium nitrate) 100.5 266 42 Soil - available Mg (mg/l) 124.6 287 43 Soil Texture No. Sites Clay 6 (11.7%) Clay loam 29 (56.8%) Sandy clay loam 10 (19.6%) Sandy loam 5 (9.8%) Sandy silt loam 1 (1.9%)
4.33 Table 9 summarises the results of the chemical and texture analysis from the bulked samples for each site in 2017. These were collected during the W-walk across the UHM feature. The dominant soil type was ‘clay loam’, occurring at 57% of sites, but clay, sandy clay loam, sandy loam and sandy silt loam were also present (Figure 4). The term ‘clay’ denotes soils classed as medium to heavy while the remainder are considered light soils (Natural England 2008c). All fall within the broad classification of ‘brown soils’ which are characteristic of UHM (Rodwell 1992) and typically have brown to reddish sub-surface horizons, are widespread in the UK, located mainly on permeable materials, occur mainly below 300m and are mostly in agricultural use. Brown soils include ‘typical’ (unmottled subsoil), ‘gleyic’ (mottled permeable subsoil) and ‘stagnogleyic’ (mottled slowly permeable subsoil) subgroups (LandIS 2018). Mottling was found to be present at 67% of sites in 2017, and gleying at 16%, representing the gleyic and
180036 30 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
stagnogleyic categories. These findings reflect brown soils in sub-montane regions (200 to 400m) that experience seasonal to permanent waterlogging with high annual precipitation of 900 to 1800mm and 180 to 200 wet days per year (Rodwell 1992). These conditions are typical of the North Pennines study area.
4.34 The analyses revealed soil pH in the range 5.1 to 6.7, with an average of 5.7. For species-rich neutral grasslands, pH is typically between 5.0 and 6.5 (Martin 2009), with the optimum for grass production considered to be about 6.0 (Walsh et al. 2011). Without lime application to neutral grassland, the pH will tend to fall, especially in soils prone to downward movement of water such as UHM (Rodwell 1992), resulting in net loss of soluble minerals such as calcium carbonate. Available P was low at all sites, from Index 0 (very low) to Index 1 (low) (Natural England 2008b). Available potassium (K) ranged more widely from Index 0 (very low) to Index 3 (high). Magnesium (Mg) levels were also variable, ranging from Index 1 (low) to Index 3 (high).
4.35 Soil compaction ranged quite widely, but field surveyors found that the measurements, taken so locally, did not effectively capture this aspect of the soils’ structure. Penetrometer observations, while broadly mirroring those taken with a nail, were considered equally biased. Furthermore, wet conditions during the survey period meant that soils were very soft. Despite these limitations, the data provides a potential baseline on soil compaction for use in future studies.
Figure 4 Chart showing Soil Texture Categories
Sandy silt loam Clay 2% 12% Sandy clay loam 20%
Sandy loam 10%
Clay loam 56%
180036 31 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Geographic Information
4.36 The 51 fields included in the study totalled 143.4ha, of which 114.9ha was UHM actively cut for hay and 35.61ha was mapped in the field as containing rushes (Appendix 5). Table 10 presents average gradients and elevation data for all sites. Elevations were taken from the most central (or nearest) contour presented on the Ordnance Survey 1:25,000 map. Gradients were calculated from GIS data for nearest highest and lowest contour data and thus are approximate, especially as some sites were very variable in gradient, e.g. undulating valley bottom or strongly domed sites could average out with a gradient of zero despite having a range of steeper gradients present. In the 2017 data (which applies to all sites in all years), gradients ranged from flat to 36%, and UHM sites were located between 135m and 470m above ordnance datum (AOD).
180036 32 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Table 10 Gradient and Elevation Summary for All Sites (n=51)
Variable Average Maximum Minimum Site gradient (% measured from OS map) 12.1 36 0 Elevation (m from OS map) 368.7 470 135
Summary of 2017 Derived Vegetation Data
4.37 Botanical species data were used to calculate coefficients of fit to target NVC vegetation communities (Rodwell 1992) for each site using three 1x1m quadrats and percent cover data (n=51). The MATCH software used only provides the ‘top ten’ best fist to the data (for both communities and sub-communities). The best three coefficients of fit results for each of the 51 sites over two years are presented in Appendix 6 (based upon 1x1m quadrat data).
4.38 In addition, Ellenberg indicator values for Light (L), Moisture (F), Reaction (or pH, R), and Nitrogen (or nutrients, N) (Hill et al. 2004) and CSR values (for competitor/stress- tolerator/ruderal strategies) (Grime 1979) were calculated. Table 11 presents the results derived for the 2017 1x1m quadrat and percent cover data. These variables were calculated for each quadrat (sample) individually (n=153).
Table 11 NVC Coefficients, Ellenberg and CSR Values for Quadrats (percent cover) in 2017
Variable YEAR - 2017 Average Maximum Minimum No. sites NVC Coefficient of Fit (%) (n=51) Fit to MG3a 40 55.7 68.5 44 Fit to MG3b (target UHM vegetation) 11 51.9 55.3 45.6 Fit to MG8 (target UHM vegetation) 51 59.1 70.1 46.5 Ellenberg No. samples (n=153) Values Ellenberg – Light (L) 7.0 7.5 6.3 Ellenberg – Moisture (F) 5.9 7.5 5.2 Ellenberg – Reaction (R) 5.5 6.3 4.1 Ellenberg – Nitrogen (N) 4.4 6.2 2.7 CSR No. samples (n=153) Values CSR_Competitor 2.7 3.47 1.97 CSR_Stress-tolerator 2.7 3.93 1.65 CSR_Ruderal 2.8 3.25 1.58
4.39 In terms of the NVC, all sites surveyed in 2017 presented a coefficient of fit to MG8, one of the target UHM vegetation communities. All fits were acceptable, ranging from 46.5% to 70.1%. Fits were poorer to MG3b, with MATCH only presenting this sub-community in the top 10 for 33
180036 33 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
sites (65%). These results show that all sites have some affiliation to upland hay meadow vegetation, as defined by JNCC (2004).
4.40 Ellenberg values averages were broadly in line with what would be expected in UHM in the North Pennines, with scores as follows:
Light – average score 7 (plant generally in well lit places);
Moisture – average score 5.9 (moist to damp site indicator on seasonally to constantly moist soils, but not wet);
Reaction – average score 5.5 (weakly to moderately acid soils, rarely either very acid or neutral to basic); and
Nitrogen – average score 4.4 (more or less infertile soils to intermediate fertility).
4.41 Similarly, average CSR scores (Grime 2001) for 2017 show a balance between competitor, stress-tolerator and ruderal species across the dataset, and the ranges are also notably similar between each group. The difficult growing conditions in UHM might be expected to favour stress-tolerators, but this is not strongly illustrated by these results, although scores were slightly higher for this group.
Combined Datasets
4.42 Combined datasets were analysed in three subsets of data as set out in Table 12 based upon the original data collection method used, paired with suitable data from the 2017 survey. Some sites appear in more than one analysis (Table 3). The full combined datasets (Year 1 and Year 2) for each analysis group are presented in Appendix 7.
Table 12 Average Number of Species per Sample for Three Data Subsets in Year 1 (Baseline) and Year 2 (2017)
Number Number Number of Species: Data of of Sites Year subset Samples Analysed Analysed Average Minimum Maximum
2002 to 1x1m Year 1 21.6 10 35 Quadrat % 28 164 2012 cover Year 2 2017 19.1 7 28 1988 to 2x2m Year 1 21.9 12 33 Quadrat 35 204 2012 DAFOR Year 2 2017 23.7 8 36 2007 to Site Year 1 41.8 22 65 19 19 2010 DAFOR Year 2 2017 56 34 84
4.43 Field workers in 2017 commented that Juncus acutiflorus seemed to be associated with higher diversity of species and positive indicators. Using the DAFOR quadrat datasets for Years 1 and
180036 34 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
2 combined, a comparison between the number of vascular species (not bryophytes) in samples that did or did not contain J. acutiflorus revealed no significant differences (p>0.05) using Chi-squared test. A similar result was achieved for positive indicators, revealing no significant difference. However, average numbers of positive species were consistently higher where J. acutiflorus was present:
Percent cover:
114 quadrats with no J. acutiflorus: average number of species 20; average number of positive indicators 3;
50 quadrats with J. acutiflorus; average number of species 21; average number of positive indicators 4.4.
DAFOR:
134 quadrats with no J. acutiflorus: average number of species 22; average number of positive indicators 3.6;
70 quadrats with J. acutiflorus: average number of species 22; average number of positive indicators 4.7.
4.44 Quadrat–based datasets prior to 2012 contained no environmental information, but data from Starr-Keddle (2014) did include some information at the whole site level. Tables 13, 14 and 15 summarise the average values for a range of variables in both the baseline year (Year 1) (where available) and 2017 (Year 2). Note: ‘baseline’ averages for Year 1 may encompass a range of dates.
Table 13 Average Values for Measured Variables at Quadrat and Site Level for Year 1 and Year 2
Variable Year 1 Year 2 Quadrat Vegetation Height (cm) 19.6 26.0 Bare ground (% cover) 1.1 0.5 Litter (% cover) 0.1 0.8 Rush (% cover of target Juncus spp.) 4.1 8.8 Depth of soil A horizon 14.8 Depth of soil B horizon 18.9 Soil core total depth 19.1 Rooting depth 12.8 Site Soil pH 5.5 5.7 Available P (mg/l) 13.2 8.4
180036 35 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Variable Year 1 Year 2 Available K (mg/l) 162.3 100.5 Available Mg (mg/l) 124.6
Table 14 Average Coefficients of Fit to Selected NVC Communities for Year 1 and Year 2 (1x1m quadrats)
Variable Year 1 Year 2 NVC Site Fit to MG3a 58.3 55.7 NVC Site fit to MG3b (UHM target community) 52.3 51.9 NVC Site Fit to all MG3 (if not matched to sub-community) 55.9 51.6 NVC Site Fit to MG6b 59.0 58.8 NVC Site Fit to MG8 (UHM target community) 60.2 59.1
4.45 In Table 12, the average number of species in the 1x1m quadrats with % cover has decreased slightly from Year 1 to Year 2, as have minimum and maximum numbers of species. For 2x2m quadrats with DAFOR, the average and the maximum number of species per quadrat have increased slightly while the minimum decreased. For whole site DAFOR datasets, the average, minimum and maximum numbers of species per site have all increased, although this may be an effect of variability in survey methods between all the studies involved.
4.46 With regard to measured variables (Table 13), vegetation height has increased on average by 6.4 cm – a variable very influenced by survey timing and the 2017 survey was conducted late in the meadow growth phase (early to mid-July) and just before hay time. Cover values for bare ground were down, but litter was up. Cover of target rush species at the quadrat level was seen to more than double, but still remained at a low 8.8%. Available P and K were seen to drop noticeably from Year 1 to Year 2.
4.47 Overall the coefficients of fit to all the selected NVC communities (Table 14) including the target MG3b and MG8 are very similar in Year 1 and Year 2, although all values have decreased slightly (Appendix 6). Rodwell (1992) cites the following:
MG3b – number of species per sample (2x2m) = 35 (range 19-43); and
MG8 – number of species per sample = 26 (15-41).
4.48 The average Ellenberg and CSR values for the baseline years and 2017 are presented in Table 15, showing broadly similar scores for each and only a slight increase in species reflecting higher pH in 2017, and a decrease in species associated with soil fertility.
180036 36 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Table 15 Average Ellenberg and CSR Values for Year 1 and Year 2 (1x1m Quadrats)
Variable Year 1 Year 2 ELL Light 7.0 7.0 ELL Wetness 5.9 5.9 ELL pH 5.4 5.5 ELL Fertility 4.9 4.4 CSR_Competitor 2.7 2.7 CSR_Stress 2.7 2.7 CSR_Ruderal 2.8 2.8
Farm Management Questionnaire
4.49 Farmers were asked to provide information on the management of each UHM site as part of the study and the main method of gaining this information was via individual telephone interviews following the proforma set out in Appendix 2. The Farm Management Questionnaire responses are collated in Appendix 5. Overall, the response to the questionnaire was good, with information for a total of 43 sites being gathered (84%) out of a total of 51 sites surveyed botanically.
4.50 49% of fields were reported to have been continuously managed for hay, with 51% not. The management in the past 10 years from farmer responses is shown on Figure 5, indicating that ‘Hay only’ makes up just 11% and that a combination of hay and haylage is the most common management (48%). Hay and haylage together comprise 79% of the crop types. Silage may be cropped in some years but is never the target crop, with no farmers reporting harvesting silage only.
180036 37 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 5 Main Crop Type Harvested Over the Past Ten Years (n=43)
Silage only Haylage or silage 0% 5% Hay only Hay & haylage/silage 11% 5% Hay & silage 11%
Haylage only 20% Hay & haylage 48%
4.51 Information on the duration of hay meadow management for field dry hay was provided by 65% of farmers. Of those who reported making field dry hay, 10% (two sites) had been placed under this management within the past 10 years, but the farmer did not know the previous management history; 71% had been making it for the past 11 to 50 years; and the remaining 19% had been under field dry hay production for at least 50 years (in some cases more than 100).
4.52 The usual shutting up dates are summarised in Figure 6. It can be clearly seen that most farmers (55%) shut up their hay meadows in mid-May, some in early May (23%) and some in late May (18%). Early shut-ups (March and April) are rare (2%).
180036 38 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 6 Usual Hay Meadow Shutting Up Dates (n=43)
Late March - start April 2%
End May Mid - end April 18% 2%
Early May 23%
Mid May 55%
4.53 The usual cutting dates from all responses are summarised in Figure 7. Mid-July is the most popular cutting time, but dates range from mid-May (most likely for haylage) to early September. These dates were reported not to have changed in the past ten years at 81% of sites, but where they had changed (19%), this was related to weather, access difficulties and changes in HLS agreement, with farmers generally reporting that cutting now took place later.
180036 39 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 7 Usual Hay Meadow Cutting Dates (n=43)
Early Sept 3% Mid May Early July Late Aug 4% 4% 10%
Mid Aug 12%
Mid July 31%
Early Aug 16%
Late July 20%
4.54 88% of responses reported spring grazing typically comprised sheep only, while 9% reported using sheep and cattle. The approximate relative proportions of livestock types reported are presented in Figure 8. Swaledale sheep were by far the most popular stock type (81%) for spring grazing, with a range of other sheep breeds including Texel-Lleyn and Texel-Swaledale crosses, Whiteface, Dalesbred, Texel and Mule (Bluefaced Leicester-Swaledale) as well as unreported breeds. Cattle were always grazed in combination with sheep and were Limousin crosses where breed was given.
180036 40 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 8 Spring Grazing Livestock Breed Types (n=42)
6% 2% 2% 6% Swaledales 2% Lleyn x Texel cross 2% Texel x Swaledale cross 2% Whiteface Dalesbred 6% Texel 2% Mule Limousin cross 70% Sheep (unknown breed) Cattle (unknown breed)
4.55 Autumn grazing was more evenly spread between sheep and cattle (20 sites, 47%) and sheep only (18 sites, 42%), with cattle only also being used at a single site (2%). Autumn grazing breed types are summarised in Figure 9. Again, for sites grazed in autumn with sheep, Swaledales are by far the most popular breed. For sites grazed in autumn with cattle, a range of types were reported with Galloway (normal and Belted), Limousin (a continental breed) and other continental crosses being the most popular. Only seven sites were reportedly grazed over winter.
180036 41 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 9 Autumn Grazing Breeds of Sheep and Cattle
Autumn grazing sheep breed type
2% 7% 2% 2% Swaledales 8% Lleyn x Texel cross Texel x Swaledale cross 2% Whiteface Dalesbred Texel Sheep (unknown breed)
77%
Autumn grazing cattle breed type
5% 10% 19%
10% Continental Galloway Limousin cross Limousin Luing Cattle (unknown breed) 28%
28%
180036 42 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
4.56 In terms of stocking, the actual numbers given by the respondents were difficult to interpret into stocking rates as the area being grazed was not easy to define and could encompass several fields as one single grazing unit. Typically, such information for individual fields is not routinely held by farmers, although it is now a requirement under some countryside stewardship options and it might be possible to use these records for future studies of this type. Overall, livestock breed types for spring and autumn grazing were reported to have changed significantly in the past 10 years in 39% of cases (17 sites), not to have changed in 56% (24 sites) and information was not known in 5% (two sites). A wide range of alterations to grazing regimes within the past 10 years were described, including reduced stock numbers due to access difficulties, change from cattle to just sheep, change from sheep to cattle, change to less enclosed grazing, cessation of grazing by fell sheep, cessation of winter grazing and reduction of sheep numbers. Because of the variability in reponses and the interpretation difficulties for individual fields, no common trend in grazing management could be identified.
4.57 Supplementary feeding was reported at 63% of sites (n=43), as summarised in Figure 10. This tallies well with the 26 fields (c.60%) that were not within HLS schemes (which usually do not permit supplementary feeding). Across most sites with supplementary feeding, a combination of feeds were used. Hay was the most frequent component of supplementary feeding practise (38% of all sites), with cake/concentrate was reported at 18% of sites. In Figure 10, ‘NA’ denotes sites where supplementary feeding was not used. Several farmers reported to field surveyors that they bring or buy hay in at least some years which may account for discrepancies between the numbers of farms using hay as supplementary feed and those reporting making hay only on the field. Timing of supplementary feeding was evenly spread between spring (lambing time, 16 sites) and tupping time (usually November/December, 14 sites) and many farms used both. Some sites which used supplementary feed did not state details of timing (six sites). Where respondents indicated a method, hay and haylage were either scattered across the field (55%), placed in a trough, rack or building (29%) or located on dry ground (3%).
180036 43 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 10 Supplementary Feed Types and Proportion of Sites Where Used (n=43)
4% 2% 2%
hay 18% haylage 38% sugar beet sheep nuts N cake/concentrate molasses mineral block/lick silage 22%
6% 4% 4%
4.58 In terms of inorganic fertiliser and FYM applications, Figure 11 shows that 76% of sites received only FYM, while 19% had a combination of FYM and inorganic fertiliser. A further 5% of sites received no inputs. Farmers gave a variety of application rates for inorganic fertilliser, and it was generally applied annually (where stated), in spring to mid-June.
180036 44 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 11 Inorganic Fertiliser and Farmyard Manure Applications (n=43)
No fertiliser or manure Fertiliser & 5% manure 19%
Manure only 76%
4.59 In terms of FYM, the rates of application were reportedly up to 10t/ha (72% of sites), with other application rates described as ‘thin’, ‘light’ or ’sprinkling’ (14%), ‘good covering’ (5%) and ‘not this year’ (one site only) (Figure 12). Some respondents did not say, or were not using FYM. At 56% of sites FYM was used just once annually and a further 26% applied it less than once per year. One site alternated years with inorganic fertiliser and another single site applied FYM more than once per year (‘up to 3 times’). Application timings where reported were in spring (5 reponses), after haytime (15 responses), or winter (8 reponses).
180036 45 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 12a/b Application Rates for Farmyard Manure and Frequency (n=43)
Application rates for farmyard manure
2% 2% 5% 5%
Up to 10t/ha 14% Thin/light/sprinkling Good covering Not applicable Not stated Not this year
72%
Frequency of farmyard manure applications
2% 5%
26% 9% Alternate with inorganic fertiliser 2% Not applicable
Not stated
More than once/year
Annually
Less than once/year
56%
180036 46 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
4.60 Lime was applied at 11 sites (26%). Application rates were given in an array of different measures ranging from tonnes/acre, tonnes/hectare, hundredweight/acre, but have been standardised to t/ha in Table 16. Responses regarding frequency of applications were patchy, but broadly lime appears to be used about every 10 years. Products cited were granulated lime and calcium oxide. Lime applications for 3 of the 11 sites had altered in the past 10 years, all introducing liming for the first time. A fourth farmer would like to use it more as it was perceived to help with rush problems. Previous application rates were not known.
Table 16 Lime Application Rates as Reported for 11 Sites
Lime Application Rate (t/ha) No. Sites “Small amount” (rate not given) 1 Less than 1 3 1 to <2 1 2 to <3 0 3 to <4 1 4 to <5 3 More than 5 2
4.61 Farmers were asked whether the area of rushes in each study field had changed significantly in the past 10 years, and if so, how. Figure 13 shows that there is a strong perception of change with 70% of farmers reporting an increase, ranging from ‘up to 10%’ to ‘75%’ change or ‘lots’. Rushes were reported to be denser, more vigorous, positively responsive to a wet growing season, to have changed toward more sharp-flowered rush and to have encroached more into meadow areas. In responses, farmers associated these changes with:
Land management (mentioned ten times);
Drainage (14);
Climate/weather (9);
Lack of farmyard manure (1);
Entry into HLS (1);
Seed coming in from moor (3); and
Lack of chemical control (2).
180036 47 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 13 Increases in Rushes Reported by Farmers in Past 10 Years (n=41)
7% 2%
30%
17% no change up to 10% increase 10-20% increase 20-30% increase 50% increase 75% increase 7% increased "a lot" 12%
25%
4.62 Just over half (55%) of all farmers responding (25 sites) reported managing rushes, the rest not (n=43). The following methods were used:
hard grazing was used on 6 sites, using either sheep or cattle.
All sites were cut with the hay crop, but additional rush cutting/topping occurred at 7 sites, with removal of arisings occurring at 2, leaving the arisings at 4 and cutting with removal not specified at 1. Timing was always after flowering and rotary toppers, flails or mowers were used.
Weed-wiping occurred at 12 sites, usually in May or occasionally in September. One farmer described using a quad bike and weed wiper with rotating brush to treat re-growth after hay cut, others used a contractor. Roundup (glyphosate) or MCPA (2-methyl-4- chlorophenoxyacetic acid) were the only chemicals mentioned.
4.63 When asked what worked best and why farmers thought this to be the case a range of responses were given, advocating and discouraging chemical treatment, as summarised in Table 17.
180036 48 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Table 17 Farmer Opinions from the Questionnaire Reponses on Rush Management
Question E8 - What Works Best and Why?
1) Mowing early and leaving the toppings. 2) Weed wiping - kills the rushes but leaves the grasses (April/May is the best time for application of weed wipe - early in growing season). Not allowed to use spray, although other farmers say this works better. Combination of approaches. MCPA works, but not allowed to use as it is a blanket spray. Cutting or grazing stops rushes seeding. Cutting tends to soften the rushes - stops them seeding, become softer, then sheep will touch them. Important that the rushes are eaten while green - not good if the flowering heads become black. Cutting “sort of” controls them. Grazing and fertiliser keeps rushes at bay. If cut in summer then weed wiping in spring would have best effect.
Not too much success with weed wipe - not really one at the moment that works (not allowed to use MCPA).
Nothing - no results at all with the weed wipe. Belted Galloway would work best but ground so wet that not able to leave on for too long (they have made a difference on the pasture on the farm). Rushes are controlled in another field by a mixture of weedwipe: agritox + 1 part depitox + another chemical (possibly agritone).
The weed wiping works for the soft rush. “Do the best we can with the situation we have”.
Using a variety of methods works, mowing alone does not work (on other pastures mowing alone makes the rushes come back stronger. Cows pulling it off helps. Weed wipe controls soft rush, but does not work on sharp-flowered rush at all.
Weed wipe works best. Mowing does not help. Weed wiped about 20 years ago but did not seem to kill them. Weed wiping (on the pastures).
“Weed wiping is the only thing that controls them” - intends to do this and has derogation from Natural England to weed wipe in future.
Weed wiping works best - thins them down, but have to keep on top of it. Cutting does not help much.
4.64 In terms of restoration management of the 43 responses, 26 fields were not in HLS management, nine were in HK6 (restoration) measures and six in HK7 aimed at maintenance of existing high diversity. Only three fields were reported to have had restoration work carried out to improve species diversity, and these measures were either not stated or involved wildflower restoration (harrowed then spread with green hay).
180036 49 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
4.65 Finally, addressing drainage, 32 sites reported having drains, nine not having any (although one farmer wanted to dig some) and for two sites the farmer did not know. A summary of the drainage types is presented in Figure 14. Many drainage systems were termed ‘old’ or ‘Victorian’ and were described as up to 150 years old. Some had had modern repairs, but no sites had had modern drains installed. Drains were repaired at 26 of the drained sites, by hand, by rodding, by jetting and by opening up and replacing burst sections. Some farms used a contractor for this. Frequency ranged from when needed to annually.
4.66 A summary of the responses to questions on drainage is presented in Table 18, highlighting sites showing trends in rush cover in the 1x1m % cover dataset illustrated in Figure 23. For the nine sites showing an increase in rushes between Years 1 and 2, drains at seven have been maintained recently (past 10 years). Six responses of the seven showing a decrease or no rush reported managing drainage in the past 10 years, while the seventh took no drainage action. No action was taken at the single site with no change. Overall there is no clear pattern of drainage management associated with changes in rush cover (in the 1x1m % cover quadrat dataset).
Table 18 Farm Management Question Responses on Drainage
Farm Management Questions and Responses: Rush Site Trend Question: Have you Question: Has the field been drained (Figure 23) maintained the drains? / in the past? When?
J075 OLD drains. No more than 50% of them are No. operational.
J101 Stone drains. Yes. Maintained by hand. New drains in c.30yrs ago. Not maintained for past decade.
J107 Stone drains. Yes. Maintained by hand. Not in last decade.
J120 increase Old stone drains. Very rarely.
J128 increase New road put in before site acquired by No. DWT. Pre-1980. Drainage put in under road - probably just reinstated old drains that were there already. No more drains have been added since then.
J166 Stone, tiled, open ditches/drains. Yes. 2014.
J167 Stone, tiled, open ditches/drains. Yes. 2015.
J202 increase Old stone culverts and orange tiles. Bit of Yes, by rodding and repair. Try to modern tubing in repair places. keep the drains clear. 2016.
J203 decrease Old stone culverts and orange tiles. Bit of Yes, by rodding and repair. Try to modern tubing in repair places. keep the drains clear. 2016.
J204 increase Old drains. The field is criss-crossed with lots Maintain by repair, when needed. of drains - nearly all stone, with a few tiled. 2017.
J205 increase Stone drains (can see in the field - sunk). Yes. When burst then repair by
180036 50 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Farm Management Questions and Responses: Rush Site Trend Question: Have you Question: Has the field been drained (Figure 23) maintained the drains? / in the past? When? opening up. 2016.
J208 increase Stone drains underneath. Yes, repair. 2016.
J209 decrease 1 or 2 stone drains, spread out. Yes, what we can, by repairing. c.10 years ago.
J212 no change Tiled. No.
J214 increase Old stone land drains. No. Farmer planning to repair (put plastic in) - weather dependent.
J216 no rush There is some drainage in the field - possibly No. Drains have become Victorian tiled. damaged over time and not been repaired.
J217 decrease Not stated. Yes, by digging up the old drains and putting back in. No new ones. (1-2 are blocked at the moment).
J226 Increase Victorian and probably stone drains as well. Yes. Sometimes dig out if get blocked. c.2015.
J230 increase All tiled drains. Yes, by jetting, rodding and repair. Every year, as needed. 2016.
J232 decrease 3", 4" pipes. Yes, by jetting and repair. Most years.
J260 Some tiled drains, but mainly stone. Yes, by repair. 2017.
J261 Victorian tiled c.5ft deep. Field lies steeply to Yes. (Allowed to maintain in the, free-draining so rushes don't take hold. Agreement). c. 2015.
J264 Old stone drains (could be c.100-200 yrs Yes, by rodding and repair, as old). needed (go round field and fix when can - get a contractor in). c. 2015.
J270 Victorian tiled. Repair frequently. Every year after hay time or in spring before stock have gone out. 2016.
J271 Victorian tiled and stone drains. Yes. Use contractor for maintenance by jetting and repair. 2017.
J283 no rush Victorian tiled and stone drains. Yes. Use contractor for maintenance by jetting and repair. 2017.
J286 Old field drains. Yes, by jetting and repair, when
180036 51 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Farm Management Questions and Responses: Rush Site Trend Question: Have you Question: Has the field been drained (Figure 23) maintained the drains? / in the past? When? needed. 2017.
J288 Old field drains. Yes, by jetting and repair, when needed. 2017.
J291 no rush Victorian tiled. Repair frequently. Every year after hay time or in spring before stock have gone out. 2016.
J292 Victorian tiled; quite a few stone drains Repair frequently. Every year after hay time or in spring before stock have gone out. 2016.
J293 Farmer thinks there might possibly be the No (in a Scheme - need odd drain at the bottom of the field. Dip at permissions to do anything). bottom of field - possibly blocked drain?
J296 Victorian tiled in top part of field; bottom part Yes, by jetting, rodding and of middle of field = stone drains/tiles - hard to repair. 2016. get across this bit.
180036 52 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 14 Summary of Field Drainage Types in Upland Hay Meadows (n=32)
Old stone/ tiled & open ditches 6% Old stone with modern repairs 9%
Old stone/ tiled 85%
Statistical Analysis
4.67 The statistical analysis focused upon whether target species of rush could be seen to be increasing significantly in the data, and whether this could be linked to any environmental factors such as changes in soil nutrient levels or pH. Supporting analyses also looked for significant changes in soil variables, occurrence of positive and negative indicator species and scores derived for the CSR model (Grime 1979) and Ellenberg indicators (Hill et al. 1999, Hill et al.2004). Specifically, significant changes at the site level were sought via pairwise analyses to examine whether individual sites had changed over time.
4.68 The three target rush species were Juncus acutiflorus, J. conglomeratus and J. effusus. In addition, the site selection phase revealed some identification difficulties between J. acutiflorus and J. articulatus in older datasets so the latter species was also included in the analysis in order to capture more data on rushes.
4.69 A summary of abundance of the target rush species is presented in Table 19, for all three datasets. A full summary of all the statistical analyses is presented in Appendix 8, for quadrat and whole site data.
180036 53 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Table 19 Summary of Abundance of the Target Rush Species in Each Dataset in Years 1 and 2
Year - Baseline Year - 2017 Dataset Dataset Variable J. effusus effusus J. effusus J. J. acutiflorus J. acutiflorus J. articulatus J. acutiflorus J. articulatus J. conglomeratus conglomeratus J. conglomeratus J.
No Quadrats 24 1 1 4 26 2 3 10 Total % cover 270 10 1 13 334 2 12 46 Average % cover 11.3 10 1 3.3 12.8 1 4 4.6 Max % cover 70 10 1 10 70 1 10 15 cover (n=28) (n=28) cover Min % cover 1 10 1 1 1 1 1 1 Quadrat 1x1 with % Quadrat No Quadrats 32 3 5 18 38 1 3 13 Median DAFOR category 2 2 1 2 3 3 2 2
(n-35) Max DAFOR 4 2 3 4 5 3 2 4 with DAFOR with DAFOR
Quadrat 2x2m 2x2m Quadrat Min DAFOR 1 2 1 1 1 3 1 1 No Quadrats 14 3 3 14 18 13 13 18 Median DAFOR category 3.0 1.0 1.0 1.0 2.5 2.0 1.0 2.0
(n=19) (n=19) Max DAFOR 5 1 1 3 4 2 1 3 Whole site Whole with DAFOR with DAFOR Min DAFOR 1 1 1 1 1 1 1 1 DAFOR categories: D=5, A=4, F=3, O=2, R=1
Juncus
4.70 To test whether the quadrat data showed any change in abundance of rushes over time, percent cover (28 sites) and DAFOR category (35 sites) were used. Species percent cover and DAFOR categories were found to be non-normally distributed when tested against a normal distribution (Appendix 8) using the Kolomogorov-Smirnov One-sample test with the Lilliefors Test Table (2-tail), as was the species percent cover when log-transformed and tested for normality in the same way. Non-parametric Kruskal-Wallis one-way ANOVA with Conover Inman pairwise comparisons were therefore used. The null hypothesis of the Kruskal-Wallis test is that the medians of all groups (in this case, rush percent cover or DOMIN category) are equal, and the alternative hypothesis is that at least one population median of one group is different from the population median of at least one other group. In ecological datasets, a significant difference in a Kruskal Wallis test needs to be further explored to identify which groups are actually different to one another and if these differences are ecologically meaningful. For example, a difference between rush cover in Site 1 in Year 1 and Site 20 and Year 2 may not be unexpected, however an difference between Site 1 in Year 1 and Site 1 in Year 2 would be of interest. This was done using the Conovar-Inman test to analyse pairwise interactions,
180036 54 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
with those pairwise interactions of interest to this project’s objective (i.e. change in Juncus at one site over time) being reviewed. When applying these tests to each rush species separately there were no overall significant differences in either percent cover or DAFOR categories between Years 1 and 2. In both datasets, grouping all rush species together (to give a total percent cover) for each site also found no significant differences between years. This also resulted in there being no significant pairwise interactions that were ecologically meaningful in the context of this project.
4.71 Mann-Whitney U-tests were also carried out, which assessed each site separately to look at change over time. This is a potentially valid non-parametric test but can produce significant results which are ‘type 1’ errors, not genuine findings when considering hay meadow sites as a habitat type/group (rather than looking only at each site individually). When applied to J. acutiflorus, a single site (J204) did show a significant difference in percent cover between Year 1 and Year 2 (p=0.05). This is only a single result (out of 28 sites) and was not repeated in other more robust analysis approaches. Thus the result is potentially an example of a ‘type 1’ error (where the null hypothesis is wrongly rejected), but in this case is considered to be potentially indicative of a genuine increase in Juncus acutiflorus at this one site. This single significant result does not, however, indicate a trend across all the sites as repeating many Mann Whitney U-tests on individual pairs of sites and then using these results to draw overarching conclusions across the entire suite of sites is not statistically robust.
4.72 To see whether there was any correlation between Year 1 and Year 2 percent cover values for Juncus acutiflorus (for which there was the most data), a Pearson correlation was used. It is a measure of the linear correlation between two variables X and Y and has a value between +1 and −1, where 1 is total positive linear correlation, 0 is no linear correlation, and −1 is total negative linear correlation. This test could identify if, for example, fields with higher rush cover in Year 1 also had higher rush cover in Year 2. The test, however, revealed only a weak positive result (correlation coefficient r = 0.323), which suggests sites with high rush cover in Year 1 tend to have higher cover in Year 2. However, the correlation is largely driven by three outliers (namely sites J204 Q1 and Q3, and J220 Q1) (Appendix 8), and to try to improve the result, these outliers were removed and the analysis re-run, resulting in a stronger correlation coefficient of r = 0.48. Although this would potentially represent a good correlation for ecological data, the new analysis identified two further outlier samples (J204 Q2, J214 Q1) plus three others with large leverage (J209 Q3, J218 Q2, J232 Q1). With each additional data manipulation (e.g. removing samples) the correlation represents the data less and less and where problem samples come from across the dataset (as here) they do not suggest a single site is atypical, but more that the correlation within the data is poor (see final graph in Appendix 8). Therefore the original weak positive correlation result is considered to represent the data best.
4.73 To look at differences in percent cover of a) individual rush species and b) all rush species together, between Years 1 and 2, an analysis of variance was undertaken. Taking a sub-set of 21 sites where Juncus was present in either Year 1 or Year 2 (i.e. discarding any site where there were no rushes recorded in the quadrat dataset), a Kruskal-Wallis one-way ANOVA with Conover Inman pairwise comparison again found no significant differences for percent cover of any individual rush species or all species together between Years 1 and 2 at any sites. In a sub- selection of 16 sites where Juncus was present in Year 1 and Year 2, a similar analysis also found no significant differences. Repeating both sub-set analyses with log-transformation of data also found no significant differences between Year 1 and Year 2. Because of the highly non-significant results, the analysis was not repeated for the quadrat dataset with DAFOR values.
4.74 Changes in individual rush species over time across the whole site DAFOR dataset (19 sites) were analysed using a Mann-Whitney U test (non parametric), a test which analyses the
180036 55 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
difference in median values between Year 1 and Year 2. Highly statistically significant changes were found for Juncus conglomeratus (p=0.001), for the non-target species J. articulatus (p<0.001) and for all Juncus combined (p=0.006). No significant changes were present for the other target rush species, J. acutiflorus or J. effusus, although these species also increased their cover categories (DAFOR), see Figure 15. The result for J. articulatus is included for interest as the species is not one of the target rush species in the study.
Figure 15 Average Rush DAFOR from Whole Site Dataset for Year 1 and Year 2
Competitor Stress-tolerator Ruderal
4.75 To test whether the quadrat datasets showed any changes in occurrence of species classed as competitor, stress-tolerator or ruderal under the CSR system (Grime 1979), a Kruskal-Wallis one-way ANOVA with Conover Inman pairwise comparisons were used. This test found no significant differences at the pairwise level (i.e. comparing each sites’ baseline and 2017 data individually). This was the case for both percent cover (n=28) and DAFOR (n=35) datasets.
Ellenberg Indicator Values
4.76 To test whether the quadrat datasets showed any changes in occurrence of species associated with light, moisture, pH and fertility under the Ellenberg indicator system (Hill et al. 1999, Hill et al. 2004), the Kruskal-Wallis one-way ANOVA with Conover Inman pairwise comparison was again used. This test found no significant differences in each individual sites’ baseline and 2017 data. This was the case for both percent cover (n=28) and DAFOR (n=35) datasets.
180036 56 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
4.77 A single ‘trend’ (or nearly significant result) was found for light at site J207, where a slight increase in species associated with light was observed (p=0.059). Higher values for ‘light’ under the Ellenberg system would reflect species that are less tolerant of shading, suggesting a shorter sward in later data. In theory, such a change could be linked to variation in weather conditions between surveys or to changes in management such as to mowing equipment, cutting timings or grazing regime. However, the field data seem to indicate that vegetation height has actually increased from an average of 9.33cm in the baseline (2012) to 16.5cm in 2017, so other more complex factors may be at play in influencing the vegetation composition.
Positive Indicators
4.78 Positive indicators are a way of considering the quality of the UHM habitat and are defined for UHM (JNCC 2004), although the list presented is not exhaustive. The occurrence of positive indicators is relevant to this study because changes in habitat quality could be linked (directly or indirectly) to rush abundance.
4.79 To test whether the dataset showed any change in occurrence of positive indicator species over time, the quadrat percent cover data (n=28) was used. A Kruskal-Wallis one-way ANOVA with Conover Inman pairwise comparisons found no significant difference between sites in Years 1 and 2 for any individual species. Looking at quadrat percent cover for all combined positive indicator species, the Kruskal-Wallis one-way ANOVA with Conover Inman pairwise comparisons found some significant differences (p=<0.05) and ‘trends’ (p=0.051 to 0.07) between sites in Years 1 and 2. Upward ‘trends’ in positive indicators were noted at sites J120, J209 and J214 with a significant increase at J128. Positive indicators had decreased significantly at site J216.
180036 57 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 16 Change in Site Percent Cover of Combined Positive Indicators between Years 1 and 2 (n=28)
4.80 Change in individual positive indicator species over time across the whole site DAFOR dataset (n=19) were analysed using a Mann-Whitney U test (non parametric), a test which compares the difference in median values derived from all sites between Years 1 and 2. Significant (p<0.05) and highly significant (p<0.001) increases were found for Achillea ptarmica (p<0.001), Alchemilla glabra (p=0.0179), Leontodon autumnalis (p<0.001), Lotus corniculatus (p=0.002) and Potentilla erecta (p=0.026) A significant decrease was found for Rhinanthus minor (p=0.047). In addition, a nearly significant positive ‘trend’ was noted for Lathyrus pratensis (p=0.053).
Negative Indicators
4.81 Negative indicators reflect the quality of upland hay meadows and are defined by JNCC (2004) for the habitat. The occurrence of negative indicators is potentially relevant to this study because changes in habitat quality could be linked (directly or indirectly) to rush abundance. However, they were generally low in occurrence and percent cover within the study datasets and this may affect the statistical power of the analyses.
4.82 Within the quadrat datasets, percent cover (n=28) was tested for change in occurrence of negative indicator species over time using a Kruskal-Wallis one-way ANOVA with Conover Inman pairwise comparison. No significant difference at the individual site level for any species was found. Negative indicators were only recorded at two quadrats within the DAFOR dataset, so occurrence was too infrequent for an analysis to be completed.
180036 58 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
4.83 Changes in individual negative indicator species over time across the whole site DAFOR dataset (n=19) were analysed using a Mann-Whitney U test (non parametric), a test which analyses the difference in median values derived from all sites between Year 1 and Year 2. Significant (p<0.05) increases were found for Cirsium arvense (p=0.027) and Urtica dioica (p=0.025). In addition, a nearly significant increasing ‘trend’ was noted for Anthriscus sylvestris (p=0.058).
Soils
4.84 To test whether the dataset showed any change in pH, Phosphorus (P), Potassium (K) and texture over time, those data from the bulked laboratory analyses were used, meaning that there was a single sample for each site. For the sites included within the quadrat percent cover analyses (n=28), a Kruskal-Wallis one-way ANOVA with Conover Inman pairwise comparisons found no significant difference at the pairwise (site) level, a result that indicates soil conditions have not changed significantly at any sites since the baseline year in terms of these parameters.
4.85 For whole sites with DAFOR (n=19), a dataset that included complete past data on soils from a range of dates, a highly significant difference (p<0.001) was found for soil P which was lower (p=0.002) in 2017, see Figure 17. Some trends are visible for potassium and magnesium but no significant differences were found for these or pH.
180036 59 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 17a/b Soil Phosphorus (P), Potassium (K) and Magnesium (Mg) in Baseline (Year 1) and 2017 (Year 2) for Whole Site DAFOR Data
Correspondence Analysis
4.86 In CCA and DCA (carried out using CANOCO software) axes are generated based upon the data being used and each site or species is placed relative to all others in the dataset. Similar sites or species in terms of their composition and ecological needs would be expected to occur together, and conversely for dissimilar sites or species. On the graphs, the axes represent the variation in the dataset, not specific variables, and the strength of the axes (or the amount of
180036 60 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
variation explained) is defined by ‘Eigenvalues’. Higher values indicate the axis explains more of the variation in the data. Being a multivariate technique, more than two axes are generated.
4.87 For these analyses, plant species names have been shortened to the first three letters of the Genus and Species name, e.g. Anthriscus sylvestris = Ant syl. Appendix 9 contains a full list of species abbreviations. In addition, CANOCO allocates a unique consecutive number to all samples. Appendix 10 provides a full list of the unique numbers and samples. Similarly for environmental variables, Appendix 11 provides a full list of the variables and references.
4.88 For both CCA and DCA, the 1x1m quadrats with percent cover data were used as this is considered the best dataset in the study and contains data for 28 sites (c.55% of the sites visited).
4.89 DCA allows one dataset (Year 1) to be used to generate the axes upon which a second dataset (Year 2) can be placed so that the second dataset can be seen in the context of the baseline and differences examined. In this study, DCA plots were used to look at differences in species composition across the dataset over time. Figure 18 shows the DCA plot of species data over time with species data log-transformed. The species are well spread across the axes (reflecting their inherent differences in ecology) but the samples are bunched in the centre of the plot (appearing very similar in overall composition). Table 19 shows the ordination results for all samples and species. In this analysis (with log-transformed species data), the cumulative percent variability explained by the first two axes is quite low at 19.2%. Thus, axes 1 and 2 show some explanation of the data but do not correlate very strongly. Axes 3 and 4 explain only 5.2% and 3.8% of the variation, respectively, so have even weaker association. Overall, the sum of all eigenvalues is 1.775, an overall low score.
4.90 The log-transformation of the data presented in Figure18 and Table 20 was carried out to even out wide variation in the data (so that patterns if present might be more visible), but may have made results hard to interpret in the context of the samples as all appear very similar (i.e. there is little apparent variation between sites). Therefore the same plot has been prepared with non- transformed data (see below).
4.91 Figure 19 shows the DCA plot with non-transformed data. Again, the sites can be seen to be intermingled with little evidence of difference between years, although 2017 data maybe slightly more clustered (indicating sites have become more similar). Table 21 presents a comparative ordination result for all samples and species where the cumulative variability explained by the first two axes is similar to the log-transformed data. At 19.4%, axes 1 and 2 show some explanation of the variation in the data but do not correlate very strongly. Again, axes 3 and 4 explain only 4.8% and 3.8% of the variation respectively, so have a weak association with the data. However, the sum of all eigenvalues in this analysis is higher than for the log-transformed data at 3.135, giving a better explanation of the data overall and supporting the use of not transformed species data in this study.
4.92 In the CCA, relationships between species, samples and environmental variables were examined. Table 22 presents ordination results for all samples, species and environmental variables. The table presents the eigenvalues for each axis, indicating how much of the variation in the data can be explained by each axis. Cumulatively, axes 1 and 2 explain 55.1% of the observed variation in the species-sample-environment relationship, indicating that environmental variables strongly influence the species found.
180036 61 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 18 DCA Plot of Species Data Over Time (1x1m quadrats with % cover) with Species Data Log- transformed. RED = baseline GREEN = 2017
180036 Natural England 62 March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows Report 2018
Table 20 Ordination Results for Samples and Species for 1x1m Quadrats with Percent Cover Data Log-transformed
Total Axes 1 2 3 4 Inertia Eigenvalues 0.187 0.154 0.092 0.067 1.775 Lengths of gradient 1.976 2.246 1.957 1.613 Cumulative percentage variance 10.5 19.2 24.4 28.2 Sum of all eigenvalues 1.775
Table 21 Ordination Results for All Samples and Species for 1x1m Quadrats with % Cover Data Not Transformed
Total Axes 1 2 3 4 Inertia Eigenvalues 0.35 0.257 0.152 0.117 3.135 Lengths of gradient 3.373 2.898 1.807 2.048 Cumulative percentage variance of species data 11.2 19.4 24.2 28 Sum of all eigenvalues 3.135
Table 22 Ordination Results for All Samples, Species and Environmental Variables
Total Axes 1 2 3 4 Inertia Eigenvalues 0.251 0.115 0.096 0.082 3.135 Species-environment correlations 0.929 0.737 0.656 0.657 Cumulative percentage variance: of species data 8 11.7 14.7 17.4 of species-environment relation 37.6 54.8 69.3 81.6 Sum of all eigenvalues 3.135 Sum of all canonical eigenvalues 0.667
4.93 Figure 20 shows the species plotted with environmental variables. The arrows indicate increasing values for each variable. The diagram places Juncus acutiflorus near the centre, indicating that its occurrence does not correlate strongly with any of the variables considered. However, J. conglomeratus and J. effusus are quite strongly linked to increased gradient (i.e. steeper sites). Also associated with increased site gradient are several positive indicators, Achillea ptarmica, Lotus corniculatus and Potentilla erecta. A. ptarmica may be linked to flushes, while the latter two species may prefer better drained sites.
180036 63 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 19 DCA Plot of Species Data Over Time (1x1m Quadrats with Percent Cover) Not Transformed RED = baseline GREEN = 2017
Mon fon
Ant syl Rx cri Her spo Cera sp
Poa ann Lol per Hol mol Gly fluAgr sto Fes pra
Alo gen Cer glo Dac glo Bro hor Tri rep Alo pra SanCre off pal Per bis Ran rep Ave pra Poa tri Phl pra Dac pur Cx hirt Ste als Rhi min Ver ser Cx dist Vic sep Fil ulm Lot ped Poa sub Ane nem Epi tet Cal pal Card sp Tri dub Bel per Jun art Sag pro Leo aut Sch aru Ran fic Sen aqu Gal uli Tro eur Cyn cri Ran bul Eup off Cer fon pru vul Tri pra Pla lan Cx echi Hol lan HypCen rad nig Myo dis Rx ace Equ pal Tar off Leo his Cx nigr Myo lax Tri fla Jun acu Ver cha Car pra Alc gla Ant odo Ran acr
Sil flo Aju rep Cx lepo Fes rub Con maj Agr can Ach mil Vio pal Cx flac Lat pra Ach pta Ran fla Luz cam Agr cap Des ces Poa pra Cx cary Ave pub Nar stri Sen jac Lol mul Jun eff Cx pani Jun squ Suc pra
Pot ere Cx pilu Lot cor Jun con Cir pal Cx pall -4 6
-1 5
4.94 Increased vegetation height is linked to occurrence of positive indicator Sanguisorba officinalis - a tall perennial plant with an ability to spread vegetatively – that may persist in taller swards
180036 64 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
even under increased competition from vigorous grasses, or when it is not able to set seed. Persicaria bistorta also shows some positive response to vegetation height, possibly for similar reasons.
4.95 Soil P is a major plant nutrient, although it is taken up in relatively small amounts compared to K and N (Natural England 2008b). It has a major influence on grass growth, which can be promoted to the detriment of forbs. UK soils are naturally low in P and levels are typically boosted on farmland by fertilisers and animal manure, leading to a general reduction in sward diversity. Once raised, levels are slow to decline even without further additions. P levels should therefore be low (index 0 or 1), in order to maintain or develop botanical diversity. In this study, soil P levels in 2017 were found to be generally in this range (average=8.4mg/l, range 4.4 to 23.4). In the diagram, increasing soil P is associated with the occurrence of negative indicator Angelica sylvestris and less-so Rumex crispus. No positive indicators are particularly associated with increasing soil P.
4.96 Soil K is essential nutrient for plant growth. It is derived naturally from weathering of clay minerals which are common in UK soils and in the UHM soils of this study. K is much more soluble than P and easily leached from soils or taken up by plants. Because of these characteristics, and because soil levels can range widely, K is not so important a soil nutrient when considering maintenance, restoration (or creation) of botanically diverse swards, although target index values should be 0 or 1. In this study, soil K levels averaged 100.5mg/l (index 1, ‘low’) although they ranged from 42 to 266 (index 3, ‘high’). In the diagram (Figure 20), soil K shows some positive association with two positive indicators, Persicaria bistorta and Anemone nemorosa, but otherwise notable species associations were limited.
4.97 Increasing soil pH shows a weaker association with the species data than other variables. However, a relationship is apparent with four positive indicators Caltha palustris, Dactylorhiza purpurella, Euphrasia officinalis and Leontodon autumnalis. Note that increasing pH indicates more base-rich conditions so these species may reflect this preference. Conversely negative associations with alkalinity can be seen for Potentilla erecta, Succisa pratensis, Centaurea nigra and Leontodon hispidus in the opposite quadrant of the diagram (together with several other more acid-loving species including several Carex species and Juncus squarrosus). C. nigra and L. hispidus have known positive associations with base-rich soils (Grime 1979) so other factors may be a play influencing the occurrence of these species, such as drainage.
4.98 Elevation shows a positive relationship with positive indicators in the second quadrant of the diagram: Carex flacca, Trollius europaeus, Silene flos-cuculi, Caltha palustris and Carex nigra all appear to be associated with higher sites. Other indicators with a weaker association to this variable are positives Euphrasia officinalis, Leontodon autumnalis and Alchemilla glabra, and negative indicator Senecio jacobaea.
180036 65 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 20 CCA Plot of Species and Environmental Variables
180036 66 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 21 CCA Plot of Samples and Environmental Variables, where Juncus acutiflorus and Total Rush Increased
180036 67 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
4.99 In order to remove the influence of sites where rush was not present or not abundant on the data analysis and interpretation, a sub-set of samples was selected where Juncus acutiflorus and total rush occurred with 5% or more cover in either baseline (Year 1) or 2017 (Year 2). Figure 22 presents a graph showing the percent cover (in 1x1m quadrats) for J. acutiflorus in Years 1 and 2 for all 28 sites within the 1x1m quadrat percent cover dataset. J. acutiflorus was the most frequently recorded rush species so merited examination on its own. Figure 23 shows percent cover (in 1x1m quadrats) for all rush species in Year 1 and Year 2. Taking all rushes together allowed a few more sites to be examined.
Figure 22 Juncus acutiflorus Percent Cover in Year 1 and Year 2 (n=28)
Juncus acutiflorus
50.00
45.00
40.00
35.00
30.00 Year 1 25.00 Year 2 20.00
15.00
10.00
5.00
0.00 J101 J107 J120 J128 J202 J203 J204 J205 J206 J207 J208 J209 J212 J214 J216 J217 J218 J219 J220 J221 J223 J225 J226 J227 J230 J232 J283 J291
180036 68 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 23 All Juncus Percent Cover in Year 1 and Year 2 (n=28)
Jucus Total Cover
50.00
45.00
40.00
35.00
30.00 Year 1 25.00 Year 2 20.00
15.00
10.00
5.00
0.00 J101 J107 J120 J128 J202 J203 J204 J205 J206 J207 J208 J209 J212 J214 J216 J217 J218 J219 J220 J221 J223 J225 J226 J227 J230 J232 J283 J291
4.100 In the Juncus acutiflorus dataset, a total of 21 sites contained the species in one or other year, and in the total rush dataset 24 sites contained one or more of the target rush species – see Table 23. Sites where the same trend was seen in J. acutiflorus and total rush graphs were highlighted within CCA plots to examine potential environmental factors in the changes detected in the data. Note that all the data shown in Figures 22 and 23 has been tested for statistically significant differences between site values over time and was found not to be significant. This means that the visible differences (even the apparently dramatic ones, e.g. J204 and J220) are most likely to have occurred by chance.
Table 23 Change in Rush % Cover between Year 1 and Year 2
Categories of change in Rush No sites (n=28) % cover J. acutiflorus (Figure 22) Total rush (Figure 23) No change - not present 7 4 No change - Y1 to Y2 2 1 Increase - None present Y1 3 5 Increase - from Y1 to Y2 8 12 Decrease - None present Y2 2 2 Decrease - from Y1 to Y2 6 4 Total 28 28
4.101 Figure 21 presents a CCA diagram showing sites where Juncus acutiflorus and total rush have increased with the environmental gradients provided by CANOCO. Looking at site J204 where a significant increase in J. acutiflorus cover was seen over time, samples were seen to move toward the centre of the diagram, broadly in the direction of decreased elevation. While
180036 69 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
elevation obviously has not changed, climate conditions could alter, e.g. due to climate warming, in effect creating conditions associated with lower altitudes.
4.102 For the other sites showing non-significant changes over time, movement of samples from baseline to 2017 took a range of directions. For J120 and J214 there might be some tentative indications of an increase in soil parameters (fertility and pH) and height over time (Figure 24). Sites where Juncus acutiflorus and total Juncus were more than 5% cover in one year and saw an increase in cover were J120, J204, J214, and J226, highlighted on Figure 21. Sites where J. acutiflorus and total Juncus were more than 5% cover in one year and saw a decrease in cover were J209, J217, J218, J220, J232 and J219, shown in Figure 24. Site J220 shows the most notable change from Year 1 to Year 2, with rush decreases (Figures 22 and 23) associated with increasing soil pH and soil P, as indicated by the environmental gradients displayed on Figure 24.
Figure 24 CCA Plot of Samples and Environmental Variables, where Juncus acutiflorus and Total Rush Decreased
5857 64 56 92 1.0 Veg Height LEGEND 63 + Baseline year 161 160 + 2017 Soil K 136 62 78 WHITE = J209 91 Soil P
144 35 YELLOW = J217 142 37 77 BLUE = J218 143 109 140 139 133 GREY = J219 89 36Soil pH95 125 137 145 132 120 61 158 ORANGE = J232 135 105 81 82 107 157 86 104 GREEN = J220 79 9093 83106 53 80 94 48 43 162 119 41 97 103 42 21 19 117 159 123 16 96 11 30 22 85 54 20 98 124 101 153 29 99 14 75 15 76 88 118 12 47 74 18 60 148 49 66 59 127 122 154 73 44 67 121 13 65 108 45 17 138 31 156 113 110 52 55 71 51 76 116 46 130 128 50 8 149 134 126 87 72 26 27 70 68 9 33 141 147 15528 69 152 10 34 32 84 2324 131 102 25 163 115 100 112 150 Elevation 111 129 1 164 2 38 34 40 5 151 146 39
Gradient114 -1.0
-1.0 1.0
180036 70 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Agronomic Assessment
4.103 The agronomic assessment explores the farm business and farm economic impacts of rushes in upland hay meadows. It is based on an analysis of responses to Sections H, I and J of the Farm Management Questionnaire (Appendix 2). Further discussion and analysis, integrating responses from other parts of the questionnaire and additional evidence from farm economic and cost data, and also from relevant literature, is set out in Chapter 6.
Hay Yield
4.104 Average hay yield across the sites is estimated to be 4.24 t/ha. This is based on estimated bales and tonnages, using the farmer responses, divided by the recorded area of hay meadow. The analysis resulted in a wide range of estimated yields, but 84% of responses were within the range 2-7 t/ha, with 69% in the 2-5t/ha bracket, see Figure 25. This dovetails with the averages used for agri-environment scheme payment calculations (English Nature/Natural England WES - 3.75t/ha; DEFRA NELMS - 5t/ha). It is important to note that the yields are estimated; the extremes in particular need to be treated with caution.
Figure 25 Estimated Hay Yield (t/ha) Based on Farmer Responses and Recorded Area of Hay Meadow (n=40)
4.105 The majority of farmers (69% or 29 responses) stated that yields have not changed significantly over the 10 years, but a sizable minority (19% or 8 responses) reported changes, with four stating an increase, one stating a decrease and three stating variability in yields.
4.106 There was a variable response when farmers were asked to compare the hay yield of the site with similar fields without rushes on the farm. A total of 38% of respondents were unable to say one way or other, due to reasons such as all fields on the farm being affected by rushes, or the variety of factors influencing yield aside from the presence of rushes (e.g. “Only other upland hay meadow fields without rushes are on alluvium so perform very differently and are a lot more productive for range of different reasons”. 48% (20 responses) gave a quantitative comparison; of these 50% indicated no difference or a decrease of less than 10% in fields affected by rushes
180036 71 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
compared to rush-free fields, and the remainder estimated a 10-50% decrease, see Figure 26; the average decrease was 17%. The remaining 14% of responses stated that the main impact was on the quality of the hay as opposed to the yield (e.g. “Yield is similar, it's the quality that's not as good”).
Figure 26 Estimated Difference in Hay Yield Compared with Similar Field on Farm without Rushes (n=20)
Hay Quality
4.107 A total of 46% of responding farmers described the hay quality from their site as excellent or good, with 27% describing it as fair, and 22% describing it as poor. The balance stated that the quality was variable. See Figure 27.
180036 72 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 27 Description of Current Hay Quality from Field (n=41)
4.108 A significant majority of farmers (88%) felt that rushes affected hay quality in terms of its feed value, with just 10% saying that it did not, and one who was unable to say. When asked how rush presence affects feed value, most (85%) stated that it affects the palatability of hay and/or palatability in combination with other elements, with a minority citing energy and nutrition only, see Figure 28 (e.g. “Palatability - stock don't eat it. Fed to the cattle only (not good for feeding to the sheep), they pick through it and what's left is burnt” and “Palatability - too sour”). Juncus acutiflorus, in particular, was regarded as unpalatable to sheep.
Figure 28 Impact of Rush Presence on Hay Quality in Terms of Reduced Feed Value (n=42)
180036 73 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
4.109 Most farmers felt that rush presence in hay also resulted in wastage of hay by livestock (77% of those able to respond, or 30 responses), see Figure 29. Some (36% or 14 responses) provided quantitative estimates of wastage, with this varying from less than 10% up to 50%, with the average being 27%. This waste was either trampled or, if dry, used as bedding on some farms (e.g. “Could be 50 out of 75 bales that get eaten, the rest are largely left and are used for bedding”). A minority (23% or nine responses) did not think rushes resulted in wastage.
Figure 29 Impact of Rush Presence in Terms of Wastage of Hay by Livestock (n=39)
4.110 Rush presence can affect hay quality in other ways according to just under a third of farmers (32% of those able to respond, or 13 responses), with no other impact according to the remainder. The additional impacts cited included more muck or soil in the hay crop, more drying required, and restrictions on the timing of the hay cut and hence hay quality. See Figure 30.
180036 74 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 30 Other Impacts of Rush Presence on Hay Quality (n=40)
4.111 Most farmers take haylage or silage from the field (93%) as an alternative to hay; only a minority take silage. A couple of farmers made ‘wrapped hay’ (“drier than haylage”), with only one stating he only took hay. Where haylage is taken, it is all baled and wrapped in plastic, and typically bales are given between two and six layers of plastic wrap. 33% of farmers (14 responses) said that rush causes spoilage of bales, with 59% (25 responses) saying it did not, and the remainder unable to say. A variety of reasons were given for the spoilage including rushes pushing through the wrap and letting air in (e.g. “creates air in it - get white dust - makes it inedible”, “have started using more wrap now as rush can push through the wrap”) and rushes bringing muck into the bale.
Other Impacts
4.112 Just under half the farmers (49% of 20 responses) identified other agronomic or knock-on impacts of rushes in hay meadows. The range of impacts included a need to use/buy-in alternative forage, less livestock kept and/or grazing available, an adverse impact on livestock health and condition, lower liveweight gain by livestock, a need to use more plastic bale wrap, and risk of spreading rush seed to other meadows. See Figure 31.
180036 75 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 31 Other Agronomic or Knock-on Impacts Arising from Rushes in Hay Meadows (n=41)
4.113 A range of additional information was provided by the farmers at the end of the survey, see Table 24. This provides an interesting commentary on the perceived causes of rushes in UHM and their farms, potential management solutions (notably liming, but also cutting and addition of FYM), the perceived impact of agri-environment schemes, and the agronomic and farm business impacts. A benefit of rushes, in providing shelter for lambs, was mentioned by a number of farmers. However, it was not clear whether they meant rushes specifically in UHM, or more generally across the farm, where more sheltering tussocks (e.g. of Juncus effusus) are more likely to develop than in annually cut UHM. Within meadows, uncut flushes rush may retain some structure that could have some shelter benefits for lambs.
180036 76 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Table 24 Additional Information Provided by Farmers
Rushes have increased across ALL of the farm. Last few summers have been very wet.
Lack of drains (need to be more) and wetter climate are the main causes. Last few years in particular have seen an increase in rushes
The main reason for more rushes is poor quality soil as slag, lime and plenty of fertiliser are not allowed. Poor drainage and wet winters don't help.
Rushes like wet, acidic ground.
Interested to know: results from other areas of UK, impacts from wetter winters, whether rush links to changes in lime use since its more regular application in 60s and 70s, whether a small amount of fertiliser (especially P and K) would help productivity, bearing mind a really lush sward not desirable because it takes too long to dry out.
Field would benefit from liming (from a farming point of view).
Lime - raises pH = more grass off = better for the wild flowers.
Lime and fertiliser is needed.
Cutting keeps on top of the rushes - sweetens field and then FYM manages it. Weather is the problem - wet in winters and most summers now - good for rushes.
ESA making land full of 'condition' - rushes don't like lots of nutrients. More management of the fields is needed and more FYM added. There have been 2-3 wet winters recently - rushes have got established. No rushes in the field before joined the ESA scheme in 1992.
Prescriptive approaches of HLS and CS (CS worse) - not working well. Lots of rushes on the pastures but not on J230 and J296 - these are the best for hay on the farm. Have had to decrease cattle on the farm by a third. Increasingly difficult to farm - spread muck etc. due to the weather - wetter and less frost. Grasses can't compete with the rushes.
Growing seasons are variable - good and not so good.
Forage similar, but more wastage. A wagonload of hay is bought in every year for the whole farm - don't want to put rushy hay on fields as will spread seeds.
Hay is bought in for the sheep, rushy bales tend to go to the Galloways (cattle).
Sheep will eat off the sharp-flowered rush over winter, then the rushes are back in summer.
Only good thing is that rushes provide shelter for lambs in spring. If rushes are big thick tussocks then no use for anything. Thinning out is better for ground-nesting birds and biodiversity better.
180036 77 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
5. LIMITATIONS
Literature Review
5.1 The literature review found that there was limited autecological information for the three target rush species Juncus acutiflorus, J. conglomeratus and J. effusus. Biological Flora for the British Isles reviews were completed for J. conglomeratus and J. effusus in 1941 (Richards and Clapham 1941a and b). Studies involving the species within an UHM setting have been few, and what relevant evidence does exist regarding the efficacy of management measures is sometimes conflicting, either in its conclusions or with the objectives of UHM management. Most studies refer only to J. effusus.
Site Selection
5.2 Site selection had to be completed in a short timescale to allow for the field survey to take place before hay time (mid-July). Therefore, the selection criteria had to be based upon existing data that was available at the outset of the project. Initial reviews of available data did not deliver sufficient sites, due to a lack of sites with quadrat data for target rush species in two or more surveys over time, so the threshold for inclusion had to be lowered to include sites with rush in only one previous dataset, e.g. ‘new’ sites from Hamilton et al. 2014. The botanical data for these sites was robust and quadrats could be accurately relocated, but is only five years old.
5.3 Necessary subdivision of the data into three datasets for the analysis will have weakened the analysis because all analyses contain less data.
Field Survey
5.4 The field survey timescale was dictated by the start date of the project (mid-June) and the need to complete the data review to select potential sites for inclusion in the study. In addition, it was necessary to complete the field survey before hay cutting commenced from mid-July.
5.5 The field survey itself was completed within prime season for botanical survey, during two weeks from 3rd to 13th July 2017. However, this timescale was later than ideal for the farmers because the meadows were at the peak of their growth and, therefore, the surveyors would potentially cause most harm to the crop by walking on it. While not a limitation for survey quality, there was concern and anxiety from some farmers over potential damage to their crops and this should be a consideration in planning future work in this habitat.
5.6 Weather conditions for the two-week survey were generally acceptable, but several very wet days were encountered and the vegetation and soils were affected by this. Weather in North England in July 2017 was on average 0.7°C warmer than the 1961 to 1990 average, with 104.2mm of rainfall representing a 150% anomaly. There were also 6.6 more days with more than 1mm of rain 7.
7 https://www.metoffice.gov.uk/climate/uk/summaries/2017/july/regional-values
180036 78 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
5.7 While those data collected from vegetation and environmental recording including soil sample collection in wet weather remain robust, the soil surface was very soft and compaction measurements are considered to be potentially affected. Because there is no previous data on compaction no analysis was completed, but this factor should be considered if these data are to be used in future analyses.
5.8 There were issues with relocating fixed quadrats in grassland. Baseline data used in O’Reilly (2010) (and the AEMA dataset more widely) was collected from fixed quadrats, but accurate relocation of the exact 2x2m quadrats from hand drawn maps with pacings and bearings was unlikely. Previous studies (including Hamilton et al. 2014) found relocating buried metal plates with a metal detector ineffective, especially in long grass and wet conditions, and so this method was not used. Re-location problems will affect the accuracy of analyses, and are highlighted for three sites out of 28 from the 1x1m quadrat with percent cover dataset and ten sites from the 2x2m quadrat with DAFOR datasets. Nonetheless, location details are still likely to place the quadrat in a similar area of the field.
5.9 Even where high-accuracy GPS was used to fix the quadrat locations in earlier studies (Hamilton et al. 2014) there is still potential for quadrat location to creep slightly, e.g. in long grass. All quadrats previously fixed with high-accuracy GPS seem likely to encompass a large proportion of the same vegetation as in previous data, unlike the quadrats relocated with pacings and bearings only, which will take the surveyor to the same part of the field but may not result in the exact same area of vegetation being re-sampled.
Farm Management Questionnaire
5.10 Only 43 responses were completed out of 51 sites visited, so the dataset is incomplete and cannot be robustly extrapolated to represent all the sites surveyed. This represented a return rate of 84%. The content of responses also varied and respondents did not always answer all questions, or provide detailed enough information for agronomic analyses to be completed.
Statistical Analyses
5.11 Rushes were not detected in all (or even most) quadrats. Even though site selection aimed to select fields with quadrat or site data containing one of the target Juncus species, the field survey found that quadrats did not always contain Juncus even in fields where rushes were quite abundant. Juncus occurrence seemed to be patchy and possibly variable from year to year making it difficult to capture changes in the species occurrence within the quadrat-based analysis.
5.12 In terms of species, it should also be noted that older studies often appeared to conflate Juncus acutiflorus with J. articulatus, whereas more recent work separated the species in all cases. It is possible (likely even) that the emergence of a significant difference in J. articulatus is related in part to the species being separately identified in later studies rather than to an actual increase in extent. It is also possible that J. conglomeratus may also have been affected in a similar way, although this can not be detected in the data. These limitations do not affect conclusions drawn regarding all Juncus combined.
Quadrat Size
5.13 The relatively small quadrat size and limited number (three per field) compared to large field size was considered an important influence on the study. This size was fixed by the methods used previously in order to allow statistical analyses over time. Quadrats only reflect a very
180036 79 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
small proportion of the total field area, so may not detect changes in abundance of a single species (or group of species) very effectively, especially where it is patchy or has low cover. Also, because the quadrat dataset is highly variable, standard deviations on the means are very high, making detecting change very difficult, again especially in species that are patchy and not dominant overall, like rushes.
Quadrat Location
5.14 For previous datasets, quadrat locations had been selected for different purposes, mainly to monitor the effectiveness of conservation management measures, e.g. under CS options, and for recording diversity and conservation value. For these purposes, a survey may aim to encompass the diversity of vegetation within a site by selecting a quadrat location in each different area of the field, or to provide unbiased quadrat locations by placing them equidistant along a line. Neither approaches were targeted at monitoring changes in an individual species (or a species group) such as rushes over time. For this purpose, more suitable methods might include: collecting quadrat data along a transect across an ecological gradient or vegetation boundary; taking many more frequent randomised quadrats recording fewer variables; or mapping species extent.
Methods
5.15 For data sourced for the whole site DAFOR analyses, it should be noted that a range of different methods were used to compile the original dataset, including indicator species only surveys (Starr-Keddle 2014). When selecting sites for this study, only those with ‘full data’ or similar were included. However, there was insufficient information to determine whether these species lists included just the hay meadow (mown) feature (as in this study) or wider areas including, for example, species-rich banks.
Dates
5.16 Baseline dates encompassed a range of years and the additional variability this introduced to the analysis may have affected the results and made rush changes more difficult to detect. The post-hoc Convar-Inman pairwise analyses would have been less affected by this constraint, however. Furthermore, degrees of freedom were low because only two years were used in the study.
180036 80 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
6. DISCUSSION AND CONCLUSIONS
6.1 This study aims to further an understanding of the perceived increase in Juncus (rush) species in species-rich UHM. To this end, the following questions have been asked of the data:
Is the sample species-rich upland hay meadow?
Can we accurately quantify the extent and recent spread of rushes?
Can hydrological conditions and management factors be identified that increase the risk of rush infestations?
What is the impact of rushes on forage production and quality?
Species-rich Upland Hay Meadow
6.2 Does the study represent species-rich UHM? A total of 51 sites were included in the study. Farmers who responded to the questionnaire (n=43) reported that 48% of fields have been managed continuously for hay, of which 90% had been making field dry hay for more than 10 years. This data indicates that the study has predominantly targeted appropriate UHM sites under active hay meadow management.
6.3 In terms of their species-richness, the 2017 data suggests that, across the sample, these sites had an average of 19.1 species per m2, 23.7 species per 2x2m quadrat and 56 species per site. Rodwell (1992) reports 23 species per 2x2m sample for MG3a, 35 for MG3b (target UHM community) and 26 for MG8 (target UHM community). The average number of species per 2x2m sample in the study therefore lies at the lower end of this spectrum, but ranges from 8 - 36 species/sample indicating that the sample encompasses some species-rich sites.
Quantifying the Extent and Spread of Rushes
6.4 A majority (70%) of the responses to the Farm Management Questionnaire reported an increase in rushes on the meadows, and the extent of increase reported ranged from 10% to 75%, based on farmers’ estimates. Farmers also reported rushes to be denser and more vigorous, positively responsive to a wet growing season, to have changed more to Juncus acutiflorus and to have encroached more into meadow areas.
6.5 To quantify the extent and recent spread of rushes, statistical analyses compared individual rush species and all rushes together over time within each dataset. Across all rush species combined (i.e. Juncus acutiflorus, J. articulatus, J. conglomeratus and J. effusus) a significant increase in extent (p=0.006) was detected over time within the whole site DAFOR data (19 sites). Highly significant changes (p<0.05) were detected for J. conglomeratus (p=0.001), and for the non-target species J. articulatus (p<0.001). No significant changes were present for the more abundant J. acutiflorus or J. effusus, although these species also increased their cover categories (DAFOR). These findings should be regarded with some caution due to small sample size (19 sites) and other limitations described earlier in this report. Quadrat data (% cover and DAFOR) did not show any significant changes in individual rush species or all rush species over time, even when just sites with rushes present were selected. However, many individual sites did show small insignificant increases (Figures 22 and 23).
180036 81 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
6.6 A positive correlation (r=0.48) was found between % cover of Juncus acutiflorus in Year 1 and Year 2, indicating that sites which had high rush cover in Year 1 had high rush cover in Year 2, but the variability was also high and several outliers had to be removed to obtain the result meaning the results did not represent the full dataset.
6.7 Field workers in 2017 commented that Juncus acutiflorus appeared to be associated with higher species diversity and more positive indicators. A comparison between the number of vascular species (not bryophytes) in samples that did or did not contain J. acutiflorus revealed no significant differences (p>0.05) using Chi-squared test. A similar result was achieved for positive indicators, revealing no significant difference. However, numbers of positive species were higher (on average) where J. acutiflorus was present in both % cover and DAFOR datasets. Significantly different or not, there is a need for bespoke site-by-site management prescriptions so that targeted rush management does not impact negatively upon floristic diversity in UHM.
6.8 Overall, the statistical results did not show conclusive evidence for an increase in rush cover in the UHM studies, although some results may hint at change. Data was difficult to analyse because it had to be sub-divided by collection method, variability was high within sub-sets and quadrats did not always contain rush. Small sample number (e.g. whole-site DAFOR), small quadrat size and low sampling intensity versus large field size, high variability and wide ranging baseline dates were also considered to influence the study and affect confidence in results. Quadrats may not effectively detect changes in abundance of a single species (or group of species), especially where it is patchy or has low cover, and where sample size is relatively small. Also, because the quadrat dataset is highly variable, variation around the means and medians are very high, making detecting statistically significant change very difficult. Baseline dates over a range of years added variability to the analysis which may have affected the results and made rush changes more difficult to detect, although the pairwise interactions would be less affected by this.
6.9 In the light of the significant changes detected at the whole site DAFOR level, there is still indication that it may be more effective to detect rush change at the field scale rather than in three 1x1m or 2x2m quadrats. This could include collection of the following information:
Follow a formal W-walk structure with 20 stops recording DAFOR for all species, remaining within the UHM feature (mown area);
Recording percent cover data for all target rush species (including Juncus articulatus) within a 1x1m quadrat at each stop, so that 2017 data can be used for analysis in future (use proforma in Appendix 1); and
Accurate GPS mapping of rush boundaries so that future studies can compare overall areas to 2017 data.
Hydrological Conditions and Management Factors
6.10 The influence of hydrological and management factors on each meadow was considered, using a combination of botanical indicators, soil analyses, community correspondence analyses and detailed review of Farm Questionnaire responses.
6.11 Botanical indicators can be used to detect alterations in the vegetation which can be related to factors such as management, wetting, drying, nutrients and climate. The data was examined for changes in such indicators between the baseline and 2017 data. No significant change in competitor/stress-tolerator/ruderal classes (Grime 1979) or for Ellenberg values for light,
180036 82 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
moisture, soil pH and fertility (Hill et al. 2004) or for positive/negative indicators (JNCC 2004) over time were found. However, on a site-by-site basis, when taking all positive indicators together, some significant differences and trends were detected, namely sites J120, J128, J209, J214 had all gone up in terms of total cover of positive indicator species in 2017, and site J216 had gone down. Looking at positive indicators over time in the whole site DAFOR dataset, significant (p<0.05) and highly significant (p<0.001) differences were found for some species, namely: increases for Achillea ptarmica, A. glabra, Leontodon autumnalis, Lotus corniculatus and Potentilla erecta; a decrease for Rhinanthus minor; and a nearly significant increasing ‘trend’ for Lathyrus pratensis. For negative indicators over time, the whole site DAFOR dataset showed significant increases for Cirsium arvense and Urtica dioica as well as a nearly significant increasing ‘trend’ for Anthriscus sylvestris.
6.12 In terms of soils, the results of soil chemical analyses were available with the species data for the whole site DAFOR dataset, so more complete analysis could be completed. A highly significant (p<0.001) decrease in soil phosphorus (P) was found, but declines in soil potassium (K), magnesium (Mg) and pH were not significant. Available P is considered the most important nutrient affecting sward diversity (Natural England 2008b), naturally limiting grass growth even when N is high. Although both Juncus effusus and J. acutiflorus have been found to be sensitive to elevated N levels (Richard and Clapham 1941a, Smolders et al. 1997), evidence on responses of all target rush species to soil phosphorus levels are lacking.
6.13 DCA showed little evidence of change in community composition between years. Ordination analyses using DCA to look at species composition across the dataset (1x1m quadrat) did not indicate any strong differences in the dataset between years, although non-transformed data appeared to show slight clustering of the sites in Year 2, suggesting slight homogenisation.
6.14 The related CCA examined relationships between species, samples and environmental variables over time. The diagram places Juncus acutiflorus near the centre, indicating that its occurrence does not correlate strongly with any of the variables considered. However, J. conglomeratus and J. effusus are quite strongly linked to increased gradient (i.e. steeper sites) – possibly because if the overall field parcel was steep, rushes might occur at the base of the slope where drainage is poorer. The diagram also suggests a tentative link to decreasing soil P and possibly K, pH and vegetation height.
6.15 Also associated with increased site gradient on the CCA diagram are several positive indicators; Achillea ptarmica, Lotus corniculatus and Potentilla erecta. Increasing soil P is associated with negative indicators Anthriscus sylvestris, Rumex crispus and Heracleum spondylium, and soil K shows some positive association with two positive indicators, Persicaria bistorta and Anemone nemorosa. Increasing soil pH shows a weaker association with the species data than other variables, but a relationship is apparent with four positive indicators: Caltha palustris, Dactylorhiza purpurella, Euphrasia officinalis and Leontodon autumnalis. Note that increasing pH indicates more base-rich conditions, so these species may reflect this preference. No clear patterns of movement were discernable when looking at how selected samples with higher Juncus cover moved within the axes over time, suggesting that conditions across all sites are very variable and high variability may mask trends in the vegetation. Overall, the CCA did not reveal any clear useful relationships between samples and environmental variables over time, even when only samples with rushes present were analysed.
6.16 The Farm Management Questionnaire responses (n=43) also provided information on hydrological and management factors potentially influencing the vegetation of each meadow. However, in view of the lack of conclusive evidence for significant change in rush cover across the datasets and the incomplete nature of the responses, statistical analyses were considered un-founded. Nonetheless, the collated dataset does provide insight into management practices across the study area. In particular, key points relate to the age of drains, the low use of
180036 83 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
inorganic fertiliser, the robust perception of an increase in extent of rush and the efficacy of herbicide as a management tool.
6.17 There was quite a high degree of consistency also in some field management practises, with 96% of farmers shutting up meadows in May; 67% cutting between mid-July and early August (range Mid-May to early September); and 81% of sites reporting no change to this regime. Spring grazing is predominantly with sheep only (81% of sites), while autumn grazing is broadly split between sheep only (42%) and sheep and cattle (47%). Winter grazing is rare and stocking rate information was variably supplied and difficult to interpret. Supplementary feeding took place at 63% of sites. FYM was used at most sites, most commonly applied at around 10t/ha (72%), with additional inorganic fertiliser applied on 19% of these. Liming, using granulated lime or calcium oxide, was carried out on 11 sites, about every 10 years.
6.18 Responses regarding rush extent and change were varied, although the majority reported an increase. A range of reasons were provided including land management, weather/climate, drainage, lack of FYM, entry into HLS, seed sources from off-site and lack of chemical control. Despite this, 55% of farmers (25 sites) reported managing rushes via hard grazing, cutting in addition to hay crop or chemical treatment, and farmers reported best effects with Chemical treatments (using glyphosate or MCPA). In terms of drainage, 32 fields (74%) were reported as having drains but all were described as old tiled or old stone or similar. Of these, 26 farmers (81%) had repaired drains and maintained them by rodding, jetting and opening up, sometimes using contractors for this. No sites had modern drainage.
Impact of Rushes on Forage Production and Quality
6.19 There was considerable variation in responses by farmers to the questions on hay yield, hay quality and other/agronomic impacts. This is unsurprising given the variation in rush presence across the sites and differences in bio-physical and farming circumstances. It is possible, however, to draw out some key findings from the responses to give a sense of the agronomic and economic impacts of rush presence in UHM.
6.20 Estimated average hay yield across the sites is slightly lower than recent averages used by Defra (4.24t/ha compared to 5t/ha), which may relate to the presence of rushes in the sample; 69% of respondents reported yields of 5t/ha or less. However, other factors also influence yield such as shut dates and grazing intensity (Smith et al. 2012). Furthermore, despite the obvious variability in yields, there appears to be a negative relationship (not statistically tested) between the total rush area mapped on site (Appendix 5) and the estimated hay yield, see Figure 32. The trend shows that, as the percentage of Juncus increases towards 80%, hay yield falls from around 5t/ha to 3t/ha. This relationship is broadly what one might expect, although farmers clearly differ in their experience and perception in terms of the impact of rushes on yield.
180036 84 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 32 Relationship between Juncus as a % of Site Area and Estimated Hay Yield (n=40)
6.21 A similar relationship (not statistically tested) is also present in an analysis of the total area of rush mapped on site of Juncus on site and estimated (by farmer) reduction in hay yield compared to a similar field without rushes, see Figure 33. As the percentage of Juncus increases, so does the reduction in yield compared to other, ‘non-rushy’ fields. For those farmers responding, the average reduction in yield was 17%, but this was based upon few sites (n=20), rounded estimates and very variable data and should be viewed with caution. However, the marginal apparent reduction in hay yield with increasing rush cover does make sense logically.
180036 85 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 33 Relationship between Juncus as a % of Site Area and Estimated Reduction in Hay Yield Compared to a Similar Field without Rushes (n=20)
6.22 It is worth noting, however, that the linkage between rush presence and hay yield did not seem to come through when farmers were asked about trends over the past 10 years. 70% of farmers felt that that there had been an increase in the area of rushes over the past 10 years (Figure 13, Appendix 2 E.1), but when asked about hay yields, 69% indicated that hay yields (Figure 25) have not changed significantly over the same period (Appendix 2 H2). It is difficult to know the reasons for this apparent inconsistency, but it is quite possible that that there are three groups of farmers: approximately 30% with no increase in rushes and no change in yield; 40% with a moderate increase in rushes and no significant change in yield; and 30% with a significant increase in rushes and some impact on yield.
6.23 Hay quality is variable across the sites, with almost half of farmers describing it as excellent or good – despite the presence of rushes - and half describing it as fair or poor. As with yield, other factors influence hay quality yield such as shut dates and grazing intensity (Smith et al. 2012), as well as site characteristics. However, when one digs deeper, it is apparent that there is a negative relationship (not statistically tested) between the total area of rush mapped on site and hay quality, see Figure 34. The trend shows that, as the percentage of Juncus increases towards 80%, hay quality falls from just below 3 (good) to between 1 and 2 (poor to fair). Again, this is in line with anticipated results.
180036 86 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Figure 34 Relationship between Juncus as a % of Site Area and Hay Quality (n=39)
6.24 Most farmers (88%) were in agreement that the presence of rushes affected the feed value of hay, with the majority stating that it affected palatability for livestock. Linked to this, a majority of farmers (77%) also agreed that the presence of rushes led to wastage in hay by livestock, with average wastage from estimates amounting to 27%. This was based upon rounded estimates from farmers and very variable data, and should be viewed with caution.
6.25 A third of farmers identified other impacts on hay quality resulting from the presence of rushes, including more muck/soil in the crop, more drying required and reduced quality due to changes in the timing of the hay cut due to rush presence. A third of farmers also felt that rushes cause spoilage of haylage bales, partly due to rushes pushing through the plastic wrap and letting air in.
6.26 Other agronomic or knock-on impacts for the farm business of rushes in upland hay meadows were identified by just under half the farmers surveyed. The main impacts were the need to use/buy-in alternative forage, less livestock kept and/or grazing available, adverse impact on livestock health and condition, and lower liveweight gain by livestock.
6.27 In addition, 60% of farmers reported managing rushes, including hard grazing, rush topping and weed wiping (28% of farmers/sites).
6.28 A summary of the agronomic impacts arising from presence of rushes in hay meadows and how this affects farm businesses is set out in Table 25. It is important to note that not all farmers acknowledged all agronomic and/or related farm business impacts listed, but a proportion did. This proportion ranged from a significant majority (e.g. adverse impact of rushes on feed value of hay) to a small minority (e.g. need to use additional bale wrap when making haylage).
180036 87 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Table 25 Summary of Agronomic and Related Farm Business Impacts Arising from Rush Presence in Upland Hay Meadows
Farm Business Impact
Less Output Extra Costs
Potential Effect of Rushes in UHM Less/poorer Less/poorer and forage grazing available Fewer livestock kept Lower liveweight gain/value of Cost alternative bought-in forage and Extra vet costs medical Extra drying/ tedding costs Rush manage- costs ment
Lower hay yield
Reduced hay quality
Reduced feed value of ‐ hay
More muck/soil in hay ‐ crop
Increased wastage of hay
Impact on timing of hay cut
More drying required
Spoilage of haylage bales
Rush management required
6.29 In order to evaluate the range of potential financial impacts for farm businesses, quantitative feedback from the survey and economic/costings evidence from other sources was used to estimate the average loss/cost of rush presence on a £/ha basis in respect of key impacts, see Table 26. The resulting estimated average loss is £185/ha based on lower hay yield, reduced hay quality and increased wastage. This estimate needs to be treated with caution; some farmers may suffer a greater loss, for example those who have experienced an estimated 50% reduction in yield due to rushes, while other farmers may suffer a lower loss or no loss at all. An analysis of individual farmer responses suggest that the financial loss due to rushes could range from £0/ha to £338/ha (the latter involving an otherwise productive meadow with significant yield loss and reduced hay quality due to rushes). It is worth mentioning that these estimates exclude impacts which are hard to value with the evidence available (e.g. impact on liveweight gain, or additional vet and med costs) so this could exacerbate the loss experienced by some farmers.
180036 88 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Table 26 Estimated Average Loss for Reduced Hay Yield, Hay Quality and Wastage Due to Rushes
Basis of Loss/Cost Impact Calculation Notes Calculation (£/ha) Market price based Average yield of 4.24t/ha x on Nix 2017, ABC average reduction in yield of 2017, Farmers Lower hay Loss in 17% = 0.72t/ha x £80/t (typical 57.60 Weekly (19.01.18, yield market value market price for small bale hay North East prices) in region) = £57.60/ha for good meadow hay Adjusted average yield of Reduced hay Loss in 3.52t/ha x £20/t (estimated 70.40 quality market value reduction in market price for low quality hay) = £70.40 Adjusted average yield of 3.52t/ha x average wastage of Increased Loss in hay by livestock of 27% = wastage of market value 0.95t/ha x £60/t (adjusted hay market price for low quality hay) = £57.00/ha Total estimated average loss for reduced hay yield, quality 185.00 and wastage Rush ABC 2017 Weed wiping management Contractor cost 25.95 contractor cost, cost required excluding chemical
6.30 There is limited evidence from elsewhere on the economic impact of rush, however, AHDB8/EBLEX9 guidance on the management and control of Juncus effusus estimated that a 15% rush infestation in a productive grass sward could reduce output by 1.25t DM/ha/annum, which, if the field is cut for big bale silage on upland in-bye fields, was valued at £192/ha (AHDB, 2013). Later guidance by the same author for Farming Connect in Wales estimated that some farmers have seen combined silage and grazing yields drop by up to 25% following rush infestation reducing output by up to £300/ha, although this is where productive swards have been affected (Cairns 2013).
6.31 Losses of up to £300/ha or more are very significant, where they occur, as they come directly off the bottom line, i.e. farm profit. They need to be seen in the context of average Farm Business Income (a measure of net profit) for Less Favoured Area (LFA) Grazing Livestock farms in the North East and North West regions of England which was £141/ha and £130/ha respectively, in 2015/16 (Rural Business Research, 2018).
8 Agriculture and Horticulture Development Board
9 A division of AHDB
180036 89 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Recommendations
6.32 At the outset, the project aimed to use existing data, plus the results of the field study and literature review, to develop recommendations for better informed and targeted rush control. The results of this study show that the issues around changes in rush extent in UHM are poorly understood at the present time, and more investigation is needed to quantify change and develop approaches to effective rush management in UHM. The study highlights a few key points for consideration when developing future research and advice:
Autecological studies of the target rush species date from 1941, e.g. (Richards and Clapham 1941a and b), since which time additional techniques and methods have been developed which might assist with understanding the species’ interactions with their environment and with other components of the vegetation. Updated autecologies might provide useful insight, and might be useful beyond UHM.
Future methods for monitoring rushes should include but not necessarily adhere to existing data, with future approaches involving mapping and/or transect methods for regularly reassessing rush extent and character. An area of particular interest would be the interface between rushy and grassy vegetation. Rush monitoring should be strongly tied in with detailed management records if the management is to be statistically linked to measured changes in rushes. At present, detailed field by field past management information is not widely recorded and may reside with farmers, if at all.
Upland hay meadows are principally allied to the NVC types MG3 Anthoxanthum odoratum-Geranium sylvaticum (sweet vernal-grass and wood crane’s-bill) grassland and MG8 Cynosurus cristatus-Caltha palustris (crested dog’s-tail – marsh marigold) grassland (Rodwell 1992). Rodwell’s descriptions are based upon 74 samples for MG3, split between two sub-communities, MG3a Bromus hordeaceus sub-community and MG3b Briza media sub-community (UHM ‘proper’); and just 15 for MG8 with no sub- communities. O’Reilly (2011) analysed UHM data from the North Pennines Area of Outstanding Natural Beauty (AONB) in order to clarify grey areas relating to the diversity of UHM vegetation, and suggested some community subdivisions. These better reflect the diversity of the UHM communities of the North Pennines as a product of their edaphic conditions and long-term management, but are not widely used.
6.33 Regarding the last point above, the NVC analysis illustrated that all the study sites had some affiliation to upland hay meadow vegetation, with coefficients of fit to MG8 ranging from 47% to 71% achieved for all 51 sites. 41 sites showed coefficients of fit between 44% and 69% for MG3a, but only 11 sites (with fits between 46% and 55%) for MG3b. However, UHM target NVC communities were not necessarily the best fits for the vegetation. In addition to the wide-ranging coefficients of fit to target communities, species data was shown to be very diverse, reflecting the high level of variety encompassed by the label ‘upland hay meadow’. The application of standard (or limited selection) of management measures to such a varied array of sites is intuitively unlikely to be suitable for all, and may result in ‘perverse outcomes’ for some sites.
6.34 Some other potential considerations are as follows:
Rushes are a natural component of UHM vegetation, growing in conjunction with many typical and positive indicator species. They also have value for livestock and wildlife, such as shelter for lambs, cover for ground-nesting birds and habitats for invertebrates and small mammals. These aspects should all be considered when developing site- specific management prescriptions so that valuable features of upland hay meadows are not lost when targeted rush management is introduced.
180036 90 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Vegetation (and soil) is influenced by climate and pollution and these factors should be considered where possible, including potential effects of climate change, changes to rainfall patterns and increasing trends in atmospheric nutrient deposition.
Better evidence of the agronomic, farm business and farm economic impacts of rushes on upland hay meadows and associated farms would be beneficial. A better understanding of financial costs and benefits would inform the identification of cost- effective measures for controlling rushes on-farm.
180036 91 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
7. REFERENCES
AHDB, 2013. Management and Control of Common (Soft) Rush. AHDB Beef and Lamb.
Atherton, I., Bosanquet, S., and Lawley, M., 2010. Mosses and Liverworts of Britain and Ireland: a field guide. British Bryological Society.
Biological Records Centre, 2017 (website accessed). Online Atlas of the British and Irish Flora. http://www.brc.ac.uk/plantatlas/
Bullock, J.M., et al., 2011. UK National Ecosystem Assessment Technical Report. UK National Ecosystem Assessment, Chapter 6: Semi-natural grasslands. UNEP-WCMC.
Burke, C. and Wolton, R., 2003. Controlling Rushes. Conservation Land Management.
Cairns, I., 2014. Management and Control of Common (soft) Rush. Farming Connect Fact Sheet.
Farming Connect, 2014. Management and Control of Common (Soft) Rush. Fact Sheet (October 2014) www.menterabusnes.co.uk/farmingconnect (accessed on 19/6/17).
Grime, J.P., 1979. Plant Strategies and Vegetation Processes. Wiley and Sons.
Grime, J.P., 2001. Plant strategies, vegetation processes, and ecosystem properties 2nd edition. Wiley.
Hamilton, H.F., Jackson, S.J. and Blackshaw, A.B., 2014. Long term effectiveness of Environmental Stewardship in conserving upland hay meadows in the Pennine Dales. Natural England Commissioned Report NECR138. Natural England.
Hill, M.O., Mountford, J.O., Roy, D.B. and Bunce, R.G.H., 1999. Ellenberg's indicator values for British plants. ECOFACT Volume 2 Technical Annex. Huntingdon, Institute of Terrestrial Ecology. (ECOFACT, 2a).
Hill, M.O., Preston, C.D. and Roy, D.B., 2004. PLANTATT Attributes of British and Irish Plants:Status, Size, Life History, Geography and Habitats. NERC Centre for Ecology and Hydrology.
JNCC, 2004. Common Standards Monitoring Guidance for Lowland Grassland Habitats Version February 2004. JNCC.
LandIS, 2018. Soil Classification System for England and Wales.
Lazenby, A., 1995. Germination and establishment of juncus effusus L.: the effect of different companion species and of variation in soil and fertility conditions. Journal of Ecology, 43, No. 1 (Jan., 1995), 103-119.
Martin, J. P., 2009. Natural England Technical Information Note TIN050 Selecting indicators of success for grassland enhancement. www.naturalengland.org.uk.
Merchant, M., 1993. The potential for control of the soft rush (Juncus effusus) in grass pasture by grazing goats. Grass and forage science.
180036 92 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Merchant, M., 1995. The effect of pattern and severity of cutting on the vigour of the soft rush (Juncus effusus L.) Grass and forage science.
Natural England and RSPB, 2014. Climate Change Adaptation Manual (Chapter 23). www.naturalengland.org.uk.
Natural England, 2008a. Soil Sampling for Habitat Recreation and restoration. Technical Information Note TIN035. Natural England 21 February 2008. www.naturalengland.org.uk
Natural England, 2008b. Soil and agri-environment schemes: interpretation of soil analysis. Technical Information Note TIN036. Natural England 21 February 2008. www.naturalengland.org.uk
Natural England, 2008c. Natural England Technical Information Note TIN037 Soil texture. www.naturalengland.org.uk.
Newbold, C. and Mountford, O., 1997. Water Level Requirements of Wetland Plants and Animals. English Nature.
O’Reilly, J., 2010. Data review examining the reasons for the declining condition of upland hay meadows. A report for Natural England by Ptyxis Ecology.
O’Reilly, J., 2011. An Analysis of Survey Data from upland hay meadows in the north Pennines AONB. Natural England Commissioned Report NECR069. Natural England.
Pinches, C.E., Gowing, D.J.G., Stevens, C.J., Fagan, K., and Brotherton, P.N.M., 2013. Natural England review of upland evidence - Upland Hay Meadows: what management regimes maintain the diversity of meadow flora and populations of breeding birds? Natural England Evidence Review, Number 005.
Richards, P.W., and A. R. Clapham, A.R., 1941a. Juncus Conglomeratus L. (J. Communis α Conglomeratus E. Mey.; J. Leersii Marsson) Journal of Ecology, 29, No. 2 (Aug., 1941), 381- 384.
Richards, P.W., and A. R. Clapham, A.R., 1941b. Juncus Effusus L. (Juncus Communis β effusus E. Mey) 1941b Journal of Ecology 29, No. 2 (Aug., 1941), 375-380.
Rodwell, J.S. (ed.), 1992. British Plant Communities – Volume 3: Grasslands and Montane Communities. Cambridge University Press.
RSPB 2007. Rush Management Information and Advice Note. The Lodge, Sandy, Beds. https://www.rspb.org.uk/
Rural Business Research, 2018. Farm Business Survey Region Reports 2015/16. Rural Business Research.
Smart, S., Goodwin, A., Wallace, H. and Jones, M., 2016. MAVIS (Ver 1.03) User Manual. NERC Centre for Ecology and Hydrology.
Smith, R.S., Sheil, R.S., Millward, D., Simkin, J., and Pratt, S., 2012. Spring grazing in northern hay meadows: influence of the timing and intensity of sheep grazing on the floristic diversity and restorative potential. Defra Science Research Report.
180036 93 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
Smolders, A.J.P., Hendriks, R.J.J., Campschreur, H.M. and Roelofs, J.G.M., 1997. Nitrate induced iron deficiency chlorosis in Juncus acutiflorus. Plant and Soil September 1997, 196, Issue 1, 37–45.
Stace, C., 2010. New Flora of the British Isles. Third Edition. Cambridge University Press.
Starr-Keddle, R., 2014. Upper Teesdale: changes in upland hay meadow vegetation over the past twenty to thirty years – results presented from botanical surveys. Natural England Commissioned report NECR139. Natural England.
Ter Braak, C.J.F., and Smilauer, P., 2002. CANOCO reference Manual and CanoDraw for Windows User’s Guide: Software for Canonical Community Ordination (version 4.5). Microcomputer Power (Ithaca NY USA).
Thomson, A., 2004. MATCH Version 4 - a computer program to aid the assignment of vegetation to the communities and subcommunities of the National Vegetation Classification. University of Lancaster.
Walsh, G., Peel, S. and Jefferson, R., 2011. Natural England Technical Information Note TIN045. The use of lime on semi-natural grassland in agrienvironment Schemes. www.naturalengland.org.uk.
Wolton, R., 2000. The control of soft rush Juncus effusus by cutting. Journal of Practical ecology and Conservation, 4, (1).
Wolton, R., 2003. Controlling rushes. Conservation Land Management Spring 2003, 1, (1) 10-13.
180036 94 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
8. ABBREVIATIONS
AEMA Agri-Environment Monitoring Archive
AHDB Agriculture and Horticulture Development Board
AOD Above Ordnance Datum
AONB Area of Outstanding Natural Beauty
CCA Canonical Correspondence Analysis
CSR Competitors, Stress-tolerators and Ruderal
DCA Detrended Correspondence Analysis
EU European Union
CS Countryside Stewardship
GIS Geographic Information Systems
CA Correspondence Analysis
EBLEX A division of AHDB
GPS Global Position System
FBI Farm Business Income
FYM Farmyard Manure
HLS Higher Level Stewardship
LFA Less Favoured Area
MCPA 2-methyl-4-chlorophenoxyacetic acid
MAVIS Modular Analysis of Vegetation Information Systems
NE Natural England
NVC National Vegetation Classification
PAA Penny Anderson Associates Ltd
SAC Special Area of Conservation
UHM Upland Hay Meadow
180036 95 Natural England March 2018 Towards an Understanding of the Perceived Increase in Juncus (Rush) Species in Species-Rich Upland Hay Meadows
FIGURE
340000 350000 360000 370000 380000 390000 400000 410000 420000 430000 550000 550000
Legend 540000 540000 Survey site location 530000 530000 520000 520000 510000 510000
British National Grid Projection: Transverse Mercator False Easting: 400000.000000 False Northing: -100000.000000 Central Meridian: -2.000000 ISO A3 Scale Factor: 0.999601 ´ Latitude Of Origin: 49.000000 500000 500000 Metres 01,500 3,000 6,000 9,000 12,000 490000 490000
Penny Anderson Associates Ltd, Parklea, 60 Park Road, Buxton, Derbyshire, SK17 6SN. Telephone 01298 27086 Project Name Juncus in Upland Hay Meadows
Discipline Ecology
Title:
Survey Site Locations - 480000 480000 Overview
Scale Drawing No. 1:300,000 Figure 3
Drawn ByOriginator Date CC HH 04/12/2017
PAA Ref. Revision G:\NATE34_JuncusHayMeadows\Maps\Figures\ 1.0 Figure1 -Site Location Overview- NATE34 CC 221117.mxd 340000 350000 360000 370000 380000 390000 400000 410000 420000 430000 Contains OS data © Crown copyright [and database right] (2017)
APPENDICES
APPENDIX 1
Field Proformas
BOTANICAL QUADRAT Site Code: Quadrat: Quadrat photo (Juncus present FORM only): Surveyor: Date: GPS Equipment used: Mobile mapper Ο [1]Existing Q + accurate GPS Ο [2]Existing Q + new GPS data Ο [3]New Q new GPS data: GPS BL corner (2x2): GPS TR corner (2x2):
Inner 1 x 1Outer 2 x 2 Inner 1 x 1 Outer 2 x 2 Species name Species name % Cover Domin DAFOR % Cover Domin DAFOR Anemone nemorosa Molinia caerulea Achillea millefolium Montia fontana Achillea ptarmica Myosotis discolor Agrostis canina Nardus stricta Agrostis capillaris Phleum pratense Agrostis stolonifera Plantago lanceolata Ajuga reptans Plantago major Alchemilla agg (NOT mollis) Poa annua Alchemilla filicaulis vestita Poa pratensis Alchemilla glabra Poa humilis(subcaerulea) Alchemilla xanthochlora Poa trivialis Alopecurus geniculatus Potentilla erecta Alopecurus pratensis Prunella vulgaris Anemone nemorosa Ranunculus acris Anthoxanthum odoratum Ranunculus bulbosus Anthriscus sylvestris Ranunculus ficaria Arrhenatherum elatius Ranunculus repens Avenula pratensis Rhinanthus minor Bellis perennis Rumex acetosa Briza media Rumex crispus Bromus hordeaceus Rumex obtusifolius Caltha palustris Sagina procumbens Campanula rotundifolia Sanguisorba minor Cardamine flexuosa Sanguisorba officinalis Cardamine pratensis Senecio jacobaea Carex caryophyllea Stellaria alsine Carex flacca Stellaria graminea Carex nigra Stellaria media Carex ovalis/leporina Succisa pratensis Carex panicea Taraxacum officinale agg. Centaurea nigra Trifolium dubium Cerastium fontanum Trifolium pratense Cerastium glomeratum Trifolium repens Cirsium arvense Trisetum flavescens Cirsium palustre Urtica dioica Cirsium vulgare Vaccinium myrtillus Conopodium majus Veronica arvensis Cynosurus cristatus Veronica chamaedrys Dactylis glomerata Veronica serpyllifolia Danthonia decumbens Vicia sepium Deschampsia cespitosa Viola riviniana Deschampsia flexuosa Equisetum arvense Equisetum palustre Euphrasia officinalis agg. Festuca pratensis Festuca rubra Filipendula ulmaria Galium saxatile Galium verum Geranium sylvaticum Heracleum sphondylium Brachythecium rutabulum Pilosella officinarum Calliergonella cuspidata Holcus lanatus Kindbergia praelonga Holcus mollis Rhytidiadelphus squarrosus Hypochaeris radicata Veg height ( 2x2) ______/______/______/______cm Juncus acutiflorus Bare Ground (%) Juncus articulatus Litter (%) Juncus conglomeratus 2x2 Qs only: Juncus effusus Rush J.acut J.cong J.effu Juncus squarrosus Rush total % cover Lathyrus pratensis Rush height ( x 4) cm cm cm Leontodon autumnalis Rush habit - T=tussock; Leontodon hispidus O=occasional shoots; Linum catharticum C=contin/dense shoots Lolium perenne Rush cut (y/n) Lotus corniculatus Rush grazed (y/n) Luzula campestris Rush - other (comment) DOMIN: 10 (91-100%); 9 (76-91%); 8 (75-51%); 7 (34-50%); 6 (26-33%); 5 (11-25%); 4 (4-10%); 3 (<4% many); 2 (<4% several); 1 (<4% few) SITE OVERVIEW FORM
Surveyor(s): Date: Site Code: Area: Previous data source: AEMA O'Reilly Hamilton Star-Keddle Topography: Slope: Aspect: Elevation: get from map/GIS
GIS Quadrat Information: Existing Qs relocated accurately (from differential GPS data) Existing Qs relocated approximately (paper records or hand held GPS) & MARKED (GPS bottom L and top R of 2x2) New Qs set up & MARKED (GPS bottom L and top R of 2x2) Equipment:______Mobile Mapper______/______hand-held GPS______Representative Photo (general site view) (direction, location, fix on notable background feature e.g. barn)
Site description
Positive indicators
Negative indicators
Management
Drainage
Juncus
Rush at site level (UHM only) J.acut J.cong J.effu Rush total % cover Rush height ( x 4) ____/____/____/____cm ____/____/____/____cm ____/____/____/____cm Rush habit - T=tussock; O= occasional shoots; C= continuous shoots Rush cut (y/n) Rush grazed (y/n) Rush - other (comment) TO DO: Map UHM and Juncus areas on aerial and mark existing & new quadrat locations 3 x quadrats (1x1m, inner Q nested in BL corner of 2x2m outer Q) 3 x Soil description with each Q W-Walk recording complete DAFOR & features across site Soil bulk sample on W-Walk (20 cores, placed in a single bag, use NE derived forms) 1 Representative photo of site GPS location. Replicate previous if possible. Mark direction on map. Date Recorder(s) SOIL DESCRIPTION FORM
PROJECT CLIENT Site Number General Notes NATE34 Juncus in UHM Natural England
Vegetation MG8 Ο MG8/MG3 Ο Slope MG3 Ο Other (describe) "Park Lea", 60 Park Road, Parent material Aspect Buxton, Desrbyshire, SK17 6SN Limestone Tel: (01298) 27086 Landscape Drainage Upland inbye farmland with meadows / pastures PROFILE DESCRIPTION PROFILE DESCRIPTION PROFILE DESCRIPTION Q1 Q2 Q3
Photo No. Photo No. Photo No. Podzol Mottling (seas)/ Mottling (perm) Gleying Podzol Compaction [nail] cm Podzol Compaction [nail] cm (seas)/ Mottling (perm) Gleying Compaction [nail] cm A Horiz (top) Horiz A (sub) Horiz B depth Root Texture (seas)/ Mottling (perm) Gleying Root depth Root Texture depth Root Texture A Horiz (top) Horiz A (sub) Horiz B (top) Horiz A (sub) Horiz B
10cm 10cm 10cm
20cm 20cm 20cm
30cm 30cm 30cm
40cm 40cm 40cm
50cm 50cm 50cm Additional Notes Additional Notes Additional Notes
Compaction - penetrometer (using ELE International Soil Tester) Compaction - penetrometer (using ELE International Soil Tester) Compaction - penetrometer (using ELE International Soil Tester) BOTANICAL W-WALK Site Code: Date Surveyor: FORM INDICATORS - % COVER of Juncus in 1m2 from the stop FULL SPECIES LIST DAFOR DAFOR DAFOR 1234567891011121314151617181920F Species (site) Achillea millefolium Molinia caerulea Juncus acutiflorus Agrostis canina Montia fontana Juncus conglomeratus Agrostis capillaris Myosotis discolor Juncus effusus Agrostis stolonifera Nardus stricta INDICATORS - PRESENCE/ABSENCE in 1m2 from the stop Alopecurus geniculatus Phleum pratense Alopecurus pratensis Plantago lanceolata DAFOR (site) NEG POS 12345678910111213141516171819 20 F Anthoxanthum odoratum Plantago major Arrhenatherum elatius Poa annua Achillea ptarmica ♦ Avenula pratensis Poa pratensis Ajuga reptans ♦ Bellis perennis Poa subcaerulea/humilis Alchemilla agg. (NOT mollis) ◊ Briza media Poa trivialis Alchemilla filicaulis vestita ◊ Bromus hordeaceus Prunella vulgaris Alchemilla glabra ◊ Campanula rotundifolia Ranunculus acris Alchemilla xanthochlora ◊ Cardamine flexuosa Ranunculus bulbosus Anemone nemorosa ◊ Cardamine pratensis Ranunculus ficaria Anthriscus sylvestris ◊♦ Carex caryophyllea Ranunculus repens Caltha palustris ♦ Carex ovalis/leporina Rumex acetosa Carex flacca ♦ Cerastium fontanum Sagina procumbens Carex nigra ♦ Cerastium glomeratum Sanguisorba minor Carex panicea ♦ Cirsium palustre Stellaria alsine Centaurea nigra ◊ Cynosurus cristatus Stellaria graminea Cirsium arvense ◊♦ Dactylis glomerata Stellaria media Cirsium heterophyllum ◊ Danthonia decumbens Taraxacum officinale agg. Cirsium vulgare ◊♦ Deschampsia cespitosa Trifolium dubium Conopodium majus ◊ Deschampsia flexuosa Trifolium pratense Crepis paludosa ♦ Equisetum arvense Trifolium repens Euphrasia officinalis agg. ◊♦ Equisetum palustre Trisetum flavescens Filipendula ulmaria ◊♦ Festuca pratensis Vaccinium myrtillus Geranium sylvaticum ◊ Festuca rubra Veronica arvensis Geum rivale ◊♦ Galium saxatile Veronica chamaedrys Lathyrus pratensis ◊ Galium verum Veronica serpyllifolia Leontodon autumnalis ◊♦ Heracleum sphondylium Vicia sepium Leontodon hispidus ◊♦ Pilosella officinarum Viola riviniana Lotus corniculatus ◊ Holcus lanatus Lychnis flos-cuculi ♦ Holcus mollis Orchidacaea ♦ Hypochaeris radicata Persicaria bistorta ◊ Juncus articulatus Potentilla erecta ♦ Juncus squarrosus Rhinanthus minor ◊♦ Linum catharticum Rumex crispus ◊♦ Lolium perenne Rumex obtusifolius ◊♦ Lotus pedunculatus Sanguisorba officinalis ◊♦ Luzula campestris Senecio jacobaea ◊ Serratula tinctoria ♦ Succisa pratensis ◊♦ Trees & scrub ◊ Trollius europaeus ◊♦ Brachythecium rutabulum Urtica dioica ◊♦ Calliergonella cuspidata Valeriana dioica ♦ Kindbergia praelonga Indicators: ◊ = MG3 only; ♦ = MG8-related (north), MG3- Rhytidiadelphus squarrosus
APPENDIX 2
Farm Management Questionnaire Proforma
FARM MANAGEMENT QUESTIONNAIRE 2017 Juncus/rushes in species-rich upland hay meadows
Field : …………………..(Please complete one questionnaire per field)
Hay meadows and hay meadow management
A. Hay management and cutting dates
1. Has the field been continuously managed for hay? Yes / No 2. If so, for how many years? 3. If less than 10 years, what was the management before? (e.g. grazed, haylage/silage/other)
4. What is the usual shutting-up date? 5. What is the usual hay cutting date? 6. Have either changed significantly over the past 10 years? 7. If so, how?
B. Grazing management
1. Please describe the usual grazing regime for the field below: - Stock type/breed, stock numbers, grazing period (1) - Stock type/breed, stock numbers, grazing period (2) 2. Has this changed significantly over the past 10 years? Yes / No (skip to C1) 3. If so, how?
C. Supplementary feeding
1. Do you carry out supplementary feeding in the field? Yes / No (Skip to C3) 2. If so, - what? (e.g. hay/haylage/silage/straw/salt lick/ concentrate) - when? - where? 3. Has this changed significantly over the past 10 years? Yes / No (Skip to D1) 4. If so, how?
D. Fertiliser, manure and lime application
1. Do you apply fertiliser to the field? Yes / No (Skip to D3) 2. If so, - what type? __:__:__ (NPK) - what rate? Kg/ha (or Cwt/ac, units/ac) - how often? - when did you last apply fertiliser to the field?
3. Do you apply Farmyard Manure (FYM) to the field? Yes / No (Skip to D5) 4. If so, - what rate? (<10 t/ha / 10-15 t/ha / 16-20 t/ha / 21-25 t/ha) - how often? - when did you last apply FYM to the field?
5. Do you apply lime to the field? Yes / No (Skip to D7) 6. If so, - how much? (< 1t/ha /1-2t/ha />2tha /other) - how often? - when did you last lime the field? 1 7. Have your fertiliser, manure or lime applications changed significantly Yes / No (Skip to E1) over the past 10 years? 8. If so, how?
- and what was it before that time?
E. Rushes and rush management
1. Has the area of rushes in the field has changed significantly in the past Yes / No (Skip to E3) 10 years? 2. If so, how? (e.g. increased by _% / decreased by _%)
3. Have the rushes changed in other ways over the past 10 years? 4. If so, Yes / No (Skip to E6) how? (e.g. vigour, density, species)
5. Have you got any thoughts on why this is?
6. Do you manage the rushes at all? Yes / No (Skip to F1) 7. If so, Hard grazing? (timings and livestock types) Cutting? - frequency & timing? e.g. 1x, 2x per year, e.g. pre-flowering or post-flowering - cutting equipment used? (e.g. topper rotary or flail or mower) - are toppings removed from fields or left on surface? Weed-wiping? - frequency & timing? - weed-wiping equipment/chemical/rate used? 8. What have you found works best and why do you think this?
F. Restoration
1. Have you carried out any restoration work to improve species diversity? Yes / No (Skip to G1) (e.g. adding seed, green hay, plug plants, with or without ground preparation such as harrowing / disking / trampling) 2. If so, what was this and when?
G. Drainage
1. Has the field been drained in the past? (E.g. Victorian or 20th Century) Yes / No (Skip to G7) 2. If so, what and when? 3. Do you have a drainage plan you could supply to the study? Yes / No 4. If so, could you provide via post / email / text? 5. If present, have you maintained the drains? (e.g. by jetting / rodding) 6. When was the last time you did this? 7. Have you carried out any additional drainage in the field? Yes / No (Skip to G9) 8. If so, what and when? (e.g. trench drainage, mole drainage or sub-soiling) 9. Can you identify any other management in the field that might have Yes / No (Skip to G11) affected drainage or rushes? 10. If so, when did it occur? 11. Do you think changes in the type and scale of machinery used have Yes / No (Skip to H1) affected drainage and/or rush growth? 12. If so, how?
2 Agronomic impact of rushes on farm
H. Hay yield
1. What is the current average hay yield from the field? (e.g. t/ha or bales/field but specify bale size, e.g. small, round) 2. Has this changed significantly over the past 10 years? Yes / No (Skip to H4) 3. If so, how?
4. How does current yield from the field compare with a similar field on your farm without rushes? (e.g. yield reduced by 1-10%/ 11-20%/ 21-30%/ other)
I. Hay quality
1. How would you describe the current hay quality from the field? Excellent/good/fair/poor
2. Does rush presence affect hay quality in terms of feed value? Yes / No (Skip to I4) 3. If so, how? (e.g. palatability/energy/nutrition/fibre/dry matter etc.) 4. Does rush presence result in more wastage of hay by livestock? Yes / No (Skip to I6) 5. If so, by how much?
6. Does rush presence affect hay quality in any other ways? Yes / No (Skip to I8) 7. If so, how? (e.g. effect on timing of hay cut and hence hay quality)
8. Is haylage or silage ever taken from the field? Yes / No (Skip to J1) 9. If so, is it foraged directly or baled? 10. If baled, how many layers of silage wrap are needed? 11. Does the rush cause spoilage of the bales?
J. Other
1. Have there been other agronomic or knock-on impacts arising from Yes / No (Skip to J3) rushes in hay/hay meadows? 2. If so, what is impact on: Livestock numbers kept?
Livestock health and condition?
Livestock liveweight gain?
Need to use/buy-in alternative forage?
Other (please specify)
3. Additional information
Please supply an email address ______if you would like to receive:
- a copy of the field survey data? Yes / No - a copy of the soil analysis data? Yes / No - a copy of our research report/summary findings? Yes / No
THANK YOU VERY MUCH FOR YOUR TIME
3
APPENDIX 3
Full Botanical Species List with Common Names, 2017
Appendix 3 Full Botanical Species List with Common Names, 2017
VASCULAR PLANTS Scientific Name Common Name Achillea millefolium Yarrow Achillea ptarmica Sneezewort Agrostis canina Velvet bent Agrostis capillaris Common bent Agrostis stolonifera Creeping bent Ajuga reptans Bugle Alchemilla agg. Lady's mantle spp. Alchemilla filicaulis vestita Lady's mantle spp. Alchemilla glabra Hairless lady's-mantle Alchemilla glomerulans Clustered lady's-mantle Alchemilla wichurae Rock lady's-mantle Alchemilla xanthochlora Pale lady's-mantle Alopecurus geniculatus Marsh foxtail Alopecurus pratensis Meadow foxtail Anemone nemorosa Wood anemone Angelica sylvestris Wild angelica Anthoxanthum odoratum Sweet vernal-grass Anthriscus sylvestris Cow parsley Arrhenatherum elatius False oat-grass Avenula pratensis Meadow oat-grass Avenula pubescens Downy oat-grass Bellis perennis Daisy Betonica officinalis Betony Briza media Quaking-grass Bromus hordeaceus Soft brome Caltha palustris Marsh marigold Campanula rotundifolia Harebell Cardamine flexuosa Wavy bitter-cress Cardamine hirsuta Hairy bitter-cress Cardamine pratensis Cuckooflower Carex caryophyllea Spring sedge Carex disticha Brown sedge Carex echinata Star sedge Carex flacca Glaucous sedge Carex hirta Hairy sedge Carex hostiana Tawny sedge Carex nigra Common sedge Carex oederi Small-fruited yellow-sedge Carex ovalis/leporina Oval sedge Carex pallescens Pale sedge Carex panicea Carnation sedge Carex pilulifera Pill sedge Carex pseudocyperus Cyperus sedge Carex pulicaris Flea sedge Carex rostrata Bottle sedge Centaurea nigra Common napweed Cerastium fontanum Common mouse-ear Cerastium glomeratum Sticky mouse-ear Cirsium arvense Creeping thistle Cirsium heterophyllum Melancholy thistle Cirsium palustre Marsh thistle Cirsium vulgare Spear thistle Comarum palustre Marsh cinquefoil Conopodium majus Pignut Crepis paludosa Marsh hawk's-beard Crepis sp. Hawk's-beard species Cruciata laevipes Crosswort Cynosurus cristatus Crested dog's-tail Dactylis glomerata Cock's-foot Dactylorhiza fuchsii Common spotted-orchid Dactylorhiza fuchsii x purpurella Common spotted x northern marsh orchid Dactylorhiza maculata Heath spotted-orchid Dactylorhiza praetermissa Southern marsh-orchid Dactylorhiza purpurella Northern marsh-orchid Dactylorhiza sp. Orchid species Danthonia decumbens Heath-grass Deschampsia cespitosa Tufted hair-grass Deschampsia flexuosa Wavy hair-grass Dryopteris filix-mas Male-fern Page 1 of 3 Scientific Name Common Name Epilobium palustre Marsh willowherb Epilobium parviflorum Hoary willowherb Epilobium tetragonum Square-stalked willowherb Equisetum arvense Field horsetail Equisetum fluviatile Water horsetail Equisetum palustre Marsh horsetail Equisetum sp. Horsetail species Equisetum sylvaticum Wood horsetail Euphrasia officinalis agg. Eyebright Festuca ovina Sheep's-fescue Festuca pratensis Meadow fescue Festuca rubra Red fescue Filipendula ulmaria Meadowsweet Galium aparine Cleavers Galium palustre Wall bedstraw Galium saxatile Heath bedstraw Galium uliginosum Fen bedstraw Galium verum Lady's bedstraw Geranium sylvaticum Wood crane's-bill Geum rivale Water avens Glyceria fluitans Floating sweet-grass Gymnadenia conopsea Fragrant orchid Heracleum sphondylium Hogweed Holcus lanatus Yorkshire fog Holcus mollis Creeping soft-grass Hypericum perforatum Perforate St. John's-wort Hypericum tetrapterum Square stalked St. John's-wort Hypochaeris radicata Cat's ear Isolepis setacea Bristle club-rush Juncus acutiflorus Sharp-flowered rush Juncus articulatus Jointed rush Juncus conglomeratus Compact rush Juncus effusus Soft-rush Juncus squarrosus Heath rush Lathyrus linifolius Bitter vetch Lathyrus pratensis Meadow vetchling Leontodon autumnalis Autumn hawkbit Leontodon hispidus Rough hawkbit Leucanthemum vulgare Oxeye daisy Linum catharticum Fairy flax Lolium perenne Perennial rye-grass Lotus corniculatus Bird's-foot trefoil Lotus pedunculatus Greater bird's-foot trefoil Luzula campestris Field wood-rush Luzula multiflora Heath wood-rush Lysimachia nemorum Yellow pimpernel Matricaria discoidea Pineappleweed Mentha aquatica Water mint Mimulus guttatus Monkeyflower Moehringia trinervia Three-veined sandwort Molinia caerulea Purple moor-grass Montia fontana Blinks Myosotis arvensis Field forget-me-not Myosotis discolor Changing forget-me-not Myosotis laxa Tufted forget-me-not Myosotis scorpioides Water forget-me-not Myosotis secunda Creeping forget-me-not Nardus stricta Mat-grass Neottia ovata Common twayblade Ophioglossum vulgatum Adder's-tongue Orchidaceae Orchid family Orchis mascula Early-purple orchid Pedicularis palustris Marsh lousewort Pedicularis sylvatica Lousewort Persicaria bistorta Common bistort Persicaria vivipara Alpine bistort Petasites hybridus Butterbur Phleum pratense Timothy Pilosella officinarum Mouse-ear hawkweed Plantago lanceolata Ribwort plantain Plantago major Greater plantain Poa annua Annual meadow-grass
Page 2 of 3 Scientific Name Common Name Poa pratensis Smooth meadow-grass Poa trivialis Rough meadow-grass Polygala sp. Milkwort species Potentilla anserina Silverweed Potentilla erecta Tormentil Primula farinosa Bird's-eye primrose Primula vulgaris Primrose Prunella vulgaris Selfheal Pteridium aquilinum Bracken Ranunculus acris Meadow buttercup Ranunculus bulbosus Bulbous buttercup Ranunculus flammula Lesser spearwort Ranunculus repens Creeping buttercup Rhinanthus minor Yellow-rattle Rumex acetosa Common sorrel Rumex acetosella Sheep's sorrel Rumex crispus Curled dock Rumex longifolius Northern dock Rumex obtusifolius Broad-leaved dock Sagina procumbens Procumbent pearlwort Sanguisorba minor Salad burnet Sanguisorba officinalis Great burnet Schedonorus arundinacea Tall fescue Senecio aquaticus Marsh ragwort Senecio jacobaea Common ragwort Silene flos-cuculi Ragged robin Stellaria alsine Bog stitchwort Stellaria graminea Lesser stitchwort Stellaria media Common chickweed Succisa pratensis Devil's-bit scabious Taraxacum officinale agg. Dandelion Trifolium dubium Lesser trefoil Trifolium medium Zigzag clover Trifolium pratense Red clover Trifolium repens White clover Triglochin palustris Marsh arrowgrass Trisetum flavescens Yellow oat-grass Trollius europaeus Globeflower Urtica dioica Common nettle Valeriana dioica Marsh valerian Valeriana officinalis Common valerian Veronica arvensis Wall speedwell Veronica beccabunga Brooklime Veronica chamaedrys Germander speedwell Veronica montana Wood speedwell Veronica officinalis Heath speedwell Veronica serpyllifolia Thyme-leaved speedwell Vicia cracca Tufted vetch Vicia orobus Wood bitter-vetch Vicia sepium Bush vetch Vicia sylvatica Wood vetch Viola lutea Mountain pansy Viola palustris Marsh violet Viola tricolor Wild pansy TOTALS 195
BRYOPHYTES Scientific Name Common Name Brachythecium rutabulum Rough-stalked feather-moss Calliergonella cuspidata Spear moss Climacium dendroides Tree-moss Hylocomium splendens Glittering wood-moss Kindbergia praelonga Common feather-moss Plagiomnium undulatum Wavy flat-moss Polytrichum formosum Wood hair-moss Pseudoscleropodium purum Neat feather-moss Rhytidiadelphus squarrosus Springy turf-moss Rhytidiadelphus triquetrus Rhytidiadelphus triquetrus Thamnobryum alopecurum Fox-tail feather-moss TOTALS 11
Page 3 of 3
APPENDIX 4
Full 2017 Species List and Occurrence by Dataset
Appendix 4 Full 2017 Species List and Occurrence by Dataset
KEY: positive indicator for MG3 & MG8; negative indicator for MG3 & MG8
Survey Type Quadrats (n=153) %cover Quadrats (n=153) dafor Sites (n=19) dafor freq % freq % freq % VASCULAR PLANTS Achillea millefolium 3 2% 6 4% 9 18% Achillea ptarmica 8 5%107%1427% Agrostis canina 1 1% 5 3% 1 2% Agrostis capillaris 98 64% 107 70% 19 37% Agrostis stolonifera 35 23% 36 24% 17 33% Ajuga reptans 13 8% 13 8% 8 16% Alchemilla agg. 11%1 2% Alchemilla filicaulis vestita 11%2 4% Alchemilla glabra 13 8% 15 10% 12 24% Alchemilla glomerulans 1 2% Alchemilla xanthochlora 2 4% Alopecurus geniculatus 18 12% 25 16% 16 31% Alopecurus pratensis 26 17% 46 30% 16 31% Anemone nemorosa 11% Angelica sylvestris 11%3 6% Anthoxanthum odoratum 138 90% 145 95% 17 33% Anthriscus sylvestris 2 1% 1 1% 9 18% Arrhenatherum elatius 1 1% 2 1% 4 8% Avenula pratensis 2 1% 2 1% 2 4% Avenula pubescens 4 3% 11 7% 7 14% Bellis perennis 48 31% 86 56% 14 27% Betonica officinalis 11%2 4% Briza media 3 2% 3 2% 10 20% Bromus hordeaceus 30 20% 37 24% 13 25% Caltha palustris 67 44% 74 48% 18 35% Campanula rotundifolia 12% Cardamine flexuosa 21%43% Cardamine hirsuta 21%11% Cardamine pratensis 31 20% 46 30% 11 22% Cardamine sp. 25 16% Carex caryophyllea 32%43% Carex disticha 21%21% Carex echinata 1 1% 2 1% 2 4% Carex flacca 96%128%918% Carex hostiana 1 1% 7 5% 2 4% Carex nigra 48 31% 60 39% 16 31% Carex ovalis/leporina 8 5% 11 7% 6 12% Carex pallescens 11%2 4% Carex panicea 11 7% 12 8% 10 20% Carex pilulifera 21% Carex pseudocyperus 12% Carex pulicaris 24% Centaurea nigra 17 11% 24 16% 16 31% Cerastium fontanum 94 61% 127 83% 18 35% Cerastium glomeratum 7 5% 20 13% 3 6% Cirsium arvense 1 1% 1 1% 8 16% Cirsium heterophyllum 1 2% Cirsium palustre 2 1% 2 1% 7 14% Cirsium vulgare 2 4% Comarum palustre 12% Conopodium majus 22 14% 38 25% 12 24% Crepis paludosa 4 3% 6 4% 13 25% Cruciata laevipes 24% Cynosurus cristatus 127 83% 138 90% 18 35% Dactylis glomerata 16 10% 31 20% 11 22% Dactylorhiza fuchsii 11%510% Dactylorhiza fuchsii x purpurella 1 1% 3 2% 2 4% Dactylorhiza purpurella 12 24% Deschampsia cespitosa 38 25% 37 24% 17 33% Deschampsia flexuosa 11% Elytrigia repens 11% Epilobium palustre 24% Epilobium parviflorum 12% Epilobium tetragonum 32%21% Equisetum arvense 11 7% 11 7% 10 20% Equisetum palustre 5 3% 7 5% 10 20% Euphrasia officinalis agg. 67 44% 85 56% 19 37% Festuca ovina 11% Festuca pratensis 36 24% 40 26% 18 35% Festuca rubra 94 61% 114 75% 19 37% Filipendula ulmaria 16 10% 23 15% 18 35% Galium aparine 12% Galium palustre 3 2% 3 2% 5 10% Galium uliginosum 11%3 6% Galium verum 12% Geranium sylvaticum 1 1% 1 1% 3 6% Geum rivale 3 2% 2 1% 6 12% Geum urbanum 11%11% Glyceria fluitans 1 1% 2 1% 4 8% Glyceria maxima 11% Heracleum sphondylium 5 3% 8 5% 13 25% Holcus lanatus 149 97% 148 97% 18 35% Holcus mollis 2 1% 5 3% 3 6% Hylocomium splendens 12% Hypochaeris radicata 19 12% 21 14% 5 10% Juncus acutiflorus 49 32% 57 37% 18 35% Juncus articulatus 7 5% 6 4% 13 25% Juncus conglomeratus 6 4% 5 3% 13 25% Juncus effusus 20 13% 23 15% 18 35% Juncus squarrosus 2 1% 4 3% 4 8% Lathyrus linifolius 11% 1 2% Lathyrus pratensis 13 8% 19 12% 14 27%
Page 1 of 2 Survey Type Quadrats (n=153) %cover Quadrats (n=153) dafor Sites (n=19) dafor freq % freq % freq % Leontodon autumnalis 64 42% 84 55% 17 33% Leontodon hispidus 9 6% 18 12% 13 25% Leucanthemum vulgare 2 1% 1 1% 3 6% Linum catharticum 36% Lolium multiflorum 11% Lolium perenne 92 60% 100 65% 17 33% Lotus corniculatus 6 4% 3 2% 11 22% Lotus pedunculatus 11%53% Luzula campestris 18 12% 32 21% 10 20% Luzula multiflora 12% Matricaria discoidea 12% Mimulus guttatus 24% Moehringia trinervia 7 5% 4 3% 3 6% Molinia caerulea 1 1% 0 0% 5 10% Montia fontana 2 1% 30 20% 1 2% Myosotis arvensis 12% Myosotis discolor 29 19% 66 43% 3 6% Myosotis laxa 34 22% 39 25% 17 33% Nardus stricta 3 2% 6 4% 2 4% Neottia ovata 4 8% Ophioglossum vulgatum 1 2% Orchidaceae 9 18% Pedicularis palustris 24% Pedicularis sylvatica 24% Persicaria bistorta 2 1% 2 1% 1 2% Phleum pratense agg. 25 16% 35 23% 17 33% Plantago lanceolata 99 65% 104 68% 2 4% Plantago major 21% 3 6% Poa annua 10 7% 8 5% 3 6% Poa pratensis 11 7% 9 6% 10 20% Poa subcaerulea 43% Poa trivialis 73 48% 110 72% 14 27% Polygonum aviculare 11% Potentilla erecta 10 7% 14 9% 12 24% Prunella vulgaris 57 37% 63 41% 19 37% Ranunculus acris 107 70% 125 82% 18 35% Ranunculus bulbosus 11%117% Ranunculus ficaria 32% Ranunculus flammula 1 1% 2 1% 7 14% Ranunculus repens 123 80% 121 79% 18 35% Rhinanthus minor 75 49% 96 63% 18 35% Rumex acetosa 129 84% 136 89% 19 37% Rumex acetosella 11% Rumex crispus 2 1% 5 3% 8 16% Rumex longifolius 12% Rumex obtusifolius 1 1% 2 1% 10 20% Sagina procumbens 21%128%3 6% Sanguisorba officinalis 4 3% 5 3% 7 14% Schedonorus arundinacea 11%1 2% Senecio aquaticus 11%1 2% Senecio jacobaea 2 1% 3 2% 5 10% Silene flos-cuculi 6 4%138%1325% Stellaria alsine 6 4% 8 5% 5 10% Stellaria graminea 7 5% 9 6% 6 12% Stellaria media 7 5% 7 5% 3 6% Succisa pratensis 11 7% 16 10% 9 18% Taraxacum officinale agg. 28 18% 58 38% 16 31% Trifolium dubium 21 14% 25 16% 12 24% Trifolium medium 11%2 4% Trifolium pratense 105 69% 110 72% 18 35% Trifolium repens 123 80% 139 91% 18 35% Triglochin palustris 11%1 2% Trisetum flavescens 29 19% 36 24% 13 25% Trollius europaeus 4 3% 9 6% 9 18% Urtica dioica 9 18% Valeriana dioica 2 4% Veronica arvensis 32%11% Veronica beccabunga 24% Veronica chamaedrys 12 8% 21 14% 11 22% Veronica montana 11%1 2% Veronica officinalis 11%11% Veronica serpyllifolia 32%149% Vicia cracca 48% Vicia sepium 3 2% 2 1% 5 10% Viola palustris 11%21% Viola tricolor 12% Total vascular plants by survey type = 113 135 144 Total vascular plants all survey types = 168 BRYOPHYTES Atrichum undulatum 11%11% Brachythecium rutabulum 18 12% 12 8% 3 16% Calliergonella cuspidata 15 10% 8 5% 15 79% Climacium dendroides 1 1% 3 16% Kindbergia praelonga 7 5% 4 3% 2 11% Plagiomnium undulatum 1 1% 2 1% 18 95% Pseudoscleropodium purum 15% Rhytidiadelphus squarrosus 25 16% 24 16% 5 26% Rhytidiadelphus triquetrus 2 1% 1 1% 2 11% Thamnobryum alopecurum 1 1% 1 1% 1 5% Total bryophytes by survey type = 9 8 9 Total bryophytes all survey types = 10
Page 2 of 2
APPENDIX 5
2017 Field Data (provided separately on CD)
APPENDIX 6
Best Three Fits to NVC Communities/ sub-communities over Two Years
Appendix 6 Best Three Fits to NVC Communities/sub-communities over Two Years using MATCH (51 Sites)
Site Year 1 NVC Coefficient Year 2 NVC Coefficient J008 1995 MG6b 65.9 2017 MG6b 64.5 MG8 61.2 MG5c 60.9 MG6 60.1 MG5a 60.9 J014 1995 MG5c 62.8 2017 U4b 55.1 MG3 60.2 MG6b 54.8 MG8 59.5 MG5c 50.7 J022 1995 MG8 64.7 2017 MG8 49.9 MG6b 56.6 MG10a 46.7 MG3a 53.8 MG6b 44.9 J053 1995 MG6b 66.5 2017 MG6b 62.1 MG6 62 MG6 56.1 MG6a 59 MG6a 55.9 J075 1993 MG6b 71.5 2017 MG6b 60.1 MG3a 67.1 MG10a 58.1 MG6 65 MG7D 57.4 J101 2002 MG3a 61.3 2017 MG6b 68.1 MG3 60.8 MG3a 64.9 MG8 59.4 MG3 64.8 J107 2002 MG6b 63.3 2017 MG6b 68.9 MG3a 61.7 MG3a 64.7 MG3 61.7 MG6 63.6 J120 2012 MG6b 65.4 2017 MG6b 68 MG8 62.9 MG8 60.7 MG3a 62.2 MG5a 60 J128 2002 MG3a 58.2 2017 MG5c 59.1 MG6b 55.3 MG5a 58.8 MG3 55.2 MG5 58.7 J166 2017 MG8 64.2 MG6b 57.9 MG6 56.3 J167 2017 MG8 62.9 MG9a 52 MG4 51.4 J202 2012 MG8 65.3 2017 MG8 63 MG6b 62.2 MG4 59.8 MG3a 60.6 MG3a 57.5 J203 2012 MG8 70.6 2017 MG8 66.6 MG6b 57.1 MG6b 56.1 MG4 55.1 MG6 53.2 J204 2012 MG8 56.5 2017 MG8 49.1 MG5c 45.9 MG10a 46.4 MG3 45.1 MG10 45.3 J205 2012 MG8 62.8 2017 MG6b 63.2 MG6b 62.5 MG8 62.2 MG3a 58.6 MG6 60.1 J206 2012 MG8 65.5 2017 MG6b 65 MG3 64.9 MG3a 63.3 MG3a 63.1 MG8 61.1 J207 2012 MG3a 63 2017 MG8 64 MG6b 62.8 MG6b 62.7 MG3 62.2 MG3a 61.2 J208 2012 MG3a 60.6 2017 MG6b 63.2 MG6b 60.3 MG3a 57.9 MG3 59.4 MG8 57.3 J209 2012 MG5c 53.4 2017 MG5c 58.1 U4b 53 U4b 52.6 MG8 50.7 MG5 49.6 J212 2012 MG6b 62 2017 MG8 65.1 MG8 60.2 MG6b 62.1 MG6 58.3 MG6 56.7 J214 2012 MG8 69.3 2017 MG6b 57.5 MG3a 62.9 MG8 57.2 MG6b 62.4 MG5a 52.7 J216 2012 MG8 61.3 2017 MG8 54.6 MG6b 57.7 MG6b 50.6 MG6 55.1 MG10a 48.8 J217 2012 MG8 59.1 2017 MG8 62.3 MG5c 49.3 MG4 52 MG6b 48.2 MG6b 51.2 J218 2012 MG8 61.1 2017 MG8 60 MG6b 56.9 MG9a 56.7 MG3a 54.5 MG6b 53 J219 2012 MG3a 63.9 2017 MG8 62.7 MG3 63.6 MG6b 59.3 MG8 62.8 MG5a 59.2 J220 2012 MG10a 50 2017 MG8 57.6 MG10 49.2 MG10 54.6 Site Year 1 NVC Coefficient Year 2 NVC Coefficient MG8 48.1 MG6a 52.2 J221 2012 MG3a 72.3 2017 MG3a 64 MG3 68.3 MG6b 62.5 MG6b 65.9 MG3 59.8 J223 2012 MG6b 68.2 2017 MG6b 64.3 MG3a 65.4 MG6 63.7 MG3 63.4 MG6a 61.9 J225 2012 MG6b 60 2017 MG6b 62.4 MG8 59 MG5a 61.7 MG6 56.2 MG5 59.8 J226 2012 MG8 59.8 2017 MG8 61.8 MG6b 55.8 MG5a 57 MG3 55.5 MG5 55.8 J227 2012 MG6b 67.8 2017 MG6b 64.6 MG8 65.4 MG8 64.3 MG6 63.2 MG6 58.6 J230 2012 MG3a 65.5 2017 MG6b 67.3 MG6b 61.3 MG6 62.7 MG3 60.6 MG6a 60.9 J232 2012 MG8 60.5 2017 MG8 65.2 MG4 51.1 MG6b 55.3 MG6b 50.6 MG4 54.6 J260 2017 MG8 60.7 MG6b 53.1 MG6a 52.4 J261 2017 MG8 62.2 MG6b 62.1 MG6 61.5 J264 2017 MG7D 65.1 MG6b 64.4 MG6a 63.2 J265 2017 MG8 61.7 MG6b 55.7 MG4 55.5 J270 2017 MG6b 67.7 MG6 65.2 MG5a 61.1 J271 2017 MG3a 68.5 MG6b 64.5 MG3 64 J283 2012 MG3a 58.1 2017 MG6b 58.6 MG6b 57.9 MG7D 57.3 MG8 55.2 MG6a 57.1 J285 2017 MG5a 63 MG3a 62.6 MG3 61.8 J286 2017 MG8 63 MG6b 62.1 MG6a 61.9 J288 2017 MG8 63.6 MG6b 55.7 MG6a 54.3 J290 2017 MG8 58.2 MG5 51.8 MG6b 51.8 J291 2012 MG3 68.6 2017 MG6b 63 MG3a 68.4 MG3a 62.2 MG6b 66.7 MG8 61.4 J292 2017 MG6b 65.1 MG8 63.7 MG6 63.1 J293 2017 MG6b 68.9 MG6 65.8 MG3a 64.2 J294 2017 MG8 70.1 MG4 58.4 MG3a 52.9 J295 1992 MG8 64.4 2017 MG8 58.8 MG6b 62.9 MG6b 55.5 MG3a 59.6 U4b 52.1 J296 2017 MG8 65.1 MG3a 58.1 MG6b 57.7 J297 1988 MG6b 62.1 2017 MG6b 63.9 MG8 59.9 MG6 61.7 MG6 57.3 MG6a 59.9 51
APPENDIX 7
Combined Botanical and Environmental Data (provided separately on CD)
APPENDIX 8
Statistical Analysis Summary
Appendix 8 Statistical Analysis Summary
Quadrat Data: nsd = no significant difference
Dataset Results Variable Details Test Description Comment Quad % Cover Quad Dafor J. acutiflorus Test for normal distribution Kolomogorov-Smirnov One-sample test - Lillefors Non-normal distribution Non-normal distribution Non-parametric tests Probability should be used J. conglomeratus Test for normal distribution Kolomogorov-Smirnov One-sample test - Lillefors Non-normal distribution Non-normal distribution Probability J. effusus Test for normal distribution Kolomogorov-Smirnov One-sample test - Lillefors Non-normal distribution Non-normal distribution Probability J. articulatus Test for normal distribution Kolomogorov-Smirnov One-sample test - Lillefors Non-normal distribution Non-normal distribution Probability J. acutiflorus Log data Test for normal distribution Kolomogorov-Smirnov One-sample test - Lillefors Non-normal distribution N/A Non-parametric tests Probability should be used J. conglomeratus Log data Test for normal distribution Kolomogorov-Smirnov One-sample test - Lillefors Non-normal distribution N/A Probability J. effusus Log data Test for normal distribution Kolomogorov-Smirnov One-sample test - Lillefors Non-normal distribution N/A Probability J. articulatus Log data Test for normal distribution Kolomogorov-Smirnov One-sample test - Lillefors Non-normal distribution N/A Probability J. acutiflorus Grouping variable: Kruskal-Wallis one-way ANOVA (Non-parametric) nsd GRAPH nsdThis non-parametric test Analysis complete Site_Year with Conover-Inman Test for pairwise comparisons compares the median of J. conglomeratus Grouping variable: Kruskal-Wallis one-way ANOVA (Non-parametric) nsd nsd the 2 to 3 quadrats per Site_Year with Conover-Inman Test for pairwise comparisons site over 2 years, the pairwise test compares J. effusus Grouping variable: Kruskal-Wallis one-way ANOVA (Non-parametric) nsd nsd this on a site by site Site_Year with Conover-Inman Test for pairwise comparisons basis J. articulatus Grouping variable: Kruskal-Wallis one-way ANOVA (Non-parametric) nsd nsd Site_Year with Conover-Inman Test for pairwise comparisons Juncus combined total Grouping variable: Kruskal-Wallis one-way ANOVA (Non-parametric) nsd GRAPH nsd Site_Year with Conover-Inman Test for pairwise comparisons J. acutiflorus YR1 against Y2 for all Pearson correlation nsd N/A Correlations are Could repeat for other sites relationships or variables if other correlations associations between are likely, but data seems variables, can be positive unlikely to show any or negative significance J. acutiflorus Grouping variable: Year T-Test (parametric test) Only J204 sig diff over N/A Test is not valid for non- not recommended time on site by site basis normal data J. acutiflorus Grouping variable: Year Mann-Whitney U test (non-parametric) Only sig diff was for site N/A Non-parametric test is Could repeat for other Juncus J204 where J. acutiflorus valid but may return species or total Juncus cover, was sig greater in 2017 more Type 1 errors (i.e. but data seems unlikely to [p=0.05, df=1] GRAPHED give a sig diff when there show any significance isn't really one, a 'false positive') J. acutiflorus - only sites with Grouping variable: Year Kruskal-Wallis one-way ANOVA (Non-parametric) nsd N/A Removed J101, J107, J206, Juncus in Yr 1 OR Yr 2 with Conover-Inman Test for pairwise comparisons J216, J223, J283, J291 (i.e. removed 7 sites that had no Juncus in both years)
1 of 4 Dataset Results Variable Details Test Description Comment Quad % Cover Quad Dafor J. articulatus - only sites with Grouping variable: Year Kruskal-Wallis one-way ANOVA (Non-parametric) nsd N/A Removed J101, J107, J206, Juncus in Yr 1 OR Yr 2 with Conover-Inman Test for pairwise comparisons J216, J223, J283, J291 (i.e. removed 7 sites that had no J. conglomeratus - only sites with Grouping variable: Year Kruskal-Wallis one-way ANOVA (Non-parametric) nsd N/A Juncus in both years) Juncus in Yr 1 OR Yr 2 with Conover-Inman Test for pairwise comparisons J. effusus - only sites with Grouping variable: Year Kruskal-Wallis one-way ANOVA (Non-parametric) nsd N/A Juncus in Yr 1 OR Yr 2 with Conover-Inman Test for pairwise comparisons
Juncus total - only sites with Grouping variable: Year Kruskal-Wallis one-way ANOVA (Non-parametric) nsd N/A Juncus in Yr 1 OR Yr 2 with Conover-Inman Test for pairwise comparisons J. acutiflorus - only sites with Grouping variable: Year Kruskal-Wallis one-way ANOVA (Non-parametric) nsd N/A In addition to J101, J107, Juncus in Yr 1 AND Yr 2 with Conover-Inman Test for pairwise comparisons J206, J216, J223, J283, J291, J. articulatus - only sites with Grouping variable: Year Kruskal-Wallis one-way ANOVA (Non-parametric) nsd N/A also removed J120, J128, Juncus in Yr 1 AND Yr 2 with Conover-Inman Test for pairwise comparisons J202, J207, J221 (i.e. removed 12 sites that had no Juncus in J. conglomeratus - only sites with Grouping variable: Year Kruskal-Wallis one-way ANOVA (Non-parametric) nsd N/A either yr1 or yr2. Analysis may Juncus in Yr 1 AND Yr 2 with Conover-Inman Test for pairwise comparisons not be so useful as removes J. effusus - only sites with Grouping variable: Year Kruskal-Wallis one-way ANOVA (Non-parametric) nsd N/A sites where Juncus had gone Juncus in Yr 1 AND Yr 2 with Conover-Inman Test for pairwise comparisons from zero to some cover)
Juncus total - only sites with Grouping variable: Year Kruskal-Wallis one-way ANOVA (Non-parametric) nsd N/A Juncus in Yr 1 AND Yr 2 with Conover-Inman Test for pairwise comparisons J. acutiflorus Log data - only Grouping variable: Year Kruskal-Wallis one-way ANOVA (Non-parametric) nsd N/A Removed J101, J107, J206, sites with Juncus in both Yr 1 OR with Conover-Inman Test for pairwise comparisons J216, J223, J283, J291 Yr 2 J. articulatus Log data - only Grouping variable: Year Kruskal-Wallis one-way ANOVA (Non-parametric) nsd N/A sites with Juncus in both Yr 1 OR with Conover-Inman Test for pairwise comparisons Yr 2 J. conglomeratus Log data - only Grouping variable: Year Kruskal-Wallis one-way ANOVA (Non-parametric) nsd N/A sites with Juncus in Yr 1 OR Yr 2 with Conover-Inman Test for pairwise comparisons
J. effusus Log data - only sites Grouping variable: Year Kruskal-Wallis one-way ANOVA (Non-parametric) nsd N/A with Juncus in Yr 1 OR Yr 2 with Conover-Inman Test for pairwise comparisons Juncus total Log data - only sites Grouping variable: Year Kruskal-Wallis one-way ANOVA (Non-parametric) nsd N/A with Juncus in both Yr 1 OR Yr 2 with Conover-Inman Test for pairwise comparisons
J. acutiflorus Log data - only Grouping variable: Year Kruskal-Wallis one-way ANOVA (Non-parametric) nsd N/A Also removed J120, J128, sites with Juncus in Yr 1 AND Yr with Conover-Inman Test for pairwise comparisons J202, J207, J221 2 J. articulatus Log data - only Grouping variable: Year Kruskal-Wallis one-way ANOVA (Non-parametric) nsd N/A sites with Juncus in Yr 1 AND Yr with Conover-Inman Test for pairwise comparisons 2 J. conglomeratus Log data - only Grouping variable: Year Kruskal-Wallis one-way ANOVA (Non-parametric) nsd N/A sites with Juncus in Yr 1 AND Yr with Conover-Inman Test for pairwise comparisons 2 J. effusus Log data - only sites Grouping variable: Year Kruskal-Wallis one-way ANOVA (Non-parametric) nsd N/A with Juncus in Yr 1 AND Yr 2 with Conover-Inman Test for pairwise comparisons
2 of 4 Dataset Results Variable Details Test Description Comment Quad % Cover Quad Dafor Juncus total Log data - only sites Grouping variable: Year Kruskal-Wallis one-way ANOVA (Non-parametric) nsd N/A Also removed J120, J128, with Juncus in Yr 1 AND Yr 2 with Conover-Inman Test for pairwise comparisons J202, J207, J221
Competitor Grouping variable: Kruskal-Wallis one-way ANOVA (Non-parametric) overall highly sig overall highly sig CSR strategies as calc Analysis complete Site_Year with Conover-Inman Test for pairwise comparisons difference (p=<0.001) but difference (p=<0.001) but from MAVIS nsd at pairwise level nsd at pairwise level
Stress Tolerator Grouping variable: Kruskal-Wallis one-way ANOVA (Non-parametric) overall highly sig overall highly sig Site_Year with Conover-Inman Test for pairwise comparisons difference (p=<0.001), difference (p=<0.001), but nsd at pairwise level but nsd at pairwise level
Ruderal Grouping variable: Kruskal-Wallis one-way ANOVA (Non-parametric) overall highly sig overall highly sig Site_Year with Conover-Inman Test for pairwise comparisons difference (p=<0.001), difference (p=<0.001), but nsd at pairwise level but nsd at pairwise level
Light Grouping variable: Kruskal-Wallis one-way ANOVA (Non-parametric) overall highly sig overall highly sig diff Ellenberg values as calc overall sig result likely due to Site_Year with Conover-Inman Test for pairwise comparisons difference (p=<0.001), (p=<0.001), only one from MAVIS differences across entire but nsd at pairwise level 'trend' (p = 0.059) in dataset pairwise interactions - J207 (slightly higher in 2017 than 2012)
Moisture Grouping variable: Kruskal-Wallis one-way ANOVA (Non-parametric) overall highly sig overall highly sig Analysis complete Site_Year with Conover-Inman Test for pairwise comparisons difference (p=<0.001), difference (p=<0.001), but nsd at pairwise level but nsd at pairwise level pH Grouping variable: Kruskal-Wallis one-way ANOVA (Non-parametric) overall highly sig overall highly sig Site_Year with Conover-Inman Test for pairwise comparisons difference (p=<0.001) but difference (p=<0.001) but nsd at pairwise level nsd at pairwise level
Fertility Grouping variable: Kruskal-Wallis one-way ANOVA (Non-parametric) overall highly sig overall highly sig Site_Year with Conover-Inman Test for pairwise comparisons difference (p=<0.001), difference (p=<0.001), but nsd at pairwise level but nsd at pairwise level
Positive indicator species, each Grouping variable: Kruskal-Wallis one-way ANOVA (Non-parametric) overall sig difference for Those with overall sig diff Analysis complete species separately Site_Year with Conover-Inman Test for pairwise comparisons some spp (see table for p were assessed for values) but nsd at pairwise sig diff - none pairwise level found
Negative indicator species, each Grouping variable: Kruskal-Wallis one-way ANOVA (Non-parametric) overall sig difference for species separately Site_Year with Conover-Inman Test for pairwise comparisons some spp (see table for p values) but nsd at pairwise level Total cover of all positive Grouping variable: Kruskal-Wallis one-way ANOVA (Non-parametric) overall highly sig N/A Analysis complete indicator species Site_Year with Conover-Inman Test for pairwise comparisons difference (p=<0.001) with some sig diff/trends at pairwise level (Sites J120, J128, J209, J214 all gone up in 2017; Site J216 gone down in 2017). GRAPHED
3 of 4 Dataset Results Variable Details Test Description Comment Quad % Cover Quad Dafor Total cover of all negative Grouping variable: Kruskal-Wallis one-way ANOVA (Non-parametric) overall sig difference N/A Those with overall sig diff indicator species Site_Year with Conover-Inman Test for pairwise comparisons (p=0.045) but nsd at were assessed for pairwise level pairwise sig diff - none found Soil pH Grouping variable: Kruskal-Wallis one-way ANOVA (Non-parametric) overall highly sig N/A overall sig result likely due to Site_Year with Conover-Inman Test for pairwise comparisons difference (p=<0.001), differences across entire but nsd at pairwise level dataset Soil P Grouping variable: Kruskal-Wallis one-way ANOVA (Non-parametric) overall highly sig N/A Analysis complete Site_Year with Conover-Inman Test for pairwise comparisons difference (p=<0.001), but nsd at pairwise level Soil K Grouping variable: Kruskal-Wallis one-way ANOVA (Non-parametric) overall highly sig N/A Site_Year with Conover-Inman Test for pairwise comparisons difference (p=<0.001), but nsd at pairwise level Soil Texture Grouping variable: Kruskal-Wallis one-way ANOVA (Non-parametric) overall highly sig N/A Site_Year with Conover-Inman Test for pairwise comparisons difference (p=<0.001), but nsd at pairwise level
Site Data: Dataset Results Description Variable Details Test Whole Site Dafor Notes J acutiflorus Grouping variable: Year Mann-Whitney U test (non-parametric) nsd GRAPH Analyses the difference in Analysis complete J conglomeratus Grouping variable: Year Mann-Whitney U test (non-parametric) highly sig diff (p=0.001) - median values derived cover of J cong is higher from all sites, between Yr1 in 2017 GRAPH and Yr2 J. effusus Grouping variable: Year Mann-Whitney U test (non-parametric) nsd GRAPH J. articulatus Grouping variable: Year Mann-Whitney U test (non-parametric) highly sig diff (p=<0.001) - cover of J artic is higher in 2017 GRAPH
Juncus combined total Grouping variable: Year Mann-Whitney U test (non-parametric) highly sig diff (p=0.006) - total cover of Juncus is higher in 2017 GRAPH Positive indicator species, each Grouping variable: Year Mann-Whitney U test (non-parametric) sig difference for some Analyses the difference in Analysis complete species separately spp - see report SYSTAT median values derived GRAPH from all sites, between Yr1 Negative indicator species, each Grouping variable:Year Mann-Whitney U test (non-parametric) sig difference for some and Yr2 Analysis complete species separately spp - see report SYSTAT GRAPH Soil pH Grouping variable: Year Mann-Whitney U test (non-parametric) nsd Analysis of the difference Analysis complete Soil P Grouping variable: Year Mann-Whitney U test (non-parametric) highly sig diff (p=0.002) - in soil samples across all soil P is lower in 2017 sites between Yr1 and Yr2 GRAPH Soil K Grouping variable: Year Mann-Whitney U test (non-parametric) nsd GRAPH Soil Mg Grouping variable: Year Mann-Whitney U test (non-parametric) nsd GRAPH
4 of 4 A. Juncus cover – results of tests for normal distribution. Where p = 0.000 then these data are highly significantly different a normal distribution. This means these data are non-normal and non-parametric tests should be used.
(1) Juncus as DAFOR categories in Quadrats
Kolmogorov-Smirnov One-Sample Test using Normal(0.00, 1.00) Distribution
Variable N of Cases Maximum Lilliefors Difference Probability (2-Tail) JUNCUS_ACUTIFLORUS 204 0.399 0.000 JUNCUS_ARTICULATUS 204 0.535 0.000 JUNCUS_CONGLOMERATUS 204 0.534 0.000 JUNCUS_EFFUSUS 204 0.497 0.000 JUNCUS_TOTAL 204 0.327 0.000
(2) Juncus as % cover in Quadrats
Kolmogorov-Smirnov One-Sample Test using Normal (0.00, 1.00) Distribution
Variable N of Cases Maximum Lilliefors Difference Probability (2-Tail) JUNC_ACUT 164 0.374 0.000 JUNCUS_ARTICULATUS 164 0.519 0.000 JUNC_CONG 164 0.516 0.000 JUNC_EFFU 164 0.502 0.000 JUNC_TOTAL 164 0.345 0.000
(3) Juncus as % cover in Quadrats – LOG transformed
Kolmogorov-Smirnov One-Sample Test using Normal (0.00, 1.00) Distribution
Variable N of Cases Maximum Lilliefors Difference Probability (2-Tail) JUNCACUTLOG 164 0.408 0.000 JUNCARTLOG 164 0.527 0.000 JUNCCONLOG 164 0.528 0.000 JUNCEFFLOG 164 0.523 0.000 JUNCTOTLOG 164 0.375 0.000
B. Juncus cover – results of KW tests
In these KW tests and p value of 0.05 or less will indicate that the median Juncus cover in Year 1 is significantly different to the median Juncus cover in year 2. In all cases there is no significant difference between means of year 1 and year 2 (p>0.05).
In all cases, the pairwise interactions also gave no significant difference (p>0.05) between years 1 and 2 for any one individual field.
(1) Juncus as DAFOR categories in Quadrats
Variable d.f. H Test P-value statistic JUNC_ACUT 69 86.77 0.073 JUNCUS_ARTICULATUS 69 64.96 0.616 JUNC_CONG 69 62.15 0.708 JUNC_EFFU 69 69.71 0.453 JUNC_TOTAL 69 83.46 0.113
(2) Juncus as % cover in Quadrats
Variable d.f. H Test P-value statistic JUNC_ACUT 55 60.66 0.279 JUNCUS_ARTICULATUS 55 52.31 0.578 JUNC_CONG 55 51.62 0.605 JUNC_EFFU 55 55.08 0.471 JUNC_TOTAL 55 66.97 0.129
C. Results of Pearson Correlation, Juncus acutiflorus Year 1 and Year 2 (% cover)
APPENDIX 9
Canoco Species Codes
Appendix 9 Canoco Species Codes
Species Species Code for Scientific Name Code for Scientific Name CANOCO CANOCO Ach mil Achillea millefolium Jun acu Juncus acutiflorus Ach pta Achillea ptarmica Jun art Juncus articulatus Agr can Agrostis canina Jun con Juncus conglomeratus Agr cap Agrostis capillaris Jun eff Juncus effusus Agr sto Agrostis stolonifera Jun squ Juncus squarrosus Aju rep Ajuga reptans Kin pra Kindbergia praelonga Alc gla Alchemilla glabra Lat lin Lathyrus linifolius Alo gen Alopecurus geniculatus Lat pra Lathyrus pratensis Alo pra Alopecurus pratensis Leo aut Leontodon autumnalis Ane nem Anemone nemorosa Leo his Leontodon hispidus Ant odo Anthoxanthum odoratum Leu vul Leucanthemum vulgare Ant syl Anthriscus sylvestris Lol mul Lolium multiflorum Ave pra Avenula pratensis Lol per Lolium perenne Ave pub Avenula pubescens Lot cor Lotus corniculatus Bel per Bellis perennis Lot ped Lotus pedunculatus Bra rut Brachythecium rutabulum Luz cam Luzula campestris Bri med Briza media Moe tri Moehringia trinervia Bro hor Bromus hordeaceus Mol cae Molinia caerulea Cal cus Calliergonella cuspidata Mon fon Montia fontana Cal pal Caltha palustris Myo dis Myosotis discolor Car hir Cardamine hirsuta Myo lax Myosotis laxa Car pra Cardamine pratensis Nar stri Nardus stricta Card sp Cardamine sp. Per bis Persicaria bistorta Cx cary Carex caryophyllea Phl pra Phleum pratense Cx dist Carex disticha Pla lan Plantago lanceolata Cx echi Carex echinata Pla maj Plantago major Cx flac Carex flacca Poa ann Poa annua Cx hirt Carex hirta Poa pra Poa pratensis Cx nigr Carex nigra Poa sub Poa subcaerulea Cx lepo Carex ovalis/leporina Poa tri Poa trivialis Cx pall Carex pallescens Pot ere Potentilla erecta Cx pani Carex panicea pru vul Prunella vulgaris Cx pilu Carex pilulifera Ran acr Ranunculus acris Cen nig Centaurea nigra Ran bul Ranunculus bulbosus Cer fon Cerastium fontanum Ran fic Ranunculus ficaria Cer glo Cerastium glomeratum Ran fla Ranunculus flammula Cera sp Cerastium sp Ran rep Ranunculus repens Cir arv Cirsium arvense Rhi min Rhinanthus minor Cir pal Cirsium palustre Rhy squ Rhytidiadelphus squarrosus Cli den Climacium dendroides Rhy tri Rhytidiadelphus triquetrus Con maj Conopodium majus Rx ace Rumex acetosa Cre pal Crepis paludosa Rx cri Rumex crispus Cyn cri Cynosurus cristatus Rx obt Rumex obtusifolius Dac glo Dactylis glomerata Sag pro Sagina procumbens Dac pur Dactylorhiza purpurella San off Sanguisorba officinalis Des ces Deschampsia cespitosa Sch aru Schedonorus arundinacea Epi tet Epilobium tetragonum Sen aqu Senecio aquaticus Equ arv Equisetum arvense Sen jac Senecio jacobaea Equ pal Equisetum palustre Sil flo Silene flos-cuculi Eup off Euphrasia officinalis agg. Ste als Stellaria alsine Fes ovi Festuca ovina Ste gra Stellaria graminea Fes pra Festuca pratensis Ste med Stellaria media Fes rub Festuca rubra Suc pra Succisa pratensis Fil ulm Filipendula ulmaria Tar off Taraxacum officinale agg. Gal pal Galium palustre Tri dub Trifolium dubium Gal uli Galium uliginosum Tri pra Trifolium pratense Geu riv Geum rivale Tri rep Trifolium repens Gly flu Glyceria fluitans Tri fla Trisetum flavescens Her spo Heracleum sphondylium Tro eur Trollius europaeus Hol lan Holcus lanatus Ver arv Veronica arvensis Hol mol Holcus mollis Ver cha Veronica chamaedrys Hyp rad Hypochaeris radicata Ver off Veronica officinalis Ver ser Veronica serpyllifolia Vic sep Vicia sepium Vio pal Viola palustris
APPENDIX 10
Canoco Quadrat Sample Numbers by Year
Appendix 10 Canoco Quadrat Sample Numbers by Year
Site_Yr_Q Year Sample No. Site_Yr_Q Year Sample No. Site_Yr_Q Year Sample No. J101_02_Q2 2002 1 J225_12_Q2 2012 63 J216_17_Q3 2017 125 J101_02_Q3 2002 2 J225_12_Q3 2012 64 J217_17_Q1 2017 126 J107_02_Q1 2002 3 J226_12_Q1 2012 65 J217_17_Q2 2017 127 J107_02_Q2 2002 4 J226_12_Q2 2012 66 J217_17_Q3 2017 128 J107_02_Q3 2002 5 J226_12_Q3 2012 67 J218_17_Q1 2017 129 J128_02_Q1 2002 6 J227_12_Q1 2012 68 J218_17_Q2 2017 130 J128_02_Q2 2002 7 J227_12_Q2 2012 69 J218_17_Q3 2017 131 J120_12_Q1 2012 8 J227_12_Q3 2012 70 J219_17_Q1 2017 132 J120_12_Q2 2012 9 J230_12_Q1 2012 71 J219_17_Q2 2017 133 J120_12_Q3 2012 10 J230_12_Q2 2012 72 J219_17_Q3 2017 134 J202_12_Q1 2012 11 J230_12_Q3 2012 73 J220_17_Q1 2017 135 J202_12_Q2 2012 12 J232_12_Q1 2012 74 J220_17_Q2 2017 136 J202_12_Q3 2012 13 J232_12_Q2 2012 75 J220_17_Q3 2017 137 J203_12_Q1 2012 14 J232_12_Q3 2012 76 J221_17_Q1 2017 138 J203_12_Q2 2012 15 J283_12_Q1 2012 77 J221_17_Q2 2017 139 J203_12_Q3 2012 16 J283_12_Q2 2012 78 J221_17_Q3 2017 140 J204_12_Q1 2012 17 J283_12_Q3 2012 79 J223_17_Q1 2017 141 J204_12_Q2 2012 18 J291_12_Q1 2012 80 J223_17_Q2 2017 142 J204_12_Q3 2012 19 J291_12_Q2 2012 81 J223_17_Q3 2017 143 J205_12_Q1 2012 20 J291_12_Q3 2012 82 J225_17_Q1 2017 144 J205_12_Q2 2012 21 J101_17_Q2 2017 83 J225_17_Q2 2017 145 J205_12_Q3 2012 22 J101_17_Q3 2017 84 J225_17_Q3 2017 146 J206_12_Q1 2012 23 J107_17_Q1 2017 85 J226_17_Q1 2017 147 J206_12_Q2 2012 24 J107_17_Q2 2017 86 J226_17_Q2 2017 148 J206_12_Q3 2012 25 J107_17_Q3 2017 87 J226_17_Q3 2017 149 J207_12_Q1 2012 26 J120_17_Q1 2017 88 J227_17_Q1 2017 150 J207_12_Q2 2012 27 J120_17_Q2 2017 89 J227_17_Q2 2017 151 J207_12_Q3 2012 28 J120_17_Q3 2017 90 J227_17_Q3 2017 152 J208_12_Q1 2012 29 J128_17_Q1 2017 91 J230_17_Q1 2017 153 J208_12_Q2 2012 30 J128_17_Q2 2017 92 J230_17_Q2 2017 154 J208_12_Q3 2012 31 J202_17_Q1 2017 93 J230_17_Q3 2017 155 J209_12_Q1 2012 32 J202_17_Q2 2017 94 J232_17_Q1 2017 156 J209_12_Q2 2012 33 J202_17_Q3 2017 95 J232_17_Q2 2017 157 J209_12_Q3 2012 34 J203_17_Q1 2017 96 J232_17_Q3 2017 158 J212_12_Q1 2012 35 J203_17_Q2 2017 97 J283_17_Q1 2017 159 J212_12_Q2 2012 36 J203_17_Q3 2017 98 J283_17_Q2 2017 160 J212_12_Q3 2012 37 J204_17_Q1 2017 99 J283_17_Q3 2017 161 J214_12_Q1 2012 38 J204_17_Q2 2017 100 J291_17_Q1 2017 162 J214_12_Q2 2012 39 J204_17_Q3 2017 101 J291_17_Q2 2017 163 J214_12_Q3 2012 40 J205_17_Q1 2017 102 J291_17_Q3 2017 164 J216_12_Q1 2012 41 J205_17_Q2 2017 103 J216_12_Q2 2012 42 J205_17_Q3 2017 104 J216_12_Q3 2012 43 J206_17_Q1 2017 105 J217_12_Q1 2012 44 J206_17_Q2 2017 106 J217_12_Q2 2012 45 J206_17_Q3 2017 107 J217_12_Q3 2012 46 J207_17_Q1 2017 108 J218_12_Q1 2012 47 J207_17_Q2 2017 109 J218_12_Q2 2012 48 J207_17_Q3 2017 110 J218_12_Q3 2012 49 J208_17_Q1 2017 111 J219_12_Q1 2012 50 J208_17_Q2 2017 112 J219_12_Q2 2012 51 J208_17_Q3 2017 113 J219_12_Q3 2012 52 J209_17_Q1 2017 114 J220_12_Q1 2012 53 J209_17_Q2 2017 115 J220_12_Q2 2012 54 J209_17_Q3 2017 116 J220_12_Q3 2012 55 J212_17_Q1 2017 117 J221_12_Q1 2012 56 J212_17_Q2 2017 118 J221_12_Q2 2012 57 J212_17_Q3 2017 119 J221_12_Q3 2012 58 J214_17_Q1 2017 120 J223_12_Q1 2012 59 J214_17_Q2 2017 121 J223_12_Q2 2012 60 J214_17_Q3 2017 122 J223_12_Q3 2012 61 J216_17_Q1 2017 123 J225_12_Q1 2012 62 J216_17_Q2 2017 124
APPENDIX 11
Canoco Environmental Variables Gazetteer
Appendix 11 Canoco Environmental Variables Gazetteer
1 VegHt 2 RUSH% 2x2 - not used 3 Grad% 4 Aspect - not used 5 Elev 6 SoilpH 7 SoilP 8 SoilK