Evaluating the Current Weed Community in Wild Blueberry Fields and IPM Strategies for Spreading Dogbane (Apocynum Androsaemifolium)

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Evaluating the Current Weed Community in Wild Blueberry Fields and IPM Strategies for Spreading Dogbane (Apocynum androsaemifolium)

Anthony G. Ayers University of Maine, [email protected]

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Recommended Citation Ayers, Anthony G., "Evaluating the Current Weed Community in Wild Blueberry Fields and IPM Strategies for Spreading Dogbane (Apocynum androsaemifolium)" (2020). Electronic Theses and Dissertations. 3321. https://digitalcommons.library.umaine.edu/etd/3321

This Open-Access Thesis is brought to you for free and open access by DigitalCommons@UMaine. It has been accepted for inclusion in Electronic Theses and Dissertations by an authorized administrator of DigitalCommons@UMaine. For more information, please contact [email protected]. EVALUATING THE CURRENT WEED COMMUNITY IN WILD BLUEBERRY FIELDS AND IPM STRATEGIES FOR

SPREADING DOGBANE (Apocynum androsaemifolium)

Anthony Ayers

B.A. SUNY College of Environmental Science and Forestry, 2012

A THESIS

Submitted in Partial Fulfillment of the

Requirements for the Degree of

Master of Science

(in Plant, Soil and Environmental Sciences)

The Graduate School

The University of Maine

December 2020

Advisory Committee:

Lily Calderwood, Extension Wild Blueberry Specialist and Assistant Professor of Horticulture, Advisor

Eric Gallandt, Professor of Weed Ecology

Seanna Annis, Associate Professor of Mycology

EVALUATING THE CURRENT WEED COMMUNITY IN WILD BLUEBERRY FIELDS AND IPM STRATEGIES FOR SPREADING DOGBANE (Apocynum androsaemifolium)

By Anthony Ayers

Thesis Advisor: Dr. Lily Calderwood

An Abstract of the Thesis Presented in Partial Fulfillment of the Requirements for the Degree of Master of Science (in Plant, Soil and Environmental Sciences) December 2020

Lowbush blueberry (Vaccinium angustifolium) is Maine’s third largest-yielding crop (USDA 2020 a). From

2017 – 2019 the three season average yield was 57 million pounds which was harvested from 19,500 acres for a value of $22,468,000 (USDA 2020 c). A common challenge for farmers is the presence of weeds within their fields.

Weeds take up valuable water, shade, nutrients and space that would otherwise be utilized by the lowbush blueberry. Weeds can reduce yield, increase disease incidence and interfere with harvest operations. Up to 84% of yield can be lost because of weed cover (Yarborough 2009; Yarborough and Mara 1997). There has not been a weed survey of lowbush blueberry fields in the state of Maine since 1980 (Yarborough and Bhowmik, 1989). We surveyed twenty fields in the field seasons of 2019-2020. Survey methods were similar to McCully et al. (1991) and used the

Daubenmire Cover Rating System to measure surface area (Daubenmire 1959). Additionally, we interviewed farmers to learn how they have been managing weeds and to learn how they perceive their weeds. We ranked weeds by their frequency and surface area for both organic and conventional fields, allowing us to compare notable weeds and trends between the two systems. Our survey found more species and genera of weeds present in fields than

Yarborough and Bhowmik (1989). Interview results showed that most farmers were able to correctly estimate the severity of weed coverage in their fields. The most frequent method of weed control was mowing, followed by string trimmer mowing.

One of the most difficult weeds to manage within wild blueberry fields is spreading dogbane (Apocynum androsaemifolium). It resists at least six common herbicides (NBDAAF 2017) and can form dense patches through its rhizomes (Niering et al. 2001). Yarborough and Marra (1997) found that if left untreated, spreading dogbane

patches reduced yield by 74%. Because of its resilient nature and negative effects on yield, research on spreading dogbane management is a priority. One facet of weed management is the use of biocontrol. While weeds in other agricultural systems have been managed through the use of pathogenic fungi, no research has been published on the use of fungi to manage spreading dogbane. The periodic mowing of woody weeds throughout the growing season has been found to significantly reduce patches of willow (Salix spp.) and white birch (Betula papyrifera

Marshall). We considered if the same cutting strategy could show similar success on dogbane patches. In the summer of 2019, dogbane leaves with leaf spots were collected, and the fungi on these leaf spots were grown on potato dextrose agar. Spores were identified to genus using Malloch (1981). To measure the effectiveness of string trimmer mowing, sixteen patches of dogbane were mowed at different frequencies. Stem height, patch area, and number of stems per patches were collected before each cutting event. Two genera of fungi were found from the leaf spots: Ulocladium and Alternaria. Mowed patches of dogbane grew wider and had more stems than those that were not mowed.

DEDICATION

I’d like to dedicate this thesis to everyone that believed in me. My parents, my friends, and my mentors. Your support means the world to me.

ACKNOWLEDGEMENTS

I’d like to thank the following for helping me directly with this thesis: Dr. Lily Calderwood, Dr. Seanna Annis, Dr. Eric

Gallandt, Brogan Tooley, Mary Michaud, Becky Gumbrewicz, Bill Halteman, Greg Kornelis, Will Peterson, Dr. Henri

Vanhanen, Louis Morin, Dr. Robert Causey, Dr. Bryan Peterson, Sydney Abramovich and Aidan Lurgio.

Thank you to the following funders for contributing to my research assistantship and research activities: National

Institute of Food and Agriculture (NIFA MAFES), University of Maine School of Food and Agriculture, University of

Maine Cooperative Extension, and the Maine Food and Agriculture Center.

TABLE OF CONTENTS

DEDICATION ...... i

ACKNOWLEDGEMENTS ...... ii

LIST OF TABLES ...... v

LIST OF FIGURES ...... vii

LIST OF EQUATIONS ...... ix

1 EVALUATING THE CURRENT WEED COMMUNITY IN LOWBUSH BLUEBERRY FIELDS ...... 1

1.1 Abstract ...... 1

1.2 Introduction ...... 1

1.2.1 Lowbush Blueberry Background ...... 1

1.2.2 Weeds and Weed Surveys in Lowbush Blueberry Fields ...... 2

1.3 Materials and Methods...... 4

1.3.1 Weed Survey ...... 4

1.3.2 Data Analysis ...... 6

1.3.3 Farmer Interviews ...... 7

1.4 Results ...... 8

1.4.1 Weed Survey Results ...... 8

1.4.2 Farmer Interview Results ...... 16

1.5 Discussion ...... 18

1.5.1 Weed Survey Discussion...... 18

1.5.2 Farmer Interview Discussion ...... 19

1.6 Conclusions ...... 20

2 EXPLORING IPM TOOLS FOR SPREADING DOGBANE (Apocynum androsaemifolium)

MANAGEMENT IN LOWBUSH BLUEBERRY FIELDS ...... 21

2.1 Abstract...... 21

iii

2.2 Introduction ...... 22

2.2.1 Lowbush Blueberry Information ...... 22

2.2.2 Weeds in Lowbush Blueberry Fields ...... 22

2.2.3 Spreading Dogbane Biology ...... 23

2.2.4 Spreading Dogbane Management ...... 24

2.3 Materials and Methods ...... 25

2.3.1 String Trimmer Trial ...... 25

2.3.2 String Trimmer Data Analysis ...... 26

2.3.3 Fungi Identification ...... 26

2.4 Results ...... 27

2.4.1 String Trimmer Results ...... 27

2.4.2 Fungi Identification Results ...... 29

2.5 Discussion ...... 30

2.5.1 String Trimmer Discussion ...... 30

2.5.2 Discussion of Fungi ...... 30

2.6 Conclusions ...... 31

BIBLIOGRAPHY ...... 32

APPENDIX ...... 36

BIOGRAPHY OF THE AUTHOR ...... 69

LIST OF TABLES

Table 1.1. The Daubenmire Cover Scale and Corresponding Area Covered as a Percent...... 6

Table 1.2. Key Questions in Farmer Interviews ...... 8

Table 1.3. The Five Most Frequent Weeds Within Conventional and Organic Fields ...... 10

Table 1.4. The Five Weeds that Covered the Most Surface Area by Practice and Year ...... 11

Table 1.5. A Summary of the Weeds Found in This Survey (Genera A-E) ...... 12

Table 1.6. A Summary of the Weeds Found in This Survey (Genera F-O) ...... 13

Table 1.7. A Summary of the Weeds Found in This Survey (Genera P-S) ...... 14

Table 1.8. A Summary of the Weeds Found in This Survey (Genera T-V) ...... 15

Table 1.9. Lowbush Blueberry Cover on Conventional and Organic Fields ...... 15

Table 1.10. The Number of Identified Species Found in Yarborough and Bhowmik (1989)

and in This Survey ...... 16

Table 1.11. The Number of Identified Genera Found in Yarborough and Bhowmik (1989)

and in This Survey ...... 16

Table 1.12. Comparison of Farmer Responses to Field Weed Survey Frequency and Surface Area...... 17

Table 2.1. Data Collection Dates ...... 25

Table 2.2. Treatment Effects ...... 27

Table A.1. Summary Table: Blue Hills Berry Company ...... 38

Table A.2. Summary Table: Coastal Mountain Land Trust...... 40

Table A.3. Summary Table: Coastal Blueberry Company ...... 42

Table A.4. Summary Table: Brodis Farms ...... 44

Table A.5. Summary Table: Nash Farms ...... 46

Table A.6. Summary Table: Burke Hill Farm ...... 48

Table A.7. Summary Table: Cherryfield Foods ...... 50

Table A.8. Summary Table: Greenhorns at Reversing Hall ...... 52

Table A.9. Summary Table: Bridges Farm ...... 54

Table A.10. Summary Table: Scott’s Blueberry Farm ...... 55

Table A.11. Summary Table: Blue Ox Barrens ...... 57

Table A.12. Summary Table: GM Allen & Son ...... 58

Table A.13. Summary Table: Wescogus ...... 59

Table A.14. Summary Table: Blueberry Hill Farm ...... 60

Table A.15. Summary Table: Moon Hill Farm ...... 61

Table A.16. Summary Table: The Passamaquody ...... 63

Table A.17. Summary Table: Lincoln-Sennett ...... 64

Table A.18. Summary Table: Blue Barrens Farm ...... 66

Table A.19. Summary Table: Ewing Fruit Company ...... 68

LIST OF FIGURES

Figure 1.1. A Map Showing Locations and Regions of the Surveyed Lowbush Blueberry Fields

Throughout the Lowbush Blueberry Growing Regions of Maine ...... 4

Figure 1.2. An Example of a Study Site ...... 5

Figure 1.3. Weed Management Strategies ...... 17

Figure 2.1. Spreading Dogbane Leaf Lesion Categories ...... 26

Figure 2.2. Least Square Means: Patch Area ...... 27

Figure 2.3. Least Square Means: Stems per Patch ...... 28

Figure 2.4. Least Square Means: Stem Height ...... 28

Figure 2.5. Ulocladium spores ...... 29

Figure 2.6. Alternaria spores...... 30

Figure A.1. Map: Merril Wild Blueberries ...... 36

Figure A.2. Map: Blue Hills Berry Company ...... 37

Figure A.3. Map: Coastal Mountain Land Trust ...... 39

Figure A.4. Map: Coastal Blueberry Company ...... 41

Figure A.5. Map: Brodis Farms ...... 43

Figure A.6. Map: Nash Farms ...... 45

Figure A.7. Map: Burke Hill Farm ...... 47

Figure A.8. Map: Cherryfield Foods...... 49

Figure A.9. Map: Greenhorns at Reversing Hall ...... 51

Figure A.10. Map: Bridges Farm ...... 53

Figure A.11. Map: Scott’s Blueberry Farm ...... 55

Figure A.12. Map: Blue Ox Barrens ...... 56

Figure A.13. Map: GM Allen & Son ...... 58

Figure A.14. Map: Wescogus ...... 59

Figure A.15. Map: Blueberry Hill Farm ...... 60

vii

Figure A.16. Map: Moon Hill Farm ...... 61

Figure A.17. Map: The Passamaquody ...... 63

Figure A.18. Map: Lincoln-Sennett ...... 64

Figure A.19. Map: Blue Barrens ...... 65

Figure A.20. Map: Ewing Fruit Company ...... 67

viii

LIST OF EQUATIONS

Equation 1.1. The Logit Transformation to Standardize Samples to a Gaussian Distribution Curve. ....7

Equation 2.1. The Linear Equation for the Predicted Patch Area...... 26

CHAPTER 1

1. EVALUATING THE CURRENT WEED COMMUNITY IN LOWBUSH BLUEBERRY FIELDS

1.1. Abstract

Lowbush (wild) blueberry (Vaccinium angustifolium Aiton) is an economically important crop of Maine.

Weeds compete with lowbush blueberries, causing a decrease in yield. Our study aimed to examine the current weed communities of lowbush blueberry and how farmers both perceive and manage weed populations. A total of twenty fields were surveyed in the summers of 2019 and 2020, including both organically and conventionally managed fields. Each broadleaf weed had surface area recorded using the Daubenmire Cover Rating System

(Daubenmire 1959). We found more weed species and genera in our survey than Yarborough and Bhowmik 1989.

Most weeds found in this survey were perennial, likely due to the fact that lowbush blueberry fields are not tilled like other agricultural systems. Overall farmers estimate of the overall level of weed presence within their fields matched our survey results, the most common weed did not match with what we found in this survey. Mowing was the most commonly used weed management strategy by farmers. The second most common weed management strategy was string trimmer mowing.

1.2 Introduction

1.2.1 Lowbush Blueberry Background

Lowbush blueberry (Vaccinium angustifolium Aiton) is a rhizomatous perennial native to Maine. The most recently reported three season (2017-2019) average crop yield was 57 million pounds and worth $22 million (USDA

2019). Lowbush blueberry fields are managed on a two-year cycle. In the fall or spring after harvest, fields are pruned to ground level either by flail mower or by prescribed burn. Lowbush blueberries sprout the following season during what is called the “prune” year when vegetative growth and bud development occurs. During the following year, known as the “crop” year, blueberry plants flower and then develop fruit. This 2-year cycle is necessary to produce new growth and maintain a consistent yield (Yarborough 2009).

1.2.2 Weeds and Weed Surveys in Lowbush Blueberry Fields

Annual and perennial weeds compete with lowbush blueberry for space, nutrients, sunlight and water. For example, two notable weeds of the lowbush blueberry are spreading dogbane (Apocynum androsaemifolium L.) and bracken fern (Pteridium aquilinum (L.) Kuhn). The shade from spreading dogbane and bracken fern can reduce blueberry yield by up to 74% and 81%, respectively (Yarborough and Marra 1997). In addition to yield reduction, weeds can also trap moisture within the crop canopy, potentially increasing the risk for diseases such as Monilinia vaccinii-corymbosi (mummy berry) (Drummond et al 2012). Rakes and mechanical harvesters can have reduced efficacy from the vegetative parts of weeds getting stuck in machinery or from weed seeds contaminating the harvested berries. Fields with many weeds can crush or tear berries (Yarborough 1996).

Lowbush blueberry farmers utilize several different tools as part of integrated pest management (IPM).

Integrated pest management is the utilization of multiple different tools to reduce pests within the environment.

These tools can be cultural, biological, or chemical in nature (NRC 1996). Herbicides have been the major weed IPM tool used by lowbush blueberry farmers for over 50 years. Hexazinone (trade name Velpar) was first recommended in the early 1980’s and was widely accepted for use in lowbush blueberry fields because of its broad-spectrum efficacy in this perennial fruit system. (Jensen and Yarborough 2004). Hexazinone is successful at reducing infestations of grasses and woody perennials, yet resistance has been observed in weeds such as red sorrel (Rumex acetosella L.) (Stopps et al. 2007) and bunchberry (Cornus canadensis L.) (NBDAAF 2017). Although herbicides can be effective, cultural and mechanical weed management tools are employed by both conventional and certified organic producers. Mechanical control has been shown to be effective at reducing infestations of woody weeds in the lowbush blueberry system. Drummond et al. (2011) found that successively cutting down white birch (Betula papyrifera Marshall) saplings twice during the growing season with a string-trimmed mower significantly reduced the number of stems per patch and stem height. Another weed management strategy farmers use is maintaining an optimal soil pH between 4.0 and 4.5. Lowbush blueberries prefer to grow in acidic soils with a pH less than 5.0, while many weeds cannot tolerate such acidic conditions. Elemental sulfur (90%) is commonly applied to fields in order to lower soil pH which increases lowbush blueberry yield and quality while reducing weed presence (Smagula et al. 2009; Smagula and Litten 2003).

Weed surveys inform researchers and farmers about the weeds present in agricultural systems. With this knowledge, farmers are able to evaluate the efficacy of current weed management tools and prioritize management.

Weed surveys can also illustrate how weed management strategies alter the weed community. Werth et al. (2013) surveyed glyphosate-resistant cotton fields between 2008 and 2011. Results were compared to early weed surveys conducted on the same fields where they found increases in glyphosate resistant weed populations. Weed surveys provide information on how to prioritize research to address management of specific weeds.

The most recent weed survey of lowbush blueberry fields in Maine was conducted by Yarborough and

Bhowmik (1989). The survey was incorporated into a study that explored the effects that the herbicide hexazinone had on weed populations. A total of 27 genera of dicot weeds were found in the 14 fields surveyed. Grasses were considered a major weed, as they were found in an average of 51% of the quadrats (144 out of 280 quadrats in the survey). Goldenrod (Solidago spp. L.) was found to be the most frequent dicot weed, having been found in an average of 35% of the quadrats. Meadowsweet (Spirea alba var. latifolia (Aiton) Dippel) covered the highest amount of surface area of the dicots found, where it covered 7.5 m2 (out of 280 m2) (Yarborough and Bhowmik 1989). Since

1980, the global expansion of invasive species ranges, a changing climate, and updates to farming technology may have impacted the Maine lowbush blueberry weed community (Lyu 2020; Wan and Wang 2018; Huang et al. 2011).

Due to these new conditions in which farmers grow lowbush blueberries, this weed survey aimed to evaluate the current weed community.

The objectives of this study were to 1) determine the current weed composition in lowbush blueberry fields,

2) compare weed communities and lowbush blueberry growth between organically and conventionally managed fields, 3) compare results from this weed survey to those of Yarborough and Bhowmik 1989, and 4) evaluate the perceptions that farmers have about weeds in their fields and examine how farmers have been managing their weeds.

1.3 Materials and Methods

1.3.1 Weed Survey

Ten lowbush blueberry fields in Maine were surveyed during the summer of 2019 and another 10 were surveyed during the summer of 2020 (Figure 1.1). Fields were selected to represent the diverse growing regions and include both conventional and organically managed fields. In each region, there was at least one conventionally managed field and one organically managed field surveyed per year. All fields were surveyed in the prune year when weed management practices typically occur.

Figure 1.1 A map showing locations and regions of the surveyed lowbush blueberry fields throughout the lowbush blueberry growing regions of Maine.

Study sites were set up using methodology from McCully et al. (1991). Study sites were established within

5 to 1,000 acre fields. Study site size ranged between 130 and 5,300 m2 (0.032-1.309 acres) depending on the whole field size, terrain, and field access and were placed in fields 1 to 5 meters away from the field edge. While most fields are larger than 5,300 m2, many of the organic fields were considerably smaller than 2,900 m2 (0.717 acres) in size. Within each study site, four transects were placed in an inverted “W” pattern (Figure 1.2). Most Ttransects were on average 21 meters in length. Survey site dimensions were manipulated to fit within the confines of smaller and more oblong fields, so transect length was variable. Five 1-m2 quadrats were evenly placed along each transect.

In each quadrat, the cover of both weeds and lowbush blueberries were rated using the Daubenmire Cover Scale

(Table 1.1) (Daubenmire 1959). One location only had two fields that were each 130 m2, intersected by a road. In this location, each field had half of a study site, where each only had two transects and two edge quadrats. Quadrat area surveyed totaled 400 m2.

All weeds within each quadrat were identified to species when possible. Some weed genera were too difficult to identify to species level and were therefore identified to genus. Identified weeds were given their own

Daubenmire Cover Scale rating. Each field was surveyed twice: once in early summer (June - early July) and once again in late summer (August - early September) to capture weeds in the beginning and end of the growing season.

Figure 1.2 An example of a study site. Four transects placed within an upside down “W” pattern and three edge quadrats. Yellow squares represent quadrats.

Table 1.1 The Daubenmire Cover Scale and corresponding area covered as a percent. Daubenmire Rating Percentage of Area

0 Not present

1 1-5%

2 6-25%

3 26-50%

4 51-75%

5 76-95%

6 96-100%

Weeds can enter lowbush blueberry fields from edge habitats and equipment entering the field. In order to further understand the overlap in weeds along the edge and in the field center, an additional three quadrats were placed on the field edges outside of the main block. Edge quadrats were analyzed separately from the quadrats in the center of the field.

1.3.2 Data Analysis

The frequency at which each weed was observed was calculated. Frequency was defined as the number of quadrats that a given weed was present out of all quadrats. Weed surface area was calculated for identified weeds.

Daubenmire ratings were converted into the midpoints of their representative percentage ranges, which were then converted to area in terms of square meters. Cover values were summed for each category by survey period.

Frequency and weed surface area were averaged by year to compare between conventional and organic fields.

Weeds were then ranked by their overall surface area and frequency under conventional and organic management categories.

In each survey period, the number of genera found in conventional and organic fields were summed and then averaged for the year. Results were rounded down to the lowest whole number. Frequency and surface area were averaged among the four survey periods to create a summary table of weeds found in the survey.

Data for the following was analyzed using JMP (Version 15.2, SAS Institute, Cary, NC). Daubenmire Ratings for lowbush blueberry cover were converted into the midpoints of their represented ranges of area (in terms of square meters). In order to compare blueberry cover between conventional and organic management styles, these ratings were subject to a logit transformation (Equation 1.1). Because cover data was limited to the midpoints of a set range, data was assumed to not follow a normal Gaussian distribution curve. The logit transformation was to ensure the cover data followed a Gaussian distribution curve, improving the reliability of the t-test (Stevens et al.

2016).

Equation 1.1 The Logit Transformation to standardize samples to a Gaussian distribution curve. p = the Daubenmire Rating. (Log(p)) /(1-Log(p))

Both the number of species and genera found were totaled for the survey and placed into categories similar to those of Lyu 2020. The same was done for the weeds found in Yarborough and Bhowmik 1989. Categories were based on the general life cycle of the weed and included: annuals, biennials, herbaceous perennials, woody perennials, ferns and grasses. Life cycles were confirmed through the USDA NRCS Plant Database (USDA 2020 b).

When weeds were only identified to genera, it was assumed that life cycles were limited to species represented in the University of Maine Cooperative Extension’s Weed ID Tool (Calderwood 2020). The number of species and genera present in this survey were compared to those of the 1980 survey in Yarborough and Bhowmik 1989. A table detailing the frequency and surface area of the weeds found on each surveyed field was given to each participating farmer.

1.3.3 Farmer Interviews

Questionnaires were sent to participating farmers via e-mail and mail that participated in our field sampling efforts. Questions were focused on field inputs, farmer perception of weed severity, and weed management strategies (Table 1.2). Results were entered into the Qualtrics survey software.

Table 1.2 Key questions in farmer interviews. Question Asked Purpose

What would you say is the most abundant weed(s) To compare to the most frequently found weeds in the across all of your fields? weed survey. What is the most economically damaging weed(s) To compare to the weed that covered the most surface across all of your fields? area. How weedy are your fields? To establish what the farmer’s perception of the weed pressure of their fields are. Over the past two cycles, how have you managed To see how farmers have been managing their weeds. weeds?

Farmers were asked what they perceived to be their most abundant weeds weed across all of their fields.

Weeds with the highest frequencies and surface area in each field were compared to farmer responses. If the farmer’s answer matched what was found in the field survey, this was seen as an indication that the farmer was aware of the weed severity in their fields and that the field survey results matched farmer perception.

Farmers were asked to rate how weedy their fields were. They were given the following choices: “weed- free” = <10% weed cover of the whole field, “few weeds” = 11-50% weed cover, “many weeds” = 51-90% weed cover, and “mostly weeds” = >91% weed cover. For each rating, the range and average was calculated for both the total frequency and total surface area of the fields. Weed management strategies were tallied and compared to one another.

1.4 Results

1.4.1 Weed Survey Results

2019: The top five most frequent weeds varied between conventional and organic fields (Table 1.3). Red sorrel was the only weed species found to occur within the five most frequent weeds on both organic (10.63% of quadrats) and conventional fields (17.50% of all quadrats). In 2019, conventional fields had an average of 23 weed genera growing. Organic fields had an average of 40 weed genera growing.

2020: Goldenrods in organic fields had the highest frequency (59.00%) and surface area (8.90 m2) of any weed across both conventional and organic fields. Red sorrel was among the most frequent weeds in both organic

(21.50% of quadrats) and conventional fields (7.00% of quadrats). Red sorrel was also found to be within the top five weeds that covered the most surface area in both conventional (0.81 m2) and organic fields (3.01 m2) (Table

1.4). Spreading dogbane was also frequent in both organic (14.50%) and conventional fields (11.00%). Bunchberry was found to be within the top five weeds that covered the most surface area in both conventional (1.97 m2) and organic fields (2.24 m2) (Table 1.4). In 2020, conventional fields had an average of 19 weed genera growing. Organic fields had an average of 38 weed genera growing.

Consistencies were noted in the species of weeds that were highly frequent and covered the most surface area during the entirety of the survey. St. John’s wort (Hypericum perforatum L.) was within the five most frequent weeds in conventional fields during both 2019 (5.50% of quadrats) and 2020 (17.00% of quadrats). In organic fields, goldenrod was consistently within the five most frequently found weeds in both 2019 (11.27% of quadrats) and 2020

(59.00% of quadrats). On organic fields, bunchberry was one of the top five weeds that covered the largest area in

2019 (2.28 m2) and 2020 (2.24 m2). Several summary tables of all weeds found in this survey were created (Table

1.5, Table 1.6, Table 1.7, Table 1.8).

Table 1.3 The five most frequent weeds within conventional and organic fields. Data was averaged from the early summer and late summer survey periods.

2019 Top 5 Frequency Conventional Field Weeds Frequency Organic Field Weeds Frequency Red sorrel (Rumex acetosella L.) 17.50% Canadian mayflower 16.30% (Maianthemum canadense Desf.) American burnweed (Erechtites 10.00% Spreading dogbane 11.90%a hieraciifolius (L.) (Apocynum androsaemifolium L.) / Raf. ex DC.) Bunchberry (Cornus canadensis L.) Blue toadflax 8.80% Brambles (Rubus spp. L.) 11.30% (Nuttallanthus canadensis (L.) D.A. Sutton) Braken fern 5.80% Goldenrod (Solidago spp. L.) 11.27% (Pteridium anquilinum (L.) Kuhn) St. John’s wort 5.50% Red sorrel (Rumex acetosella L.) 10.70% (Hypericum perforatum L.) 2020 Top 5 Frequency Conventional Field Weeds Frequency Organic Field Weeds Frequency St. John’s wort 17.00% Goldenrod (Solidago spp L.) 59.00% (Hypericum perforatum L.) Bunchberry 13.50% Chokeberry (Aronia spp. Medik.) 22.50% (Cornus canadensis L.) Violets (Viola spp. L.) 11.50% Red sorrel (Rumex acetosella L.) 21.50% Spreading dogbane 11.00% Cinquefoil (Potentilla spp. L. ) 15.50% (Apocynum androsaemifolium L.) Poverty oat grass 7.00%a Spreading dogbane 14.50% (Danthonia spicata (L.) P. Beauv. ex (Apocynum androsaemifolium L.) Roem. & Schult.) / Red sorrel (Rumex acetosella L.) A: Weed frequency was the same for mentioned weeds.

Table 1.4 The five weeds that covered the most surface area by practice and year. Surface area was summed in each survey period, and averaged from the two survey periods per year. 2019 Top 5 Surface Area Conventional Field Weeds Surface Organic Field Weeds Surface Area Area (m2) (m2) Bracken fern (Pteridium anquilinum (L.) 3.37 Bunchberry (Cornus canadensis L.) 2.28 Kuhn) Red sorrel (Rumex acetosella L.) 2.04 Brambles (Rubus spp. L.) 1.42 American burnweed (Erechtites 1.22 Mountain laurel (Kalmia latifolia L.) 1.32 hieraciifolius (L.) Raf. ex DC.) Spreading dogbane (Apocynum 0.67 Gray birch (Betula pendula Roth.) 1.28 androsaemifolium L.) Chokecherry (Prunus virginiana L.) 0.47 Poverty oat grass (Danthonia spicata 1.08 (L.) P. Beauv. ex Roem. & Schult.)

2020 Top 5 Surface Area Conventional Field Weeds Surface Organic Field Weeds Surface Area Area (m2) (m2) Bunchberry (Cornus canadensis L.) 1.97 Goldenrod (Solidago spp L.) 8.90

St. John’s wort 1.69 Chokeberry (Aronia spp. Medik.) 3.45 (Hypericum perforatum L.) Poverty oat grass (Danthonia spicata 0.94 Spreading dogbane (Apocynum 3.06 (L.) P. Beauv. ex Roem. & Schult.) androsaemifolium L.) Red sorrel (Rumex acetosella L.) 0.81 Red sorrel (Rumex acetosella L.) 3.01

Violets (Viola spp. L.) 0.78 Bunchberry (Cornus canadensis L.) 2.24

Table 1.5 A summary of the weeds found in this survey (genera A-E). Weed categories included annuals (A), biennials (B), perennials (P), woody weeds (W), ferns (F) and grasses (G). A total of 400 quadrats were surveyed covering a total of 400 m2. Common Name Latin Name Category Average Average Total Frequency Surface Area (m2) Yarrow Achillea millefolium L. P 0.25% 0.02 Red maple Acer rubrum L. W 1.11% 0.68 Alder Alnus spp. W 0.38% 0.06 Spreading dogbane Apocynum androsaemifolium L. P 10.25% 2.55 Wild sarsaparilla Aralia nudicaulis L. P 0.38% 0.05 Chokeberry Aronia spp. W 6.00% 1.90 Milkweed Asclepias syriaca L. P 0.13% 0.04 Asters Aster spp. P 0.88% 0.02 Birch Betula spp. W 0.75% 0.09 Gray birch Betula pendula Roth. W 2.90% 0.83 Fireweed Chamerion angustifolium (L.) P 0.25% 0.02 Holub. Pipsissewa Chimaphila umbellata (L.) P 0.05% 0.01 W.P.C. Barton. Sweet fern Comptonia peregrina (L.) J.M. W 0.38% 0.05 Coult. Canadian horseweed Conyza canadensis (L.) A/B 0.63% 0.07 Cronquist Bunchberry Cornus canadensis L. P 9.63% 3.18 Hawthorne Craetagus spp. W 0.13% 0.01 Oatgrass Danthonia spicata (L.) P. Beauv. G 6.75% 1.62 ex Roem. & Schult. Northern Diervilla lonicera Mill. W 1.50% 0.24 honeysuckle Burnweed Erechtites hieraciifolius (L.) Raf. A 3.25% 0.63 ex DC. Eastern daisy Erigeron annuus (L.) Pers. A 0.88% 0.12 fleabane Common eyebright Euphrasia nemorosa (Pers.) A 1.00% 0.15 Wallr. Cypress spurge Euphorbia cyparissias L. P 0.38% 0.01 Common boneset Eupatorium perfoliatum L. P 0.50% 0.06

Table 1.6 A summary of the weeds found in this survey (genera F-O). Weed categories included: annuals (A), biennials (B), perennials (P), woody weeds (W), ferns (F) and grasses (G). A total of 200 quadrats were surveyed covering a total of 200 m2. Common Name Latin Name Category Average Average Total Frequency Surface Area (m2)

Wild strawberry Fragaria vesca L. P 0.88% 0.12 Wintergreen Gaultheria procumbens L. P 1.00% 0.18 Black huckleberry Gaylussacia baccata (Wangenh.) W 0.25% 0.01 K. Ground Ivy Glechoma hederacea L. P 0.13% 0.01 Hawkweed Hieracium spp. P 4.63% 0.81 Azure bluet Houstonia caerulea L. P 1.38% 0.21 Canadian St. John's Hypericum canadense L. A 0.88% 0.12 wort Orange grass St. Hypericum gentianoides (L.) A 0.50% 0.06 John's wort Britton, Sterns & Poggenb. St. John's wort Hypericum perforatum P 7.88% 1.19 Juniper seedling Juniperus spp. W 0.13% 0.01 Laurel Kalmia latifolia L. W 2.25% 3.11 Wild lettuce Lactuca canadensis L. B 1.00% 0.09 Ox-eye daisy Leucanthemum vulgare Lam. P 1.50% 0.18 Butter and eggs Linaria vulgaris Mill. P 1.00% 0.06 Wild lupine Lupinus perennis L. P 0.13% 0.01 Whorled loosestrife Lysimachia quadrifolia L. P 3.50% 0.75 Swamp candle Lysimachia terrestris (L.) Britton, P 0.25% 0.05 Sterns & Poggenb. Canadian mayflower Maianthemum canadense Desf. P 6.00% 1.56 Narrowleaf cow Melampyrum lineare Desr. A 3.13% 0.28 wheat Bluntleaf sandwort Moehringia lateriflora (L.) Fenzl. P 1.50% 0.09 Sweet Gale Myrica gale L. W 0.25% 0.05 Toadflax Nuttallanthus canadensis (L.) A/B 4.88% 0.40 D.A. Sutton Primrose Oenothera spp. B 0.01% 0.01

Table 1.7 A summary of the weeds found in this survey (genera P-S). Weed categories included: annuals (A), biennials (B), perennials (P), woody weeds (W), ferns (F) and grasses (G). A total of 200 quadrats were surveyed covering a total of 200m2. Common Name Latin Name Category Average Average Total Frequency Surface Area (m2) Pine seedling Pinus spp. W 0.13% 0.01 White pine Pinus strobus L. W 0.13% 0.01 Common plantain Plantago major L. P 0.13% 0.01 Aspen Populus spp. W 0.63% 0.16 Bigtooth aspen Populus grandidenta Michx. W 0.13% 0.01 Cottonwood Populus deltoides W. Bartram ex W 0.25% 0.05 Marshall Quaking aspen Populus tremuloides Michx. W 0.25% 0.02 Cinquefoil Potentilla spp. A/P 4.63% 0.75 White Prenanthes alba L. B/P 0.38% 0.02 rattlesnakeroot Cherry Prunus spp. W 1.75% 0.37 Black cherry Prunus serotina Ehrh. W 0.44% 0.04 Chokecherry Prunus virginiana L. W 3.50% 0.57 Bracken fern Pteridium anquilinum (L.) Kuhn F 3.38% 2.00 Red oak Quercus rubra L. W 0.13% 0.01 Buckthorn Rhamnus cathartica L. W 0.13% 0.01 Rose Rosa spp. W 6.63% 0.72 Brambles Rubus spp. W 4.38% 1.29 Black Eyed Susan Rudbeckia hirta A/B/P 3.38% 0.46 Curly dock Rumex crispus L. P 0.25% 0.05 Red sorrel Rumex acetosella L. P 14.63% 3.30 Willow Salix spp. W 0.13% 0.04 Woodland ragwort Senecio sylvaticus L. A 0.63% 0.07 Blue-eyed grass Sisyrinchium montanum Greene P 0.50% 0.03 Goldenrod Solidago spp. P 18.88% 5.16 Spiny sow thistle Sonchus asper (L.) Hill A 0.13% 0.01 Spiraea Spiraea spp. W 3.50% 0.76 Meadowsweet Spiraea alba Du. Roi. W 3.00% 0.35

Table 1.8 A summary of the weeds found in this survey (genera T-V). Weed categories included: annuals (A), biennials (B), perennials (P), woody weeds (W), ferns (F) and grasses (G). A total of 200 quadrats were surveyed covering a total of 200 m2. Common Name Latin Name Category Average Average Total Frequency Surface Area (m2) Meadow salsify Tragopogon dubius Scop. A/B 0.13% 0.01 Starflower Trientalis borealis Raf. P 0.25% 0.02 Yellow hop clover Trifolium campestre Schreb. A/B 0.63% 0.13 Red clover Trifolium pratense L. B/P 1.38% 0.24 Elm Ulmus spp. W 0.50% 0.30 Common speedwell Veronica officinalis L. P 0.13% 0.01 Viburnum Viburnum spp. W 0.50% 0.12 Vetch Vicia spp. A/P 1.13% 0.13 Violets Viola spp. A 7.25% 1.00

Lowbush blueberry cover was found to be significantly higher on conventional fields than on organic fields within the study site and during the late summer of both years (both P = < 0.001) (Table 1.7). We did not find significant differences in blueberry cover in the early summer of both years. No differences were found in lowbush blueberry cover between conventional and organic fields within the edge quadrats.

Table 1.9 Lowbush blueberry cover on conventional and organic fields.* Time Location Conventional Logit Organic Logit Pooled T-test P-values Early 2019 Study Site 0.0786 0.0331 0.6706 Edges 0.1649 0.1913 0.9233 Late 2019 Study Site 0.8209 0.2906 < 0.001* Edges 0.5188 0.5731 0.8492 Early 2020 Study Site - 0.2304 - 0.2710 0.0569 Edges 0.0283 - 0.0402 0.7918 Late 2020 Study Site 0.6031 0.2238 < 0.001* Edges 0.4544 0.1516 0.2855 *p=0.05

Our survey found more weed species and genera than Yarborough and Bhowmik 1989 (Table 1.10, Table

1.11). Because there were several weeds identified to only genus in both this survey and Yarborough and Bhowmik

(1989), both genus and species were compared. In Yarborough and Bhowmik 1989, woody perennials were the highest category of weeds found in lowbush blueberry fields. While we found a high number of woody perennial weeds, most species/genera that we found were herbaceous perennials.

Table 1.10 The number of identified species found in Yarborough and Bhowmik 1989 and in this survey. Weed Category 1980 2019-2020 Annual 0 13 Biennial 0 9 Perennial 4 30 Woody 11 17 Fern 2 1

Table 1.11 The number of identified genera found in Yarborough and Bhowmik 1989 and in this survey. Weed Category 1980 2019-2020 Annual 2 15 Biennial 1 8 Perennial 10 35 Woody 12 29 Fern 2 1

1.4.2 Farmer Interview Results

Nine of the twenty farmers (45.00%) identified their most frequent weed as the same weed we found to be most frequent at the study site on their field. Seven of the twenty farmers (35.00%) identified their most economically damaging weed as the same weed we found to have the greatest surface area on their field. Fifteen of twenty respondents (75.00%) indicated that they had “many weeds”, while the remaining 25% indicated that they had “few weeds.” No farmer indicated that their field was “weed-free” or “mostly weeds” when describing their fields (Table 1.12).

Table 1.12 Comparison of farmer responses to field weed survey frequency and surface area. Farmer Response on Range of Frequency Average Range of Surface Average Surface Weed Pressures (%) Frequency (%) Area (m2) Area (m2) Many Weeds (n=15) 35%-100% 84% 0.615-14.35 5.40 Few Weeds (n=5) 0-85% 48% 0-7.6 1.95

Farmers implemented a variety of weed-control strategies over the past two cropping cycles (four years)

(Figure 1.3). The most common weed-control strategy was mowing, where farmers use a tractor-mounted flail mower to cut weeds above the lowbush blueberry canopy. Farmers indicated that they have also used mulching with woodchips, hand weeding, string trimmer mowing, soil acidification with sulfur, and herbicides as weed management tactics.

"Over the past two cycles, how have you managed weeds?"

Flail Mowing String-Trimmer Mowing Herbicide Prescribed Burn Hand-Pulling Sulfur Other Weed-management strategies Weed-management 0 2 4 6 8 10 12 14 Farmers

Figure 1.3 Weed management strategies lowbush blueberry farmers implemented in their fields over the past four years.

1.5 Discussion

1.5.1 Weed Survey Discussion

Several weeds were notably widespread and covered a large area in this survey. In both 2019 and 2020, red sorrel was within the top five most frequent weed species in both conventional and organic fields. Red sorrel is an herbaceous creeping perennial that has historically found to be present in many crop systems, including lowbush blueberries. A prior survey in Nova Scotia found red sorrel in 15.70% of the quadrats, making it one of the most frequent weeds in the survey (McCully et al. 1991). A more recent weed survey found red sorrel to now be the most abundant weed in Nova Scotia’s lowbush blueberry fields (Lyu 2020). One of the reasons red sorrel is widespread is due to its reproductive abilities. Red sorrel can produce 124-247 seeds per stem, and it can reproduce through vegetative means from underground shoots. Stems are able to produce seeds in the first year after germination, which can then be further dispersed by agricultural machinery (Stopps et al. 2011). Another factors in red sorrel’s success as a weed is how difficult it can be to manage. Populations of red sorrel can become resistant to herbicides like hexazinone (Li et al. 2014).

Goldenrod was a frequent weed that covered a large amount of surface area. Past surveys have noted goldenrod frequency within lowbush blueberry fields. In Yarborough and Bhowmik (1989), goldenrods were the most frequent dicot, occurring within 35.00% of the quadrats on average. McCully et al. (1991) found goldenrod in

11.70% of the quadrats. While goldenrod has been historically frequent, conventional farmers have successfully controlled it through the use of herbicides. Applications of the pre-emergent herbicide hexazinone followed by applications of the post-emergent herbicide mesotrione applied before flowering led to 90.00% control of goldenrod patches (Boyd and White 2010). In 2020, our survey found it to be both the most frequent weed and cover the most area within organic fields. Because organic fields cannot apply either hexazinone or mesotrione, they are unable to control it as effectively as conventional farms. Future research should address IPM ad organic strategies to managing goldenrod in lowbush blueberry fields.

The composition of the weed communities appeared inconsistent between 2019 and 2020. This could be because only ten surveys were completed each growing season, and because lowbush blueberry fields are variable.

According to our farmer interviews, each farmer had a unique combination of management strategies. Choice of pruning methods, nutrient management, and herbicide choices can alter the weeds present within a field (NBDAAF

2017; Jensen and Yarborough 2004). Because we could only survey ten fields per season, we report a small sample of the lowbush blueberry fields. In 2017, the state of Maine had 485 farms listed on the agricultural census (USDA

2019). Assuming this amount has not changed, we only were able to survey approximately 4% of the lowbush blueberry operations in Maine. We recommend future surveys include more lowbush blueberry operations to improve accuracy.

There was a greater number of weed species and genera found in this survey than Yarborough and

Bhowmik 1989. These results are consistent with Lyu 2020, a weed survey of wild blueberry fields in Nova Scotia.

Lyu 2020 compared their results to those of McCully et al. 1991 and found a similar increase in weed diversity. As expected, the majority of weeds found in this survey were perennials. Lowbush blueberry fields are not tilled, making a favorable environment for perennial weeds.

1.5.2 Farmer Interview Discussion

A majority of farmers interviewed (fifteen of twenty respondents) had claimed that their fields had “many weeds”. Within these fields the average total surface area and average weed frequency were higher than the averages for the fields labeled “few weeds”. These differences in averages suggest that farmers were generally aware of how much weeds were present on their fields. However, most farmers did not correctly identify their most frequent weed (eleven of twenty respondents) or the weed that covered the most area (seven of twenty respondents). While most farmers were aware of the level of weeds their field has, more than half of them did not correctly identify their most frequent weed or their most economically damaging weed. It is possible that the weeds farmers claimed to be their most frequent or most economically damaging were still present, just not as frequent or large as their most frequent or most economically damaging. This highlights the importance of weed surveys as they allow farmers to learn which weeds are actually the most damaging of their fields.

According to our survey, flail mowing was the most common method of weed management (thirteen respondents), followed by string-trimmer mowing (eleven respondents). Technically, flail mowing and prescribed burning are considered pruning strategies, not weed management. However, pruning methods have an impact on weed communities (DeGomez 1988). Mowing is useful in reducing the aboveground biomass of perennial weeds and can remove flowerheads from weeds before they set seed. It is recommended that more than one mowing is

19 done within a season to be effective, as a single mowing can release perennial weeds from apical dormancy (NBDAAF

2017; Yarborough 1996).

1.6 Conclusions

This survey improves upon current knowledge of the weed community in lowbush blueberry fields. As each farmer was given a table summarizing the weeds found in their field, they are able to see which weeds are their most frequent and most economically damaging. The most frequent weeds and weeds covering the most surface area were ranked for organic and conventional fields, indicating which weeds are a priority for future research. This survey also demonstrated how organic and conventional weed management strategies can impact the weed community. The number of species and genera richness in fields has increased since Yarborough and Bhowmik 1989.

Farmer interviews improved our knowledge of how farmers understand and manage their weeds. While farmers understand the abundance of weeds on their field, they can benefit further from the specifics that weed surveys provide. Farmers utilize a variety of strategies to manage weeds but most of them see flail mowing as a weed management strategy.

CHAPTER 2

EXPLORING IPM TOOLS FOR SPREADING DOGBANE (Apocynum androsaemifolium) MANAGEMENT IN LOWBUSH

BLUEBERRY FIELDS

2.1. Abstract

Wild blueberries (Vaccinium angustifolium Aiton) are an important crop for the state of Maine. Many farmers describe weeds as a major concern of theirs. Weed cover has been attributed to increased yield loss and disease incidence (Drummond et al. 2012; Yarborough and Marra 1997). Spreading dogbane (Apocynum androsaemifolium L.) is a troublesome weed of wild blueberry fields as it is difficult to manage and it spreads through underground rhizomes (NBDAAF 2017; Groen 2005). Yarborugh and Mara (1997_ found that if left untreated, spreading dogbane patches could reduce yield by 74%. Because of its difficulty to management and its effect on yield, spreading dogbane management should be a priority for researchers. This paper aims to explore the following:

1) determine the effectiveness of repeated mowing on spreading dogbane patches and 2) identify pathogenic fungi on spreading dogbane. Spreading dogbane leaves with suspected leaf spot were collected during August of 2019.

Leaves were surface sterilized and fungi from suspected leaf spots were cultured onto potato dextrose agar. In the summer of 2020, sixteen dogbane patches were cut just above the lowbush blueberry canopy using a string trimmer at four different frequencies (never, once, twice, three times). Two genera of fungi were found to grow on dogbane:

Ulocladium and Alternaria. Future experiments should investigate if the fungi isolated from spreading dogbane fulfill

Koch’s postulates. Patch area and number of stems per patch increased with mowing events. This change may indicate that string trimmer mowing may not be suitable for managing spreading dogbane. Future experiments should investigate string trimmer mowing over multiple years to measure the long-term effects of cutting for dogbane management.

2.2 Introduction

2.2.1 Lowbush Blueberry Information

Wild lowbush blueberries (Vaccinium angustifolium Aiton) are one of Maine's most economically important crops. In 2019, Maine had 19,500 fruit-bearing acres of wild blueberries, resulting in a yield of 27,200 tons (USDA 2020 C). Wild blueberries are low-growing perennials managed on a two-year cycle. In year one, referred to as the “prune year,” vegetative growth and bud development occurs. In year two, known as the “crop year,” flowers bloom, pollination occurs, and fruit is harvested in August. After harvest, fields are pruned either by tractor- mounted flail mower or a prescribed fire. This biennial cycle maintains high yields, as the second-year growth produces the most berries (DeGomez 1988). Whole field pruning is not detrimental to lowbush blueberry plants, as a majority of wild blueberry biomass (approximately 70%) grows underground (UNH Coop Ext 2016; Drummond et al. 2008).

2.2.2 Weeds in Lowbush Blueberry Fields

Lowbush blueberry yield decreases as weed cover increases. Yarborough and Marra in 1997 studied the negative effects two prominent weeds, bracken fern (Pteridium aquilinum (L.) Kuhn) and spreading dogbane

(Apocynum androsaemifolium L.) had on lowbush blueberry yield. If either are left unmanaged, they could reduce yield by up to 81% and 74%, respectively. Weeds can also create moist microclimates, that may lead to increases in lowbush blueberry disease presence (Drummond et al. 2012).

The use of integrated pest management (IPM) in perennial weed management for lowbush blueberry fields is a topic of interest to both farmers and researchers. IPM is the use of multiple cultural, mechanical, and chemical tools to reduce the presence of a given pest to below a threshold of economic damage (National Research Council

1996). The current methods of integrated pest management used to manage weeds in the lowbush blueberry system include pruning whole fields, cutting woody weeds, string trimming weeds above the blueberry canopy, reducing soil pH below 4.5, mulching, pre and post emergence herbicides (boom sprayer and wiper applied). The seasonal pruning of wild blueberry by either flail mowing or prescribed fire reduces broadleaf weed competition by removing above ground growth to the ground yet pruning alone is not enough to manage weeds in this production system. Drummond et al. (2012) studied how successive cutting events using a string trim mower affected white birch (Betula papyrifera Marshall) and willow (Salix spp. L.) saplings. At least two successive cutting events during

22 one season were required to significantly reduce the height and number of stems of white birch saplings. Three successive cutting events were required to reduce the stem height of willow saplings. Sulfur is typically applied to fields to reduce the soil pH to between 4.0 and 4.5. Lowbush blueberry prefers acidic soil within this range while weed species do not. Grasses are particularly well managed using this technique (Smagula et al. 2009).

2.2.3 Spreading Dogbane Biology

Spreading dogbane is a competitive, native perennial that creates colonies via spreading rhizomes established throughout most of North America, north of Texas (USDA 2020 b; Groen 2005; Niering et al. 2001). It grows in sandy, well-draining soils and can be found in fields and roadsides (Niering et al. 2001; Yarborough and

Mara 1997). Initial ramet emergence occurs in mid-April to early May. On average, the main stem of spreading dogbane can range between 30 and 120 cm tall, with maximum height being achieved in early July. The leaves are ovate, arranged oppositely, and 5-10 cm long. As dogbane is in the milkweed family, white latex can flow from stem and leaf breaks. Flower buds first appear at the end of June. They grow into 8 mm wide flowers that are bell shaped and white with faint red stripes along petals. Flowers develop into fruits at the end of July. Fruits are paired maroon follicles that can be 7.5 to 20 cm long and contain numerous, papery seeds. Individual seeds are 1.8 to 2 mm long.

Seeds are widest at the tip and taper off into pappus, allowing for seeds to be spread via the winds. Plants are also rhizomatous and can spread into localized patches (Wu et al. 2013; Wu et al. 2012; Boyd and Hughes 2011).

Seed germination for spreading dogbane depends on several factors. One of the most important factors is soil depth. Spreading dogbane seeds tend to be more successful germinating close to the surface. As the depth of seeds increase, so does the chance of suicidal seed germination. Seeds that undergo suicidal seed germination do germinate but fail to break the surface. Dogbane seedlings are able to germinate in media as dry as -0.5 mpa, but germination rates decline in drier conditions. Seeds can be stored for up to 16 months in 4 Co and remain viable

(Boyd and Hughes 2011).

2.2.4 Spreading Dogbane Management

Yarborough and Bhowmik (1989) found spreading dogbane within 57% of Maine fields surveyed in 1980.

In addition to its frequency, spreading dogbane is difficult to control as it has been documented to be resistant to at least six common herbicides (NBDAAF 2017). This creates an opportunity for dogbane to spread within lowbush blueberry fields. Spreading dogbane was observed to replace weed species previously controlled with the commonly used herbicide, hexazinone (Yarborough and Bhowmik 1989). The biennial pruning of fields is believed to have no significant effect on spreading dogbane populations (Wu and Boyd 2010). Burning does not affect spreading dogbane, rhizomes have been documented to survive high intensity wildfires (Groen 2005).

Wu and Boyd (2012) found that patches treated with glyphosate had a higher degree of control one year later than patches that were uprooted by hand. However, glyphosate can be very damaging to lowbush blueberry plants. MacEachern-Balodis (2017), conducted a series of experiments utilizing the dogbane leaf beetle (Chrysochus auratus Fabricius) as a biocontrol agent, finding that six feeding adults per ramet significantly reduced leaf dry weight by 4.9 g per leaf. Given that the natural population level of dogbane leaf beetle is 1-2 beetles per ramet, use of this species as a biocontrol agent does not appear to be feasible at this time. While this study investigated an insect for spreading dogbane biocontrol, no research to our knowledge has explored the use of fungal pathogens as a source of biocontrol. Farmers and researchers have observed that spreading dogbane starts to show symptoms of decline in July and August in Maine. Symptoms include yellowing, necrotic spotting, and drooping which could be the signs of either pathogenic fungal attack or opportunistic fungal organisms colonizing plants after senescence is triggered.

Fungal pathogens have been used to successfully control agricultural weeds. The fungal pathogen Colletotrichum gloeosporioides (Penz.) Sacc f. sp. aeschynomene was found to reduce infestations of northern jointvetch

(Aeschynomene virgini (L.) Britton, Sterns & Poggenb.) by 99% when inoculum is applied to Arkansas rice fields

(Daniel et al. 1973).

In an effort to expand the types of IPM tools available for Maine lowbush blueberry growers, we explored fungal presence and successional cutting on spreading dogbane. To our knowledge, little research has been conducted on the mechanical control of spreading dogbane. Because successive cutting with a string trimmer has shown success in controlling patches of woody weeds (Drummond et al. 2012), we explored the use of this method

24 to manage spreading dogbane patches. The objectives of this study were to: (1) determine the effectiveness of repeated mowing on spreading dogbane patches and (2) identify pathogenic fungi on spreading dogbane.

2.3 Materials and Methods

2.3.1 String Trimmer Trial

The experimental design was a completely randomized design with 4 replicates. On June 17th of 2020, sixteen patches of spreading dogbane were located within a 5-acre area in a 1,000-acre commercial lowbush blueberry field in Cherryfield, Maine (44°36′36″N 67°55′46″W). Patches were selected for the experiment if they had clear boundaries and were less than 100 m2 in area and contained more than 10 dogbane plants. Cutting treatments were randomly assigned to patches. Beginning on June 26 and ending on August 7, patches were cut: never (control), once, twice or three times with three weeks between each cutting (Table 2.1).

Table 2.1 Data collection dates. An “x” represents a cutting took place after collecting data. No cutting was administered on August 28th, as that was just a data collection day.

Data Collection Date Treatment June 26 July 17 August 7 August 28 Control 1 Cut X 2 Cuts X X 3 Cuts X X X

Cuttings were accomplished using a Homelite UT33600A string trimmer allowing dogbane to be cut above the lowbush blueberry crop canopy. Measures of spreading dogbane growth were collected every three weeks before cutting occurred and included patch area and number of dogbane stems per patch. Additionally, six dogbane stems were randomly selected for height measurements within each patch. Patch area was recorded using a Trimble

Geoexplorer 6000 (Sunnyvale, CA). The length and width of the patches were recorded using tape measurers at their longest and widest points in case of GPS failure.

2.3.2 String Trimmer Data Analysis

All data was averaged by treatment and date. Results were analyzed in JMP (Version 14.1.0, SAS Institute,

Cary, NC) using an ANOVA with repeated measures at the 0.05 level of significance. Least square means were separated by Tukey’s Test at the 0.05 level of significance. Patch area measured using length and width in the field significantly differed from the actual area found by the GPS. To remedy this, all of the length-width areas and the corresponding areas found using the GPS underwent a linear regression. The general area was substituted into the linear model to find the predicted area, which was much more similar to the GPS area (Equation 2.1).

Equation 2.1 The linear equation for the predicted patch area. X is the area found using the measuring tapes in meters squared. Y is the predicted area in square meters. (r2 = 0.8707)

Y = 1.4716107 + 0.6336406(X)

2.3.3 Fungi identification

In August of 2019, spreading dogbane leaves were collected from fields in Cherryfield (44°42'19.7"N

67°53'43.9"W) and Jonesboro, Maine (44°38'46.5"N 67°38'57.4"W). Leaves were collected when they appeared to have symptoms of leaf spot fungi. Fungal patterns were categorized into three broad groups; “large leaf spots”,

“multiple small leaf spots”, and “leaf spots centered on veins” (Figure 2.1).

Figure 2.1 Spreading dogbane leaf lesion categories: large leaf spots (left), multiple small leaf spots (center), and leaf spots centered on veins (right).

Culturing techniques were similar to those used in Venkatasubbaiah et al. (1992), however the potato dextrose agar was not made with antibiotic properties. In Dr. Seanna Annis’ lab at the University of Maine in Orono, leaves were surface sterilized and cut into small pieces along suspected symptomatic leaf tissue. Leaf pieces were placed in potato dextrose agar and incubated at 20 OC for one to two weeks before being stored in 4 OC. Fungi were

26 isolated through periodic and subsequent culturing. Spores were observed under a microscope and identified to genus using comparisons to Malloch (1981). Diagnoses were compared to the list of known fungi to occur on the dogbane genus found in Farr et al. (1989).

2.4 Results

2.4.1 String Trimmer Results

Significant treatment effects were found in patch area and the number of stems per patch (Table 2.2).

Patch area appeared to get larger the more times patches were mowed with a string trimmer (Figure 2.2). The number of stems per patch was significantly higher in patches that were cut three times than the control patches

(Figure 2.3). Stem height did not show significant treatment effects (Figure 2.4).

Table 2.2 Treatment effects on factors of dogbane patches* Fixed Effects Test P-Value Patch Area < 0.01 Stems per Patch < 0.01 Stem Height 0.07 *p=0.05

40 A

35 A

30 ) 2 25 B

20 C 15 Patch Area (mArea Patch

0 Control 1 Cut 2 Cut 3 Cut Treatments

Figure 2.2 Least square means of patch area by treatment. Different letters denote significant differences (p=0.05).

200 A 180

160 AB 140 B 120

100 B

80 Stem Number Stem 60

0 Control 1 Cut 2 Cut 3 Cut Treatment

Figure 2.3 Least square means of stems per patch by treatment. Different letters denote significant differences (p= 0.05).

40.00

35.00

30.00

25.00

20.00

Stem Height Stem 15.00

10.00

5.00

0.00 Control 1 Cut 2 Cut 3 Cut Treatment

Figure 2.4 Least square means of stem height by treatment.

2.4.2 Fungi Identification Results

Two distinct genera of spores were found from cultured fungi. Ulocladium Preuss spores were found within cultures grown from leaves that had multiple small leaf spots (Figure 2.5). These cultures were grown from leaves collected from Cherryfield. Associated fungal cultures were consistently gray to blackish-green. To our knowledge, there are no species of Ulocladium listed as pathogenic of the dogbane genus in Farr et al. (1989).

Alternaria Nees spores were found in two different cultures (Figure 2.6). One culture was dark gray to black in coloration and grown from a leaf where the leaf spots were “centered on the veins,” found in Cherryfield. The other culture was light gray to brown in coloration and grown from a leaf that had “multiple small leaf spots,” found in

Jonesboro. There are no species of Alternaria listed as being pathogenic on the dogbane genus in Farr et al. (1989).

No fungi were identified from leaves with large leaf spots. Cultures associated with these leaves failed to produce identifiable spores.

Figure 2.5 Ulocladium spores isolated from leaf lesion category “multiple small leaf spots.”

Figure 2.6 Alternaria spores isolated from a leaf where leaf spots were “centered on veins” (left) and where leaf spots were “small and numerous leaf spots” (right).

2.5 Discussion

2.5.1 Discussion of the String Trimmer Experiment

String trimmer mowing had significant effects on both patch area and the number of stems per patch.

Cutting events may have stimulated immediate growth from the rhizome. String trimmer mowing did not have a significant effect on stem height. It is possible that stems regrew in height from cutting events to compensate from being cut.

One of the limitations of this experiment was that patches were only observed for one season. Similar experiments have followed up on their patches of weeds a year later to observe long-term treatment effects

(Drummond et al. 2012). Another limitation was that we only had four replications of treatments. More repetitions would have made for statistically stronger data.

2.5.2 Discussion of Fungi

We found two genera of fungi from isolating leaf tissues: Ulocladium and Alternaria. The Ulocladium genus is primarily composed of saprobes that grow on decaying plant matter and the soil (Runa et al. 2009; Malloch 1981).

Some species of Ulocladium are pathogenic. Ulocladium atrum (Preuss) Sacc. is a pathogen that causes a leaf blight on potatoes. The blight is a damaging epidemic in areas of Iran (Esfahani 2019). Ulocladium chartarum (Preuss) E.

G. Simmons is a pathogen causes leaf blight and wilt on lemon verbena (Aloysia triphylla (L'Hér.) Britton). This wilt was found to infect more than 45% of the plants within Iranian lemon verbena farms and was sometimes fatal

(Zarandi and Sharzei 2015)

The genus Alternaria consists of several species of saprobes and pathogens (Malloch 1981). Alternaria alternata f. sp. mali is the causal agent for a fruit spot of pink lady apples (Malus domestica var. “pink lady ™”) in

Israel. The disease causes fruit to crack and rot, reducing yield by 80% in some orchards (Gur et al. 2017). Several species of Alternaria are responsible for Alternaria leaf blight of brassicas. This can reduce yields of brassica crops by 15- 70% (Nowakowska et al. 2019). While Ulocladium and Alternaria are genera with many saprobic species, there are species that are pathogenic. Future experiments should investigate the pathogenicity of these two genera derived from spreading dogbane and if they fulfill Koch’s postulate.

2.6 Conclusions

Our spreading dogbane successive cutting and pathogenic fungi investigation contributes to the knowledge of spreading dogbane in Maine lowbush blueberry fields. String trimmer mowing may not be an adequate method of managing spreading dogbane, but continued experiments would be required to fully evaluate this weed management method. The fungal genera Ulocladium and Alternaria were both isolated from suspected leaf spots.

While these genera include many saprobes of decaying plant matter, they also include important pathogenic fungi.

Future experiments should investigate if the found fungi can fulfill Koch’s postulate.

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APPENDIX

Figure A.1. Map: Merril Wild Blueberries. Hancock, Maine. 2019. No table accompanies this map as no weeds were found.

Figure A.2. Map: Blue Hills Berry Company. Surry, Maine. 2019.

Table A.1. Summary table: Blue Hills Berries. Surry, Maine. 2019 Common Name Latin Name Early Late Early Late Summer Summer Summer Summer Frequency Frequency Surface Surface Area (m2) Area (m2) Red maple Acer rubrum L. 5% 0% 0.03 0.00 Spreading dogbane Apocynum androsaemifolium L. 5% 5% 0.155 0.16 Gray birch Betula pendula Roth. 5% 0% 0.03 0.00 Bunchberry Cornus canadensis L. 20% 20% 1.77 0.85 Oatgrass Danthonia spicata (L.) P. Beauv. ex 10% 0% 0.76 0.00 Roem. & Schult.

Northern Diervilla lonicera Mill. 5% 0% 0.03 0.00 honeysuckle Laurel Kalmia latifolia L. 5% 10% 0.03 0.19 Canadian Maianthemum canadense Desf. 5% 0% 0.16 0.00 mayflower Narrowleaf cow Melampyrum lineare Desr. 40% 0% 0.52 0.00 wheat Cinquefoil Potentilla spp. 5% 0% 0.16 0.00 Cherry Prunus spp. 15% 15% 0.34 0.47 Brambles Rubus spp. 5% 0% 0.16 0.00 Red sorrel Rumex acetosella L. 5% 5% 0.03 0.03

Grasses 95% 95% 3.12 4.20

Rush 15% 10% 0.22 0.06

Total Weeds 100% 95% 6.28 6.10 Total Surveyed 20 survey quadrats 20

Figure A.3. Map: The Coastal Mountain Land Trust. Camden, Maine. 2019.

Table A.2. Summary table: Coastal Mountain Land Trust. Camden, Maine. 2019 Common Name Latin Name Early Late Early Late Summer Summer Summer Summer Frequency Frequency Surface Surface Area (m2) Area (m2) Red maple Acer rubrum L. 15% 15% 0.09 0.09 Alder Alnus spp. 5% 5% 0.03 0.16 Spreading dogbane Apocynum androsaemifolium L. 10% 20% 0.19 0.25 Milkweed Asclepias syriaca L. 0% 20% 0.00 0.60 Gray birch Betula pendula Roth. 15% 40% 0.34 2.17 Pipsisewa Chimaphila umbellata (L.) W.P.C. 0% 5% 0.00 0.03 Barton. Bunchberry Cornus canadensis L. 25% 30% 0.63 0.78 Oatgrass Danthonia spicata (L.) P. Beauv. ex 45% 0% 1.02 0.00 Roem. & Schult.

Northern Diervilla lonicera Mill. 0% 5% 0.00 0.03 honeysuckle Wild strawberry Fragaria vesca L. 0% 10% 0.00 0.06 Cypress spurge Euphorbia cyparissias L. 0% 10% 0.00 0.31 Hawkweed Hieracium spp. 40% 5% 0.49 0.16 Laurel Kalmia latifolia L. 0% 30% 0.00 2.43 Whorled loosestrife Lysimachia quadrifolia L. 0% 40% 0.00 0.84 Canadian Maianthemum canadense Desf. 70% 40% 0.80 0.24 mayflower Narrowleaf cow Melampyrum lineare Desr. 0% 15% 0.00 0.09 wheat Cottonwood Populus deltoides W. Bartram ex 5% 5% 0.16 0.16 Marshall Cinquefoil Potentilla spp. 10% 0% 0.06 0.00 Cherry Prunus spp. 0% 10% 0.00 0.06 Chokecherry Prunus virginiana L. 0% 30% 0.00 0.43 Buckthorn Rhamnus cathartica L. 5% 0% 0.03 0.00 Rose Rosa spp. 5% 5% 0.03 0.03 Brambles Rubus spp. 40% 45% 0.49 2.20 Red sorrel Rumex acetosella L. 5% 0% 0.03 0.00 Goldenrod Solidago spp. 35% 50% 0.46 1.05 Meadowsweet Spiraea alba Du. Roi. 25% 40% 0.28 0.87 Dandelion Taraxacum officinale F.H. Wigg. 5% 0% 0.03 0.00 Starflower Trientalis borealis Raf. 10% 0% 0.06 0.00 Elm Ulmus spp. 0% 10% 0.00 1.01 Viburnum Viburnum spp. 0% 15% 0.00 0.34 Vetch Vicia spp. 5% 5% 0.03 0.03 Violets Viola spp. 5% 0% 0.03 0.00

Table A.2. cont.

Common Name Early Late Early Late Summer Summer Summer Summer Frequency Frequency Surface Surface 2 2 Area (m ) Area (m ) Grasses 85% 90% 1.51 1.89

Rush 0% 5% 0.00 0.03

Total Weeds 95% 100% 5.65 10.92 Total Surveyed 20 survey quadrats 20

Figure A.4. Map: Coastal Blueberry Company. Union, Maine. 2019.

Table A.3. Summary Table: Coastal Blueberry Company. Union, Maine. 2019 Common Name Latin Name Early Late Early Late Summer Summer Summer Summer Frequency Frequency Surface Surface Area (m2) Area (m2) Oatgrass Danthonia spicata (L.) P. Beauv. ex 15% 0% 0.215 0.00 Roem. & Schult.

Whorled loosestrife Lysimachia quadrifolia L. 5% 5% 0.03 0.03 Brambles Rubus spp. 5% 0% 0.03 0.00 Goldenrod Solidago spp. 5% 0% 0.03 0.00

Grasses 25% 25% 0.4 0.40

Rush 0% 15% 0.00 0.565

Total Weeds 30% 30% 0.62 1.00 Total Surveyed 20 survey quadrats 20

Figure A.5. Map: Brodis Farms. Hope, Maine. 2019.

Table A.4. Summary table: Brodis Farms. Hope, Maine. 2019 Common Name Latin Name Early Late Early Late Summer Summer Summer Summer Frequency Frequency Surface Surface Area (m2) Area (m2) Spreading dogbane Apocynum androsaemifolium L. 5% 0% 0.03 0.00 Asters Aster spp. 0% 5% 0.00 0.16 Gray birch Betula pendula Roth. 0% 5% 0.00 0.03 Bunchberry Cornus canadensis L. 5% 10% 0.03 0.19 Hawkweed Hieracium spp. 5% 0% 0.03 0.00

St. John's wort Hypericum perforatum L. 0% 10% 0.00 0.06

Whorled loosestrife Lysimachia quadrifolia L. 5% 0% 0.03 0.00

Bluntleaf sandwort Moehringia lateriflora (L.) Fenzl. 0% 5% 0.00 0.03 Toadflax Nuttallanthus canadensis (L.) D.A. 15% 20% 0.09 0.25 Sutton Black Eyed Susan Rudbeckia hirta L. 5% 10% 0.03 0.19 Red sorrel Rumex acetosella L. 30% 15% 0.56 0.34 Violets Viola spp. 0% 15% 0.00 0.22

Grasses 30% 25% 0.43 0.40

Sedges 10% 0% 0.19 0.00

Rush 5% 0% 0.03 0.00

Total Weeds 60% 40% 1.46 1.39 Total Surveyed 20 survey quadrats 20

Figure A.6. Map: Nash Farms. Appleton, Maine. 2019.

Table A.5. Summary Table: Nash Farms. Appleton, Maine. 2019 Common Name Latin Name Early Late Early Late Summer Summer Summer Summer Frequency Frequency Surface Surface Area (m2) Area (m2) Alder Alnus spp. 5% 0% 0.03 0.00 Gray birch Betula pendula Roth. 0% 5% 0.00 0.03 Oatgrass Danthonia spicata (L.) P. Beauv. ex 5% 0% 0.38 0.00 Roem. & Schult.

Wild strawberry Fragaria vesca L. 0% 5% 0.00 0.03 Orange grass St. Hypericum gentianoides (L.) Britton, 0% 5% 0.00 0.03 John's wort Sterns & Poggenb.

St. John's wort Hypericum perforatum L. 5% 5% 0.03 0.03 Whorled loosestrife Lysimachia quadrifolia L. 5% 5% 0.03 0.03 Canadian Maianthemum canadense Desf. 5% 0% 0.03 0.00 mayflower Bluntleaf sandwort Moehringia lateriflora (L.) Fenzl. 15% 0% 0.09 0.00 Toadflax Nuttallanthus canadensis (L.) D.A. 35% 15% 0.34 0.22 Sutton Cinquefoil Potentilla spp. 5% 5% 0.03 0.16 Red sorrel Rumex acetosella L. 15% 5% 0.09 0.03 Violets Viola spp. 5% 0% 0.16 0.00

Grasses 95% 90% 2.27 2.24

Sedges 5% 0% 0.03 0.00

Rush 50% 35% 0.55 0.34

Total Weeds 95% 90% 3.75 3.36 Total Surveyed 20 survey quadrats 20

Figure A.7. Map: Burke Hill Farm. Cherryfield, Maine. 2019.

Table A.6. Summary Table: Burke Hill Farm. Cherryfield, Maine. 2019. Common Name Latin Name Early Late Summer Early Late Summer Frequency Summer Summer Frequency Surface Surface Area (m2) Area (m2) Spreading dogbane Apocynum androsaemifolium 15% 15% 0.34 0.47 L. Sweet fern Comptonia peregrina (L.) J.M. 0% 5% 0.00 0.03 Coult. Bunchberry Cornus canadensis L. 5% 0% 0.03 0.00 Oatgrass Danthonia spicata (L.) P. 5% 0% 0.03 0.00 Beauv. Ex Roem. & Schult.

Northern Diervilla lonicera Mill. 0% 5% 0.00 0.38 honeysuckle Burnweed Erechtites hieraciifolius (L.) 30% 70% 0.18 1.90 Raf. Ex DC. Wintergreen Gaultheria procumbens L. 0% 15% 0.00 0.22 Black huckleberry Gaylussacia baccata 0% 5% 0.00 0.03 (Wangenh.) K. Laurel Kalmia latifolia L. 0% 10% 0.00 0.19 Whorled loosestrife Lysimachia quadrifolia L. 20% 10% 0.60 0.89 Narrowleaf cow Melampyrum lineare Desr. 0% 5% 0.00 0.03 wheat Chokecherry Prunus virginiana L. 45% 20% 0.87 0.57 Bracken fern Pteridium anquilinum (L.) 35% 35% 2.49 4.26 Kuhn Grasses 5% 5% 0.03 0.03

Total Weeds 85% 85% 4.14 7.64 Total Surveyed 20 survey quadrats 20

Figure A.8. Map: Cherryfield Foods. Cherryfield, Maine. 2019.

Table A.7. Summary table: Cherryfield Foods. Cherryfield, Maine. 2019. Common Name Latin Name Early Summer Late Summer Early Late Frequency Frequency Summer Summer Surface Surface Area Area (m2) (m2) Spreading dogbane Apocynum 10% 10% 0.19 0.31 androsaemifolium L. Whorled loosestrife Lysimachia quadrifolia L. 5% 0% 0.03 0.00 Narrowleaf cow Melampyrum lineare Desr. 0% 15% 0.00 0.22 wheat Toadflax Nuttallanthus canadensis 0% 5% 0.00 0.03 (L.) D.A. Sutton Cherry Prunus spp. 0% 5% 0.00 0.16 Red sorrel Rumex acetosella L. 15% 15% 0.34 0.69

Grasses 40% 45% 0.49 1.00

Rush 5% 5% 0.16 0.38

Total weed 50% 65% 1.27 2.59 Total Surveyed 20 survey quadrats 20

Figure A.9. Map: Greenhorns at Reversing Hall. Pembroke, Maine. 2019.

Table A.8. Summary table: Greenhorns at Reversing Hall. Pembroke, Maine. 2019. Common Name Latin Name Early Summer Late Summer Early Late Summer Frequency Frequency Summer Surface Area Surface (m2) Area (m2) Alder Alnus spp. 5% 0% 0.03 0.00 Spreading dogbane Apocynum 35% 25% 0.21 0.53 androsaemifolium L. Wild sarsaparilla Aralia nudicaulis L. 5% 5% 0.03 0.16 Asters Aster spp. 0% 15% 0.00 0.09 Northern Diervilla lonicera Mill. 5% 10% 0.03 0.06 honeysuckle Eastern daisy Erigeron annuus (L.) Pers. 5% 0% 0.03 0.00 fleabane Burnweed Erechtites hieraciifolius (L.) 0% 10% 0.00 0.06 Raf. ex DC. Wild strawberry Fragaria vesca L. 0% 5% 0.00 0.03 Common eyebright Euphrasia nemorosa 5% 0% 0.03 0.00 (Pers.) Wallr. Cypress spurge Euphorbia cyparissias L. 0% 10% 0.00 0.19 Hawkweed Hieracium spp. 15% 0% 0.22 0.00 St. John's wort Hypericum perforatum L. 5% 20% 0.03 0.12 Ox-eye daisy Leucanthemum vulgare 5% 5% 0.03 0.03 Lam. Whorled loosestrife Lysimachia quadrifolia L. 0% 10% 0.00 0.19 Canadian Maianthemum canadense 0% 10% 0.00 0.06 mayflower Desf. Bluntleaf sandwort Moehringia lateriflora (L.) 0% 5% 0.00 0.03 Fenzl. Common plantain Plantago major L. 5% 0% 0.03 0.00 Cinquefoil Potentilla spp. 0% 5% 0.00 0.03 Black cherry Prunus serotina Ehrh. 0% 5% 0.00 0.03 Chokecherry Prunus virginiana L. 0% 5% 0.00 0.03 Bracken fern Pteridium anquilinum (L.) 0% 5% 0.00 0.03 Kuhn Rose Rosa spp. 10% 10% 0.31 0.54 Black Eyed Susan Rudbeckia hirta L. 5% 15% 0.03 0.09 Curly dock Rumex crispus L. 5% 0% 0.03 0.00 Red sorrel Rumex acetosella L. 20% 30% 0.12 1.16 Goldenrod Solidago spp. 0% 5% 0.00 0.03 Meadowsweet Spiraea alba Du. Roi. 5% 5% 0.03 0.03 Red clover Trifolium pratense L. 5% 5% 0.03 0.03 Common speedwell Veronica officinalis L. 0% 5% 0.00 0.03 Vetch Vicia spp. 5% 0% 0.03 0.00 Violets Viola spp. 20% 30% 0.12 0.31

Table A.8. cont.

Common Name Early Summer Late Summer Early Late Summer Frequency Frequency Summer Surface Area Surface (m2) 2 Area (m ) Grasses 50% 55% 3.05 2.16

Sedges 5% 0% 0.03 0.00

Rush 0% 50% 0.00 1.28

Total Weeds 65% 85% 4.29 6.07 Total Surveyed 20 survey quadrats 20

Figure A.10. Map: Bridges Farm. Calais, Maine. 2019.

Table A.9. Summary table: Bridges Farm. Calais, Maine. 2019. Common Name Latin Name Early Summer Late Summer Early Late Summer Frequency Frequency Summer Surface Area Surface Area (m2) (m2) Red maple Acer rubrum L. 10% 0% 0.06 0 Birch Betula spp. 0% 5% 0 0.03 Gray birch Betula pendula Roth. 0% 10% 0 0.31 Canadian Conyza canadensis (L.) 10% 15% 0.06 0.22 horseweed Cronquist Bunchberry Cornus canadensis L. 5% 0% 0.03 0 Burnweed Erechtites hieraciifolius (L.) 5% 20% 0.03 0.37 Raf. ex DC. Eastern daisy Erigeron annuus (L.) Pers. 0% 5% 0 0.16 fleabane Ground Ivy Glechoma hederacea L. 5% 0% 0.03 0 Hawkweed Hieracium spp. 15% 0% 0.215 0 Orange grass St. Hypericum gentianoides 0% 15% 0 0.22 John's wort (L.) Britton, Sterns & Poggenb. St. John's wort Hypericum perforatum L. 25% 30% 0.15 0.31 Wild lettuce Lactuca canadensis L. 15% 20% 0.09 0.25 Swamp candle Lysimachia terrestris (L.) 0% 10% 0 0.19 Britton, Sterns & Poggenb.

Bluntleaf sandwort Moehringia lateriflora (L.) 0% 10% 0 0.06 Fenzl. Toadflax Nuttallanthus canadensis 45% 20% 0.27 0.12 (L.) D.A. Sutton White pine Pinus strobus L. 5% 5% 0.03 0.03 Quaking aspen Populus tremuloides 0% 5% 0 0.03 Michx. Chokecherry Prunus virginiana L. 5% 5% 0.03 0.16 Black Eyed Susan Rudbeckia hirta L. 5% 25% 0.03 0.4 Red sorrel Rumex acetosella L. 65% 70% 1.49 0.67 Woodland ragwort Senecio sylvaticus L. 0% 25% 0 0.28 Goldenrod Solidago spp. 10% 5% 0.19 0.16 Meadowsweet Spiraea alba Du. Roi. 5% 5% 0.03 0.03 Dandelion Taraxacum officinale F.H. 5% 5% 0.03 0.03 Wigg. Meadow salsify Tragopogon dubius Scop. 5% 0% 0.03 0 Elm Ulmus spp. 0% 5% 0 0.03 Violets Viola spp. 0% 15% 0 0.22

Grasses 70% 80% 1.05 2.06

Rush 25% 5% 0.525 0.16

Total Weeds 90% 95% 4.74 4.86 Total Surveyed 20 survey quadrats 20

Figure A.11. Map: Scott’s Blueberry Farm. Waldboro, Maine. 2020.

Table A.10. Summary table: Scott’s Blueberry Farm. Waldboro, Maine. 2020. Common Name Latin Name Early Summer Late Summer Early Late Summer Frequency Frequency Summer Surface Area Surface Area (m2) (m2) Wild sarsaparilla Aralia nudicaulis L. 5% 5% 0.03 0.16 Chokeberry Aronia spp. 5% 10% 0.16 0.54 Bunchberry Cornus canadensis L. 55% 60% 2.36 1.46 Wintergreen Gaultheria procumbens L. 5% 10% 0.03 0.41 Black huckleberry Gaylussacia baccata 0% 10% 0.00 0.06 (Wangenh.) K. St. John's wort Hypericum perforatum L. 10% 10% 0.06 0.06 Laurel Kalmia latifolia L. 0% 5% 0.00 0.16 Whorled loosestrife Lysimachia quadrifolia L. 5% 5% 0.09 0.03 Canadian Maianthemum canadense 15% 0% 0.09 0.00 mayflower Desf. Black Eyed Susan Rudbeckia hirta L. 0% 10% 0.00 0.06 Goldenrod Solidago spp. 35% 10% 0.59 0.19 Violets Viola spp. 5% 5% 0.16 0.16

Grasses 35% 0% 0.46 0.00

Total Weeds 85% 80% 3.69 3.46 Total Surveyed 20 survey quadrats 20

Figure A.12. Map: Blue Ox Barrens. Mount Desert Island, Maine. 2020.

Table A.11. Summary table: Blue Ox Barrens. Mount Desert Island, Maine. 2020. Common Name Latin Name Early Summer Late Summer Early Late Summer Frequency Frequency Summer Surface Area Surface Area (m2) (m2) Chokeberry Aronia spp. 60% 95% 0.49 5.00 Birch Betula spp. 15% 15% 0.09 0.21 Gray birch Betula pendula Roth. 0% 15% 0.00 0.34 Bunchberry Cornus canadensis L. 5% 5% 0.03 0.16 Oatgrass Danthonia spicata (L.) P. 60% 0% 1.24 0.00 Beauv. ex Roem. & Schult. Northern Diervilla lonicera Mill. 15% 0% 0.09 0.00 honeysuckle Canadian St. John's Hypericum canadense L. 0% 5% 0.00 0.16 wort St. John's wort Hypericum perforatum L. 0% 5% 0.00 0.03 Laurel Kalmia latifolia L. 10% 0% 0.06 0.00 Wild lupin Lupinus perennis L. 0% 5% 0.00 0.03 Whorled loosestrife Lysimachia quadrifolia L. 5% 10% 0.03 0.19 Narrowleaf cow Melampyrum lineare Desr. 20% 5% 0.12 0.03 wheat Sweet Gale Myrica gale L. 0% 10% 0.00 0.19 Cinquefoil Potentilla spp. 20% 10% 0.12 0.19 White Prenanthes alba L. 0% 5% 0.00 0.03 rattlesnakeroot Chokecherry Prunus virginiana L. 0% 5% 0.00 0.03 Red oak Quercus rubra L. 0% 5% 0.00 0.03 Rose Rosa spp. 5% 5% 0.03 0.16 Brambles Rubus spp. 25% 20% 0.40 0.62 Red sorrel Rumex acetosella L. 5% 0% 0.03 0.00 Goldenrod Solidago spp. 90% 85% 1.64 2.79 Blue-eyed grass Sisyrinchium montanum 0% 5% 0.00 0.03 Greene Spiraea Spiraea spp. 70% 70% 0.92 2.12 Violets Viola spp. 5% 10% 0.06 0.19

Grasses 100% 100% 3.65 3.78

Total Weed 100% 100% 7.98 14.35 Total Surveyed 20 survey quadrats 20

Figure A.13. Map: GM Allen & Son. Orland, Maine. 2020.

Table A.12. Summary table: GM Allen & Son. Orland, Maine. 2020. Common Name Latin Name Early Summer Late Summer Early Late Summer Frequency Frequency Summer Surface Area Surface Area (m2) (m2) St. John's wort Hypericum perforatum L. 0% 5% 0.00 0.03 Butter and eggs Linaria vulgaris Mill. 10% 0% 0.06 0.00 Toadflax Nuttallanthus canadensis 0% 10% 0.00 0.31 (L.) D.A. Sutton Grasses 30% 65% 0.18 0.52

Total Weeds 35% 65% 0.24 0.86 Total Surveyed 20 survey quadrats 20

Figure A.14. Map: Wescogus. Columbia Falls, Maine. 2020.

Table A.13. Summary table: Wescogus. Columbia Falls, Maine. 2020. Common Name Latin Name Early Summer Late Summer Early Late Summer Frequency Frequency Summer Surface Area Surface Area (m2) (m2) Bunchberry Cornus canadensis L. 15% 0% 0.09 0.00 Oatgrass Danthonia spicata (L.) P. 50% 10% 1.25 0.31 Beauv. ex Roem. & Schult.

St. John's wort Hypericum perforatum L. 35% 45% 0.34 1.37 Canadian Maianthemum canadense 0% 5% 0.00 0.16 mayflower Desf. Bracken fern Pteridium anquilinum (L.) 10% 15% 0.19 0.47 Kuhn Red sorrel Rumex acetosella L. 20% 10% 0.25 0.19 Violets Viola spp. 50% 20% 0.68 0.25

Grasses 80% 80% 2.03 2.31

Rush 0% 15% 0.00 0.79

Total Weeds 85% 95% 3.51 5.82 Total Surveyed 20 survey quadrats 20

Figure A.15. Map: Blueberry Hill Farm. Jonesboro, Maine. 2020.

Table A.14. Summary table: Blueberry Hill Farm. Jonesboro, Maine. 2020. Common Name Latin Name Early Summer Late Summer Early Late Summer Frequency Frequency Summer Surface Area Surface Area (m2) (m2) Fireweed Chamerion angustifolium 5% 0% 0.03 0.00 (L.) Holub. Oatgrass Danthonia spicata (L.) P. 10% 0% 0.31 0.00 Beauv. ex Roem. & Schult.

St. John's wort Hypericum perforatum L. 25% 40% 0.40 1.12 Juniper seedling Juniperus spp. 5% 0% 0.03 0.00 Wild lettuce Lactuca canadensis L. 0% 5% 0.00 0.03 Primrose Oenothera spp. 0% 5% 0.00 0.03 Cottonwood Populus deltoides W. 10% 5% 0.06 0.03 Bartram ex Marshall Chokecherry Prunus virginiana L. 0% 5% 0.00 0.16 Red sorrel Rumex acetosella L. 35% 5% 1.04 0.16 Blue-eyed grass Sisyrinchium montanum 5% 0% 0.03 0.00 Greene Goldenrod Solidago spp. 5% 5% 0.16 0.03 Violets Viola spp. 20% 10% 0.12 0.19

Grasses 20% 10% 0.60 0.41

Total Weeds 60% 50% 2.10 1.84 Total Surveyed 20 survey quadrats 20

Figure A.16. Map: Moon Hill Farm. Whiting, Maine. 2020.

Table A.15. Summary table: Moon Hill Farm. Whiting, Maine. 2020. Common Name Latin Name Early Summer Late Summer Early Late Summer Frequency Frequency Summer Surface Area Surface Area (m2) (m2) Yarrow Achillea millefolium L. 5% 5% 0.03 0.03 Chokeberry Aronia spp. 0% 70% 0.00 1.42 Fireweed Chamerion angustifolium 0% 5% 0.00 0.03 (L.) Holub. Hawthorne Craetagus spp. 5% 0% 0.03 0.00 Bunchberry Cornus canadensis L. 45% 45% 1.60 2.55 Northern Diervilla lonicera Mill. 10% 5% 0.06 0.16 honeysuckle Eastern daisy Erigeron annuus (L.) Pers. 5% 15% 0.03 0.22 fleabane Common eyebright Euphrasia nemorosa 5% 30% 0.16 0.43 (Pers.) Wallr. Wild strawberry Fragaria vesca L. 10% 5% 0.19 0.16 Wintergreen Gaultheria procumbens L. 5% 5% 0.03 0.03 Hawkweed Hieracium spp. 60% 45% 1.24 0.90 Azure bluet Houstonia caerulea L. 30% 10% 0.43 0.31 Laurel Kalmia latifolia L. 10% 5% 0.19 0.16 Ox-eye daisy Leucanthemum vulgare 30% 20% 0.18 0.50 Lam. Butter and eggs Linaria vulgaris Mill. 20% 0% 0.12 0.00 Total Surveyed 20 survey quadrats 20

Table A.15. cont.

Common Name Latin Name Early Summer Late Summer Early Late Summer Frequency Frequency Summer Surface Area Surface Area (m2) (m2) Canadian Maianthemum canadense 5% 0% 0.03 0.00 mayflower Desf. Narrowleaf cow Melampyrum lineare Desr. 5% 10% 0.03 0.06 wheat Aspen Populus spp. 0% 20% 0.00 0.50 Bigtooth aspen Populus grandidenta 0% 5% 0.00 0.03 Michx. Cinquefoil Potentilla spp. 55% 50% 0.83 0.80 White Prenanthes alba L. 10% 0% 0.06 0.00 rattlesnakeroot Cherry Prunus spp. 10% 0% 0.06 0.00 Chokecherry Prunus virginiana L. 20% 0% 0.37 0.00 Bracken fern Pteridium anquilinum (L.) 10% 10% 0.19 0.31 Kuhn Rose Rosa spp. 30% 45% 0.91 0.90 Brambles Rubus spp. 15% 15% 0.57 0.69 Black Eyed Susan Rudbeckia hirta L. 15% 50% 0.09 0.55 Willow Salix spp. 5% 0% 0.16 0.00 Goldenrod Solidago spp. 80% 85% 2.56 2.96 Spiraea Spiraea spp. 15% 10% 0.09 0.06 Dandelion Taraxacum officinale F.H. 0% 5% 0.00 0.03 Wigg. Yellow hop clover Trifolium campestre 25% 0% 0.53 0.00 Schreb. Red clover Trifolium pratense L. 20% 25% 0.50 0.40 Vetch Vicia spp. 15% 10% 0.34 0.06 Violets Viola spp. 0% 5% 0.00 0.03

Grasses 100% 100% 2.48 3.65

Rush 0% 15% 0.00 0.34

Total Weeds 100% 100% 10.30 13.79 Total Surveyed 20 survey quadrats 20

Figure A.17. Map: The Passamaquody. Colombia Falls, Maine. 2020.

Table A.16. Summary table: The Passamaquody. Colombia Falls, Maine. 2020. Common Name Latin Name Early Summer Late Summer Early Late Summer Frequency Frequency Summer Surface Area Surface Area (m2) (m2) Spreading dogbane Apocynum 75% 70% 2.60 3.52 androsaemifolium L. Bunchberry Cornus canadensis L. 5% 0% 0.03 0.00 St. John's wort Hypericum perforatum L. 5% 5% 0.03 0.16 Cinquefoil Potentilla spp. 5% 5% 0.16 0.16 Bracken fern Pteridium anquilinum (L.) 10% 0% 0.06 0.00 Kuhn Curly dock Rumex crispus L. 5% 0% 0.16 0.00 Red sorrel Rumex acetosella L. 5% 10% 0.03 0.06 Goldenrod Solidago spp. 10% 10% 0.54 0.79

Grasses 70% 75% 1.17 2.40

Rush 15% 0% 0.09 0.00

Total Weeds 100% 100% 4.87 7.09 Total Surveyed 20 survey quadrats 20

Figure A.18. Map: Lincoln-Sennett. Whitneyville, Maine. 2020.

Table A.17. Summary table: Lincoln-Sennett. Whitneyville, Maine. 2020. Common Name Latin Name Early Summer Late Summer Early Late Summer Frequency Frequency Summer Surface Area Surface Area (m2) (m2) Spreading dogbane Apocynum 65% 45% 0.89 0.52 androsaemifolium L. Bunchberry Cornus canadensis L. 5% 0% 0.03 0.00 Bracken fern Pteridium anquilinum (L.) 0% 5% 0.00 0.03 Kuhn Violets Viola spp. 5% 0% 0.03 0.00

Grasses 15% 10% 0.09 0.06

Total Weeds 75% 50% 1.01 0.65 Total Surveyed 20 survey quadrats 20

Figure A.19. Map: Blue Barrens Farm. Harrington, Maine. 2020.

Table A.18. Summary table: Blue Barrens Farm. Harrington, Maine. 2020. Common Name Latin Name Early Summer Late Summer Early Late Summer Frequency Frequency Summer Surface Area Surface Area (m2) (m2) Oatgrass Danthonia spicata (L.) P. 0% 5% 0.00 0.16 Beauv. ex Roem. & Schult.

Common boneset Eupatorium perfoliatum L. 0% 5% 0.00 0.03 Azure bluet Houstonia caerulea L. 10% 5% 0.06 0.03 Canadian St. John's Hypericum canadense L. 20% 10% 0.12 0.19 wort St. John's wort Hypericum perforatum L. 15% 20% 0.09 0.37 Bluntleaf sandwort Moehringia lateriflora (L.) 5% 0% 0.03 0.00 Fenzl. Toadflax Nuttallanthus canadensis 0% 20% 0.00 0.12 (L.) D.A. Sutton Red sorrel Rumex acetosella L. 100% 95% 3.63 2.27 Goldenrod Solidago spp. 40% 45% 0.99 1.72 Spiny sow thistle Sonchus asper (L.) Hill 0% 5% 0.00 0.03 Violets Viola spp. 30% 25% 0.43 0.65

Grasses 35% 25% 0.71 0.75

Sedges 45% 55% 1.27 2.03

Rush 25% 35% 0.40 0.94

Total Weeds 100% 100% 7.59 8.24 Total Surveyed 20 survey quadrats 20

Figure A.20. Map: Ewing Fruit Company. Warren, Maine. 2020.

Table A.19. Summary table: Ewing Fruit Company. Warren, Maine. 2020. Common Name Latin Name Early Summer Late Summer Early Late Summer Frequency Frequency Summer Surface Area Surface Area (m2) (m2) Milkweed Asclepias syriaca L. 0% 5% 0.00 0.16 Birch Betula spp. 5% 10% 0.03 0.06 Bunchberry Cornus canadensis L. 15% 5% 0.09 0.03 Oatgrass Danthonia spicata (L.) P. 25% 30% 0.28 0.53 Beauv. ex Roem. & Schult.

Common boneset Eupatorium perfoliatum 0% 15% 0.00 0.22 L. Butter and eggs Linaria vulgaris Mill. 5% 0% 0.03 0.00 Narrowleaf cow Melampyrum lineare 5% 5% 0.03 0.03 wheat Desr. Bluntleaf sandwort Moehringia lateriflora (L.) 5% 15% 0.03 0.09 Fenzl. Sweet Gale Myrica gale L. 0% 20% 0.00 0.12 Toadflax Nuttallanthus canadensis 0% 5% 0.00 0.16 (L.) D.A. Sutton Cinquefoil Potentilla spp. 5% 5% 0.16 0.16 Black Eyed Susan Rudbeckia hirta L. 30% 0% 0.43 0.00 Goldenrod Solidago spp. 60% 85% 0.99 2.84 Vetch Vicia spp. 5% 0% 0.03 0.00 Violets Viola spp. 0% 10% 0.00 0.06

Grasses 60% 60% 0.99 0.84

Rush 0% 40% 0.00 0.37

Total Weeds 95% 95% 3.25 5.05 Total Surveyed 20 survey quadrats 20

BIOGRAPHY OF THE AUTHOR

Anthony Ayers was born in Schenectady, New York on August 23, 1990. He was raised in Round Lake, New

York and graduated from Shenendehowa High School in 2008. He attended the State University of New York’s

College of Environmental Science and Forestry and graduated in 2012 with a bachelor’s degree in Environmental

Science. He traveled to Maine and entered the Plant, Soil and Environmental Health graduate program at The

University of Maine in the spring of 2019. Anthony is a candidate for the Master of Science degree in Plant, Soil and

Environmental Science from the University of Maine in December 2020.