Ekhagastiftelsen Final Report Ground Cover Management in Organic

Ekhagastiftelsen

Final Report

Ground cover management in organic apple orchards in South Africa: Trade-offs between above- and belowground ecosystem services

Ansokan 2015-11 (18 months)

Pl's: K. Birkhofer (coordinator, previously Lund University, now BTU Cottbus-Senftenberg), R. Lindborg (Stockholm University), W. Swart (University of the Free State)

Collaborators: M. Addison, P. Adisson, C. S. Bazelet, F. Daramola, D. Conlong, C. Janion Scheepers, C. Kapp, A. P. Malan, S. Storey, N. F. Stokwe (all Stellenbosch University), S. Louw (t 22.04.2018), C. Haddad (both University of the Free State), F. Arvidsson (Lund University), J. Bengtsson (SLU Uppsala), G. Cumming (James Cook University), R. Malinga (University of KwaZulu-Natal)

Coordinator: Prof Klaus Birkhofer, Department of Ecology, Brandenburg University of Technology Konrad-Wachsmann-Allee 6, 03046 Cottbus, Germany

Administrator: Anne Fogelberg, Department of Biology, Lund University, Telephone: 046 222 93 15; [email protected]

1 Contents 1. Introduction ...... 4 2. Material and Methods ...... 7 2.1. Site selection ...... 7 2.2. Ground cover management ...... 10 2.3. Sampling ...... 11 2.4. Farmer interviews ...... 12 3. Results and Discussion ...... 15 3.1. Soil properties ...... 15 3.2. Vegetation ...... 18 3.3. Microbial communities ...... 20 3.3.1. Fluorescein-diacetate analysis (FDA analysis) ...... 20 3.3.2. Active Carbon (AC) ...... 21 3.3.3. Biolog analysis ...... 21 3.3.4. Phospho-lipid fatty acid analysis (PLFA) ...... 23 3.3.5. Next Generation sequencing ...... 24 3.4. Entomopathogenic nematodes and entomopathogenic fungi ...... 25 3.5. Nematodes ...... 25 3.5.1. Community structure ...... 26 3.5.2. Faunal profile ...... 26 3.6. Collembola ...... 29 3.7. Insects ...... 31 3.7.1. Small pitfall traps ...... 31 3.7.2. Large pitfall traps ...... 31 3.7.3. Grasshoppers ...... 34 3.7.4. Web-building spiders and prey ...... 35 3.8. Damage Assessment ...... 39 3.9. Grower interviews ...... 40 3.9.1. Rationale ...... 40 3.9.2. Objectives ...... 40 3.9.3. Management practices and challenges ...... 40 3.9.4. Education, knowledge and needs ...... 42 3.9.5. Perceptions on organic production and barriers to conversion ...... 43 3.9.6. Social, economic and environmental priorities of sustainable agriculture ...... 44 3.9.7. Climate change ...... 45

2 4. Conclusions ...... 46 4.1 . Trade-offs & synergies ...... 46 4.2. Outlook ...... 47

3 1. Introduction

The global demand for organically farmed products is increasing (Willer & Lernoud 2015), as consumers become aware of the lower environmental impact of organic farming (Pearson et al. 2011). Organic growers have to rely on the simultaneous provision of multiple ecosystem services, as they cannot replace natural regulatory processes (e.g. biological control) by artificial inputs (e.g. synthetic pesticides, Zehnder et al. 2007). The provision of individual ecosystem services in organic production systems can be actively supported by management decisions (Marliac et al. 2015), but it remains unknown to what extent individual management practices affect the relationships between multiple above- and belowground ecosystem services (Birkhofer et al. 2018). Here we aim to understand the ecological mechanisms that underlie the simultaneous provision of above- and belowground ecosystem services resulting from different ground cover management options in organic orchards (Kremen & Miles 2012). Ultimately, our study will help growers to make informed decisions about ground cover management in organic orchards, that will lead to synergies between multiple services at the lowest possible management intensity.

Global pome fruit production is affected by a range of ecosystem services, with above- (e.g. biological control, pollination) and belowground (e.g. decomposition, nutrient mineralization) services and disservices (nutrient competition) affecting fruit production and quality (Clothier et al. 2013). South Africa is one of the top 20 apple producing countries in the world (790000 tons) with a total orchard area of 22900 ha (2012 data; FAOSTAT 2015). The country is among Africa's largest organic producers (37466 ha organically managed land in 2013; Willer & Lernoud 2015) and is a net exporter of certified organic apples (mainly to Europe; TIPS & AusAID 2008). Temperate pome fruits are cu rrently only grown organically in a small area of approximately 508 ha (Willer & Lernoud 2015). Our study addresses the major constraints for organic pome fruit production, namely the limited availability of alternative strategies for pest control and nutrient management in soils (Weibel & Haseli 2003, Wyss et al. 2005, Peck et al. 2006, Jonsson 2007, Wooldridge et al. 2013).

Organic farmers cannot control pests through the application of synthetic pesticides and therefore to a large extent have to rely on management of habitats to the benefit of natural enemies ("conservation biological control", Barbosa 1998). A range of natural enemy groups contribute to below- and aboveground biological control in pome fruit orchards, with specialized parasitoids (e.g. Chalcid wasps), aboveground predators (e.g. spiders) and soil-living entomopathogenic fungi and nematodes being important antagonists (Blommers 1994, Prokopy et al. 1996, Hatting et al. 2009, Mody et al. 2011 ). Furthermore, since organic producers cannot rely on inorganic fertilizers, they need to manage nutrient conditions by promoting soil ecosystem services. Both the decomposition of dead organic matter (Birkhofer et al. 2011) and mineralization processes (de Vries et al. 2014) are affected by the composition of soil organism and weed communities. Management effects on these communities and decomposition or mobilization processes can cascade up to affect crop plants (Haynes 1980, Merwin and Stiles 1994, van der Heijden et al. 2008).

Ground cover management in organic orchards generally aims to reduce competition for soil nutrients and water between weeds and fruit trees (Atucha 2011, Andersen et al. 2013) and directly impacts the composition of weed communities in orchards in South Africa (Fourie et al. 2011). These practices hold the potential to indirectly affect natural enemy and pest populations (Mathews et al. 2002, 2004, Bostanian et al. 2004, Miliczky & Horton 2005, Mark6 et al. 2013), soil communities and nutrient conditions (Yao et al. 2005, St. Laurent et al. 2008,

4 Andersen et al. 2013, Pokharel et al. 2015) and tree performance and fruit quality (Mifiarro 2012, Tahir et al. 2015) via alterations of weed communities. Microbial and animal communities are not only affected by management effects on the overall density of weeds, but also strongly respond to weed plant diversity, with distinct soil communities and levels of above- and belowground ecosystem services observed at different plant species (Bezemer et al. 2010, Simon et al. 2011 a, Latz et al. 2015). Effects of ground cover management on the taxonomic and functional diversity of weed communities therefore may simultaneously alter the relationships between multiple ecosystem services (Lavorel and Grigulis 2012). The effects of ground cover management practices on biotic communities have previously been related to the provision of individual ecosystem processes and services in orchards (Haynes 1980, Merwin et al. 1994, Neilsen et al. 2014), as for example biological control services (Wyss et al. 1995, Mark6 et al. 2012) may be reduced in herbicide-free orchards (Weibel & Haseli 2003). However, it has only recently been emphasized that our knowledge about the effect of management practices on trade-offs between multiple ecosystem services is still very poor (Lavorel and Grigulis 2011 , Kragt and Robertson 2014, Setala et al. 2014, Birkhofer et al. 2015). Organic apple production for example often suffers from problems with nutrient and water competition through weeds (Lososova et al. 2011 ). These aspects are particularly relevant as the Western Cape province in South Africa experiences an over three years lasting severe drought period. In contrast to these disservices, organic orchards are known to often have higher microbial activity (Pokharel and Zimmermann 2015), soil quality (Glover et al. 2000, Vogeler et al. 2006), overall biodiversity (Doles et al. 2001 , Simon et al. 2010, 2011 a) and may produce yields and fruit quality that are comparable to conventionally managed orchards (Reganold et al. 2001 , Peck et al. 2006, Roussos and Gasparatos 2009, but see Simon et al. 2011b). Below- and aboveground services may not only be linked indirectly due to shared relationships with different weed plant species. Direct links may exist due to the fact that herbivorous pests are nitrogen limited and that populations often grow faster under higher nitrogen supply from plants (Garratt et al. 2010, Butler et al. 2012, Lohaus and Vidal 2013). It is therefore possible that effects of ground cover management on the decomposition of litter material and mineralization of nutrients cascade up to affect pest populations via effects on the nutrient status and growth condition of apple trees (Hoyt and Burts 1974, Prokopy 1994, Hoagland et al 2008). These cascading effects in turn will alter the role of natural enemies in pest control, as the rapid growth of pest populations on nutrient rich plants may reduce the potential of antagonists to control pest populations. It has been previously shown that both, social learning processes to support management practices and the configuration of economic incentives to reward farmers are key elements to motivate growers to adopt practices (Cullen et al. 2008). It is therefore crucial to identify if there are social constraints towards the application of novel management practices that may for example deviate from "traditional" management and therefore are not taken up by growers. Economic incentives to support individual management practices have the purpose to encourage landowners and growers to act in ways that are considered beneficial to the environment (Hasund 2007, Rigueiro et al. 2009). A diverse range of additional variables including climate, topography, spatial separation between orchards further affect management decisions by growers (Kaine and Bewsell 2008). Understanding how growers perceive economic incentives and how these conditions interplay with aims, ambitions and abilities of growers is a pre-condition for successful management changes (Stenseke 2006).

5 Here, we suggest studying the role of ground cover management practices for weed density and community composition under the canopy of trees in organically managed fruit orchards with the aim to understand how weeds affect below- and aboveground communities and the simultaneous provision of multiple below- and aboveground services and disservices (Fig. 1) . We aim to understand how weeds can be managed to mitigate trade-offs and to maximize synergies between services ("multifunctionality of production systems"; Hector and Bagchi 2007). We hypothesize that: (1) certain levels of weed coverage are beneficial for the simultaneous provision of multiple below- and aboveground services and (2) effects of weeds on microbial and animal communities and trade-offs between services differ between ground cover management options and (3) it is possible to establish ground cover management strategies that are characterized by a certain tolerance towards weeds. We further hypothesize that (4) an improved understanding of the motivation of growers to apply certain ground cover management strategies will improve communication between growers and researchers and can lead to a win-win situation for growers and the environment. Ultimately, an improved understanding of the ecological mechanisms that cause trade-offs and synergies between multiple ecosystem services will help to improve multifunctionality in organic pome fruit production systems at reduced environmental impact.

6 2. Material and Methods 2.1 . Site selection

After the initially identified organic apple farm in the Western Cape went out of production last year (Elgin Organics, for details: http://www.elginorganics.com/), the project partners searched for new organic apple growers. We realized that organic apple production in the Western Cape was even rarer than we originally anticipated. We therefore visited growers in the Western Cape that were not certified organic growers, but either established sustainable approaches or cultivated fruits under organic principles without certification. The following section provides an overview of the farm we visited during the kick-off meeting: At farm Spier, a single old, abandoned pear orchard managed with short term, high density cattle grazing was visited (Fig. 1a). The consortium quickly decided that abandoned orchards cannot be included in the project. At farm Petervale, a single apple orchard cultivated without pesticides for production of apple juice that is exclusively sold on the farm (no picture) and a single small abandoned pear orchard grazed by donkeys and cattle (Fig. 1b) were visited. At farm Bokveldskloof, a single pear orchard which was no treated with pesticides, but received compost (Fig. 1c) and a single pear orchard managed with pesticides (incl. Glyphosate), but only organic fertilizer (Fig. 1d) were visited. All of these orchards and the respective growers lack organic certification and the consortium therefore decided to rather change the fruit crop from apple to pome fruits in general to maintain options to sample in organically certified orchards.

Figure 1 Visited orchards during field site selection: a) abandoned pear orchard on farm Spier, b) abandoned pear orchard on farm Petervale, c) pear orchard which was no treated with pesticides on Farm Bokveldskloof and d) pear orchard which was treated with pesticides on Farm Bokveldskloof

7 The owner of Tierhoek Organics (Mr Bruce Gilson) started farming in 1998. By now approx. 24-30 ha are in production (total farm size = 180 ha) and are certified as organic since 2005. The grower cultivates 6 ha of apricots, 2 ha plum, 1.5 ha quinces and 1.4 ha peaches. Most fruits are used for drying or canning, but apricots and plums are also packed. All orchard plots were irrigated throughout summer on demand with drippers (apricot "imperial" & "bulida", plum & quince) or micro-jets (apricot "super gold", peach). All orchard ground cover is managed by mechanically cutting of weeds under tree canopies 4-5 times a year and removal of the cut material, working rows are only cut 1-2 times a year. The grower uses his own compost, but also has to buy additional compost to satisfy nutrient demand. The grower further applies certified organic fertilizer, chicken manure and liquid guano as fertilizers.

Figure 2 a) the researcher team at their visit to Farm Petervale, b) apricot orchard, c) plum orchard and d) quince orchard at the research Farm Tierhoek

The consortium concluded at the kick-off meeting that it will be impossible to select eight certified organic apple orchards after the main organic apple grower in the region recently sold his farm, which then was immediately converted to conventional management (http://www.elginorganics.com/). The consortium also realized that several of the non-certified, but more sustainably managed orchards were located at very different altitudes or on very different soils. We therefore decided to focus on the fully-organic (since 2005) certified farm Tierhoek. The owner was very supportive and interested in our research and we involved him in the design and research questions from the start of our project. The consortium selected eight organic orchard plots in the four cultivated pome fruits that were available on the farm (two sites of each: apricot. peach, plum and quince). These fruits share several economically important pests with apple and suffer from the same competition for nutrients and water as apple trees in organic orchards. As being part of the pome fruit group (subtribe Malinae of the family Rosaceae) they all share important traits with apple trees. The discussion resulted in priority criteria for the selection of sites within a fruit species: 1.) identical rootstock, 2.) identical fruit variety, 3.) approx. identical planting age. In addition to the eight selected organic study plots, we included two conventional orchard plots on a neighbouring farm (two apricot sites, Table 1). These ten orchard plots were sampled in

8 November/December 2016 (Figure 3) . In addition to our original proposal, we decided to perform a second sampling campaign in June/July 2017. Even though this repeated sampling stressed the project budget, it provides a more solid database. The decisions to add conventional sites as a reference and include a second sampling date both strengthened our results significantly compared to the original proposal.

Table 1 The five pome fruit orchards sampled at Spaarkloof farm on Tierhoek. Note that two quince orchards were sampled due to their small sizes.

Size No. Year Harvest Crop: variety Harvest Time (ha) trees planted 2015/2016

Apricot: Imperial 1.75 974 2005 Nov/Dec 9800 Plum: Southern Belle, Angelino, Songold 1.14 1591 2002 Mar/Apr 1865 Peach: Neethling 1.49 826 1992 Feb/Mar 3060 Quince: Portuguese 0.75 187 2007 May 2860 Quince: Portuguese 0.39 268 2007 May 2860

Spaarkloof Farm 2016/2017 ..... • ..".,..

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Figure 3 Map of the study orchards at Sparkloof (=Tierhoek) farm. Note that two control and two treatment plots were established in each of the single organically managed plum (light blue), peach (light orange) and apricot (dark orange) orchards, but that only one control and treatment plot were established in the two quince (yellow) orchards. The conventionally managed apricot orchard had two control plots, but is not shown on the map.

9 2.2. Ground cover management

The ground cover treatments that were established in the eight organic orchard plots were a) business as usual = 4-5 cuts under the canopy with removal of material and 1-2 cuts in the working row versus b) mow & blow: 4-5 cuts under the canopy and 1-2 cuts in the working row with addition of the cut material ("living mulch") under tree canopies. All mowing was performed mechanically (Figure 4), placement of mulch was performed manually.

I Figure 4 Mowing of the work alley in an orchard plot at Tierhoek.

The treatments were established in October 2016 (Figure 5a&b), so that our sampling in November/December 2016 reflects short-term and our sampling in June/July 2017 longer-term effects of the ground cover treatments.

Figure 5 Ground cover treatments with a) control plot without added mulch under the canopy and b) treatment plot with mulch from cutting the working rows added under the canopy to supress weeds.

10 On average, mulch covered an area of approximately 1.2 m2 below the canopy at a height of 24 cm after treatment establishment in October 2016 and an area of 0.7 m2 with an average height of 9 cm at the time of the second sampling in June 2017 (Figure 6).

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Figure 6 Mean mulch cover and 95% Cl under tree canopies in the treatment plots early (October 2016) and late (June 2017) during the field study with a) width (X), b) breadth (Z) and c) height (Y) of the mulch layer under five randomly chosen trees in each plot. 2.3. Sampling

Most sampling focused on the treatment impact area under the tree canopy and the fruit tree rhizosphere. Samples for microbial measures, soil properties, nematodes (plant-parasitic and free living), entomopathogenic nematodes (EPNs) and entomopathogenic fungi (EPF) were derived from joint soil sampling and identical soil samples. Natural enemies and their prey were

11 collected in different microhabitats (on the tree, below tree canopies and in working rows). Soil properties were analysed from samples taken under the canopy of fruit trees in all study plots in November/December 2016 and were analysed by Ward Laboratories, Kearney, Nebraska, USA in association with Soil Health Solutions, a division of Oakdene Project Sales, Bellville, South Africa. Vegetation was sampled between December 4-5 (2017) in one square meter quadrants adjacent to tree trunks (southwards) and in one square meter quadrants one meter away from the tree trunk. Soil samples, for the analysis of plant-parasitic and fee-living nematodes, EPN and EPF were taken to a level of 30 cm, close to the stem of the tree and transported to a Stellenbosch. At the same time 300 g rhizosphere soil for microbial analysis, was collected from each tree (5 trees per plot) and placed in plastic bags on ice packs for transfer to the laboratory in Bloemfontein. A total of 90 soil samples were thus collected from the 18 subplots at each sampling date. For each of the five analytical procedures to study microbial communities, sub-samples were made from the original 90 samples by combining five subsamples (trees) in each subplot. Thus with 2 subplots = 2 per treatment (= 18 composite samples in total). Soil samples for nematode extraction were collected from the root zone of five randomly selected trees from within the 20 x 20 m plot area designated to each fruit type. These subsamples were transported back to the laboratory where they were thoroughly mixed to comprise one sample per plot per fruit type. Nematodes were extracted from the soil samples by means of the Cobb's decanting and sieving method, in combination with a modified Baermann funnel. The extracted nematodes were counted and identified to genus level. The nematodes were then categorised into various feeding groups.

For the collection of EPNs and EPF, 250 g soil from each of the 18 composite samples were transferred to a 1 L plastic container to which the trap insects, Tenebrio molitor (mealworm) and Galleria me/lone/la (wax moth) larvae were added. Containers were inspected for dead or mycosed insects after 7 and 14 days. Dead insects were washed, dipped in 75% alcohol and placed on a moist filter paper in a petri dish and inspected for EPN. If the dead insects mycosed, spores were sub cultured on Saboraud dextrose agar petri dishes. Identification to species level were done using molecular techniques.

Web-building spiders and their prey were hand collected from all orchard sites for 90 minutes in the morning and for a second 90 min. period in the afternoon between 01 and 28 November 2016 and 12 June and 08 July 2017. All samples were then transported to the University of the Free State in Bloemfontein and identified by F. Arvidsson (Lund University) under supervision of S. Louw and C. Haddad (both University of the Free State).

2.4. Farmer interviews

The study was conducted in the Western Cape Province in South Africa (Figure 7), being one of the main fruit exporting districts in South Africa. The Western Cape is predicted to be heavily affected by climate change, including higher temperatures and more frequent extreme weather events. The current situation is exceptionally alarming due to three consecutive years of severe drought, which has affected the entire agricultural production in the Western Cape. The average annual rainfall in range between 500 - 1500 mm across the province, but due to the rapidly growing urban population, large water demand and short run-off distance from the mountains to the sea, the Western Cape is a water-scarce region (Saldias et al. 2016). The fruit industry, from production, to packing and processing, is an important source of employment in the Western Cape.

12 Figure 7 The study area and location of the ten orchards for grower interviews. Ten fruit growers participated in the study. To cover a range of perspectives, the study includes organic and conventional fruit growers, as well as growers that have adopted a farming practice called nature farming aimed at reducing artificial fertilizer and chemical herbicides by applying mulch and compost (Table 2). Western Cape fruit growers were identified through google searches and contacted by email and phone until the number reached five organic and five non-organic (conventional or nature farming) producers. The growers produce a wide range of different deciduous fruits (apple, pears, nectarines, peaches, apricots, plums, mangoes, lemons, oranges and soft citrus varieties). The sizes of the orchard range from 1-300 hectares and vary in target market and processing of fruits (Table 2). In-depth, semi-structured, interviews were conducted with the owners or orchard managers at their orchards during April 2017 and January 2018. The interviews followed a semi structured interview questionnaire (Appendix 1) and lasted 1-2 hours. The interviews were recorded and transcribed. The data was coded and grouped into themes and analysed. Data collected included: General information: Produce, target market, processing, location, area, additional produce/business, brief history of the orchard, yield and quality of the produce and information about permanent and seasonal labour. Agricultural knowledge of the respondents: Education, "knowledge heritage", ways to keep updated about management practices Maintenance of natural habitats, biodiversity and perceived benefits Management practices: soil health, pest control, weed control, irrigation, water storage and use, pollination, replanting schedule, cover crops Views on organic vs conventional: visions, perceived pros and cons. barriers Challenges: key challenges and uncertainties Understanding of climate change and coping strategies Knowledge gaps and requests

13 Table 2 Overview of participating fruit growers and their orchards: Type of farms, produce, area, market and location. The code refers to type of farm; O=Organic, N=Nature Farming, C=Conventional

Area Code Type offann Produce orchard Market/ processing Location ha Export, local market, 01 Organic Mango, Citrus 30 Clanwilliam drying, juicing Apricots, Plums, 02 Organic Peaches, Quinces, 14.5 Local market, drying Robertson Lemons Prince Alfred 1 1 Juicing 03 Organic Apples Hamlet 04 Organic Lemon, Oranges 100 Export, local market Citrusdal Export, local market, 05 Organic2 Apples juicing, apple cider Gabouw vinegar, jam Ceres/Prince Apples, Pears 144 Export, local class 1 N1 Nature Farming Alfred Hamlet Export, local class 1, 2/3 Conventional/ Apples, Nectarines, C1/N2 300 some pears for Kouebokkeveld Pears 1/3 Nature Farming processing C2 Conventional Table grapes 14 Export Worcester Peaches, Apricots, C3 Conventional 15.5 Canning Robertson Lemon, Citrus C4 Conventional Plums 37 Export, local market Stellenbosch 1Not certified 2Closed down 2016

14 3. Results and Discussion

3.1. Soil properties

Major soil properties were sampled in all orchard sites (Table 3&4). Quince and peach was cultivated on less sandy soils than plum and apricot. The conventionally managed orchard area differs from all organic sites by having a very low content of clay, silt, Mn, Zn and plant available P (Figure 8) . Plum and organically managed apricot sites had a higher Zn and plant available P content than peach and quince sites. The apricot sites in the conventional orchards had the highest sand content. The water holding capacity of soils was by far highest at the organic apricot sites, with lower and variable values at all other sites.

Table 3 Soil texture, water holding capacity (WHC) and pH value of soils in each orchard study area (Apricot CON = conventional)

Soil texture Clay(%) Silt{%) Sand(%) WHC (mm/m) pH (KCI) QUINCE 1 21 26 53 90.2 5.5 QUINCE 2 19 28 53 110.1 6.2 PLUM 1 13 16 71 114.8 6.7 PLUM 2 11 16 73 103.5 6.7 PEACH 1 17 22 61 94.7 6.4 PEACH 2 21 24 55 127.2 6.4 APRICOT 1 13 16 71 145.2 6.7 APRICOT2 13 16 71 141 .1 6.7 APRICOT CON. 7 6 87 121.4 4.7

Table 4 Nutrient levels of soils in each orchard study area

Bray-P(mg/kg) K (mg/kg) Na (cmol/kg) Ca (cmol/kg) Mg (cmol/kg) Cu (mg/kg) QUINCE 1 44 65 0.21 7.08 3.55 12.30 QUINCE 2 45 71 0.44 9.13 4.28 18.00 PLUM 1 337 229 0.54 10.95 4.66 52.60 PLUM2 359 183 0.45 10.88 4.81 57.60 PEACH 1 143 111 0.37 10.42 3.57 48.70 PEACH 2 212 131 0.51 9.99 3.85 56.70 APRICOT 1 417 215 0.57 12.18 4.94 26.10 APRICOT2 442 156 0.52 10.16 4.30 26.10 APRICOT CON. 43 55 0.16 2.64 1.11 20.90

15 Table 4 (continued) Nutrient levels of soils in each orchard study area

Zn (mg/kg) Mn (mg/kg) B (mg/kg) Fe (mg/kg) Co/o S (mg/kg) QUINCE 1 15.30 362.10 0.52 259.00 2.78 9.28 QUINCE2 16.70 391 .10 0.52 254.00 3.19 16.62 PLUM 1 50.50 229.60 1.10 178.00 3.44 58.85 PLUM 2 62.10 253.70 1.40 153.00 3.74 39.52 PEACH 1 33.80 355.50 0.72 181.00 2.99 22.10 PEACH 2 37.30 362.50 1.02 198.00 2.99 39.96 APRICOT 1 71.50 285.20 1.18 215.00 3.49 117.32 APRICOT2 58.30 335.80 0.97 189.00 2.92 52.05 APRICOT CON. 8.20 203.50 0.43 97.00 1.01 18.69

IResemblance : S15 Gow~ 20 Stress: 0.02 Fruit A Quince • -y Plum • Peach + Apricot • Apricot Con . .... Brar·Pf~g ==-

• n /mg,lcg) . (%) Cloy(%) • -----•

Figure 8 Nonmetric multidimensional scaling ordination showing the resemblance between control orchard plots based on their standardized soil properties with vectors for the most discriminating properties between plots. Treatment effects on N (including N03, NH4 and total N), P (including organic and inorganic P), K, volumetric aggregate stability and a soil health index (provided by Soil Health Solutions, Bellville, South Africa) were not significant (F1,9=0.72; P=0.571). Fruit types differed significantly (F4,9=5.22; P=0.001). The conventionally managed Apricot plots had the lowest total N (Figure 9a) and total P values (together with Quince plots, Figure 9b), and the lowest K values (together with peach and quince plots, Figure 9c).

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0 i ,' § !i ,' ~ 2 i 8 ~ I ft.it Figure 9 Mean and 95% Cl for a) nitrogen, b) phosphate and c) potassium levels in soils of all study plots (control and treatment) by fruit type. Apricot Con stands for the two conventionally managed apricot study plots.

Both the volumetric aggregate stability and the soil health index (Figure 1Oa&b) were lowest in the conventionally managed apricot plots, but aggregate stability was also considerably low in the plum plots.

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0 t .. w' 8 6 6 }l ' ~ ~ 6 i 0u ~ Frutt Figure 10 Mean and 95% Cl for a} volumetric aggregate stability and b) soil health index levels in soils of all study plots (control and treatment) by fruit type. Apricot Con stands for the two conventionally managed apricot study plots. 3.2. Vegetation The percentage cover of bare ground, rocks, litter and cryptophytes differed significantly between fruit types (F4,s9=4.15; P<0.001) with peach plots almost having no bare ground (Figure 11 a) and conventionally managed apricot plots having the lowest litter (Figure 11 c), but highest cryptophyte coverage (Figure 11 d). The percentage cover of bare ground, rocks, litter and cryptophytes did not differ significantly between sample location under the canopy or in the work alley (F,,12=0.80; P=0.430).

18 IO a) " b) 10 140 , . i • • a '# • ,0 . 0 • •

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r ,_ Figure 11 Mean and 95% Cl for percentage coverage with a) bare ground, b) rocks, c) litter and d) cryptophytes in all study plots (control and treatment) by fruit type. The percentage cover of bare ground, rocks, litter and cryptophytes differed significantly between treated and untreated trees in organically managed orchards (F1 ,so=4.04; P=0.027). The percentage of bare ground was higher in the treatment plots (22.3% vs. 13.6%), but the percentage of litter was lower (40.5% vs. 52.3%, Figure 12a&b). a)

,. .. • ..

-i •. . J_ ! J Figure 12 Mean and 95% Cl for percentage coverage- in treatment and control plots with a) bare ground and b) litter across all organically managed fruit types.

19 Considering the species composition of plant communities based on plant species that were observed in at least six survey plots (26 species), fruit type (F3,49=8. 21; P<0.001) affected it significantly, but depending on the treatment level (fruit type x treatment level, F3,49=1.59; P=0.030). With sample location having no significant effect on plant species composition (F1 ,49=1.30; P=0.223). The dissimilarity of plant communities between treatment and control trees decreased from quince (78.3%) to apricot (66.7%) to plum (61 .2%) to (54.9%). Among the most discriminating species, Plantago lanceolata was more abundant in control plots of apricot and plum orchards, but more abundant in treatment plots of quince and peach orchards. Cynodon dactylon was absent from treatment plots in quince and plum orchards, but more abundant in treatment plots in apricot plots. Bromus diandrus was more abundant in control plots in quince and apricot plots. All three species are alien species, which can reach high individual densities of up to 39% in local plant communities.

3.3. Microbial communities The diversity of microbial communities is related to the provision of belowground ecosystem services and key groups are analysed using state-of-the art, yet relatively inexpensive methods. In general, none of the five used methods indicated pronounced differences between treatment and control plots for microbial communities. However, we observed considerable differences between the December and July sampling, which is of particular relevance given the ongoing drought conditions in the Western Cape province of South Africa. 3.3.1 . Fluorescein-diacetate analysis (FDA analysis) The rate of FDA hydrolysis (breakdown) in soil is considered a suitable index of overall soil enzyme activity. Bacteria and fungi both produce extra-cellular enzymes to decompose organic matter, and the amount of enzymes in a sample is indicative of the presence, and viability, of the microbial biomass. FDA is hydrolysed by a number of different enzymes, such as proteases, lipases, and esterases. Generally, a correlation between FDA hydrolytic activity and other soil biological parameters such as active C can be found. The ability to hydrolyze FDA is widespread among soil organisms. The product of this conversion is fluorescein, which can be quantified using spectrophotometry. This method is widely applied to measure total activity of microbial enzymes in soil. The activity of mobile enzymes did not differ between treatment and control plots, but was higher in July than in December (Figure 14a&b).

a) Dec 2016: T & C means b) July 2017: T & C means

500

G 50 4 so lOO 400 i ~(J '50 3 0,.1 .HJO l.50 l >0 ).00 ,)00 l.~O 1.00 1 ~l) 0 50 1 00 o.oo 1111 11 O.SO M'RICOT PLl,M (lUINCE PlAlH APll/l,<.I OOO A~R •. 01 PLUM OUINCE PCArll APR/('\!( a TREATMENT a

Figure 14 Results of Fluorescein-diacetate analysis in control and treatment plots in a) December 2016 and b) July 2017.

20 3.3.2. Active Carbon (AC)

The procedure measures the fraction of organic matter in a form readily utilizable as energy source by microorganisms. It measures the fraction of C and nutrients in total % organic matter (%OM) that is readily biologically available for soil organisms and plants. Much of the total %OM is in the form of highly stabile "humus' and is not readily available as "food" for the many beneficial microbes in soil. Humus only very slowly releases carbon for soil microbes and nutrients for plant growth. The method shows a response to soil management sooner than total organic matter changes can be detected. AC is therefore more quickly responsive to soil management practices. For this reason, AC is considered a "leading indicator" of %OM and can inform growers earlier about detrimental conditions. AC is positively correlated with aggregate stability, biological activity and crop yield. The fraction of OM readily available for microbes did not systematically differ between treatment and control plots (Figure 15a&b).

a) Dec 2016: T & c means b) July 2017: T & C means 3000 3000

2500 2500 ·~ 2000 ]., 2000 1500 Ji Jf 1500 ...... E° 1000 e1000 SOO 500 0 APRICOT PLUM I 0 QUINCEI P[ACH APR/CvC I APRICOT PI.UM QUINCE PFACH APR/CvC • TREAlMfNT • CONTROL

Figure 15 Results of active carbon analysis in apricot (Apr), plum (Pim), quince (Qui) and peach (Pch) plots under control (e) or treatment (T) conditions in December 2016 and July 2017. eve stands for the conventionally managed plots. 3.3 .3. Biolog analysis

Community-level physiological profiling (CLPP) has been demonstrated to be effective at

distinguishing spatial and temporal changes in microbial communities. The Biolog EcoPlate TM assay allows testing of a number of ecologically relevant C substrates in soil in order to differentiate between microbial communities present that are able to utilize these substrates. The EcoPlates contain carbon substrates that are known to be plant root exudates or that have previously been found to have a high discriminatory power among soil communities. Communities of organisms will give a characteristic reaction pattern called a metabolic fingerprint. These fingerprint reaction patterns rapidly and easily provide a vast amount of information from a single Biolog MicroPlate. In applied ecological research, EcoPlates are used as both an assay of the stability of a normal population and to detect and assess changes based upon a variable introduced to the environment. Such changes could be determined by both biotic and abiotic factors.

The 31 carbon sources in each of the three replications per plate are allocated to six carbon groups: Ten carboxylic acids, seven carbohydrates, six amino acids, four complex carbon, two amines, and two phosphate-carbons. Carbon substrate utilisation patterns are a measure of microbial diversity and are used to characterise and classify the heterotrophic microbial communities that colonise a particular substrate. Tetrazolium salt is used as an indicator dye

21 that turns blue when the particular carbon source to which it is bound is metabolized. A portion (1 g) of each of the 18 composite soil samples was suspended in 100 ml of sterile, distilled water and shaken on an orbital shaker for 20 min at 20 °C and then incubated at 4 °C for 30 min. 150 µL of each soil suspension was then inoculated into each well of an EcoPlate and incubated at 25 °c. The rate of utilization was indicated by the reduction of the tetrazolium, a redox indicator dye that changes from colourless to purple. The colour development was recorded with a microplate reader (spectrophotometer, BioTek EL X808, A.D.P) at 590 nm, starting at 24 h, and then every 24 h until 72 h. The average well colour development (AWCD) was calculated for each sample by dividing the sum of the optical density data by 31 and data subjected to dendogram and principal component analyses (PCA). AWCD is an indication of inoculum density.

The individual AWCD readings for the 16 plots in the organic orchards and the plot totals were significantly greater than that of the 2 plots in the conventional Apricot orchard at 24 and 48 hours in December and July (Figure 16 a-d). This is therefore a pronounced indication that the conventional apricot soils had very low microbial density. The AWCD readings for Treatment and Control plots in the four organic orchards indicated no differences between Treated and Control plots.

AWC) 11;1 ),t HOUR5 a AW<; l.l4h b

l.!00

I I I I ,11,. l'T,I I •M 111 JI" If •·t ,1 ,. •• 9-U I APR (ari[i PW M (oril QUIM'.£("'111 PEACH l

C AWC.:l48h d l' lM.Jt 1 •• J ... vJ .. L ~ ... h ~

111,, ,, .)(<',, I ., t1i I.I I IJ.. I I II "I' ~ I a •r •I 1 f I A 'II I 11 APR !oral PtUM (or..l OUIIICE {ore} PEACH lor1I APR joonv.) Figure 16 Average well colour development (AWCD) in different fruit type orchards after 24 and 48 hours in December 2016 (blue) and July 2017 (yellow).

22 The CLPP profiles of individual plots confirm that there are differences between the 18 orchards in terms of the relative utilization of the individual 31 carbon sources expressed as a percentage of total carbon utilization. The conventionally managed apricot plots clearly have a very distinct microbial community with generally very low utilization of resources (Figure 17 a&b). The differences between the 16 organic orchards however are less pronounced than differences between them and the two conventional apricot plots.

0.48 D.ti7 a) b) o.n 0.58

D.71 ?: 0.68 ~ .:: :§ 1).12 " '.§ 0.78 ·e "' iii 0.87

D.92

D.'17

Figure 17 Community-level physiological profiles (CLPP) in a) December 2016 and b) July 2017 after 48h. Coding stands for apricot (Apr), plum (Pim), quince (Qui) and peach (Pch) plots under control (C) or treatment (T) conditions. CvC stands for the conventionally managed plots. 3.3.4. Phospho-lipid fatty acid analysis (PLFA) Phospholipid fatty acids are components of the membranes of all organisms and each species has a characteristic fatty acid pattern. To obtain fatty acid profiles, the fatty acids are extracted from soil and the fatty acid pattern is used to determine community composition. The biomass of groups such as gram-negative bacteria, gram-positive bacteria, actinomycetes, fungi and other soil organisms can be estimated by determining the concentration of so-called signature fatty acids which are specific for a given group. PLFA patterns have been used to study the effect of a range of factors on soil microbial communities, e.g. pH or acid rain in forest soils, heavy metal addition or soil amendments. The effect of environmental factors on microbial community structure can also be assessed by PLFA. Examples include effects of management and crop rotation, the introduction of foreign bacterial strains, heavy metal pollution, biosolid application, plant species or salinity.

23 The fungal biomass was higher than bacterial biomass in all plum, quinces and the two conventionally managed apricot plots (Figure 18). There is a shift in dominance from bacterial to fungal biomass in mature ecosystems and systems with a low pH. In highly productive agricultural soils the fungal-to-bacterial ratio will approach one (F/8=1 ), meaning that the biomass of the fungi and bacteria is approximately even. The soils framed with a red box in Fig. X have higher fungal:bacteria ratios, particularly the conventionally managed apricot plots.

FUNGI vs BACTERIA 11ioo.ro 1400.00 1/l .)0,1

~ lU)O.ll) :::,. 0 soooo E C: bOO 00 ,1(X} {l(l 20000 {I {1(} 11111 1111 111 1111I I 11.1. ,... r" ~ .., N ("- -t N N ~ .-i N rl N 19", I" ...... f"',l C!- o_ ~ c.. Ic,,. c,,. 0.. c.. e. e. 0.. c.. 0.. 0.. 0.. ·;::: ...... ' ~~~ ...... _ .._ ...... -- -...... _ V I-' '-' w -u ~ E: u...... - ~ t::: ~ ' > > '~- t::: .!::::. I., V c..a.o.c. e· .§ ~ E ::i :; ·s :; i i :s- ~ ':_... ""::_, ~ <( "(

Figure 18 Fungal to bacterial biomass. Coding stands for apricot (Apr), plum (Pim), quince (Qui) and peach (Pch) plots under control (C) or treatment (T) conditions. CvC stands for the conventionally managed plots. Both, gram-positive and gram-negative bacteria usually decrease in biomass under drought conditions (Figure 19).

C,u.o, , 30000 a) b)

)lllt>O ll)) 00 1111111111~1~ ·:: 111111 11 ih .1111 It .,

a ·lut [)foe .?tllb WT01111; l17

Figure 19 Biomass of a) gram-positive and b) gram-negative bacteria in December 2016 and July 2017. Coding stands for apricot (Apr), plum (Pim), quince (Qui) and peach (Pch) plots under control (C) or treatment (T) conditions. CvC stands for the conventionally managed plots. 3.3.5. Next Generation sequencing The next generation sequencing results at the genus level suggest that microbial communities in quince orchards differed from all other plots at both sampling times (Fig. 20 a&b). Microbial communities in plum and apricot orchards resembled each other more than peach or quince communities.

24 ., 01.. ..,.,lum (•••·•FI ,ndr.l: ,1_JS 1;') .. a) b)

e ~ r/1/Pl " ,, l,

n ~/C/Pl • I.) Apr/CvC/Pl • ; ,... ;, Apr/CvC/P2• i:= ~ E. ~ ' .. "'...

• ~r/Cv<_/Pl Apr/<.:vt/Pl Pth/r/'j 11

,l .II ., . ,n ,. F1 (10U %) F1 (1J.ti'o\)

Figure 20 Next generation sequencing results at the genus level for microbial communities in a) December 2016 and b) July 2017. Coding stands for apricot (Apr), plum (Pim), quince (Qui) and peach (Pch) plots under control (C) or treatment (T) conditions. CvC stands for the conventionally managed plots. 3.4. Entomopathogenic nematodes and entomopathogenic fungi From all soil samples, EPNs were isolated from only one sample, from the quince control orchard. The low number of EPNs was an unexpected result in an organic farming system. The species of EPN was identified as Heterorhabditis bacteriophora, using the ITS region. This nematode is one of the most common nematodes in the Western Cape province. Among the fungi isolated from the soil samples, four species of EPF were identified. Three gene regions were used for fungal species identification, which include the internal transcribed spacer region (ITS}, elongation factor 1-a and beta tubulin. Species from quince plots were: Metarhizium anisop/iae, Beauveria bassiana and Metarhizium robertsii. Species from apricot plots were: M. anisopliae, Metarhizium majus and M. robertsii. Species from plum plots were: B. bassiana and M. anisopliae. All species were previously being reported from South African orchards, except for M. majus. This is the first known report on the occurrence of M. majus in South African soils. 3.5. Nematodes The success of nematodes as bio-indicators is reflected in their ability to provide information regarding succession and fluctuations in decomposition pathways in the soil food web, fertility, nutrient status and acidity of soil as well as the effects of soil pollutants. Through routine analysis of the soil nematode fauna one can rapidly assess responses to management practices in addition to environmental stress, which in turn provides one with decision making conditions for remediation and conservation.

25 3.5.1. Community structure The community composition of nematodes based on genus-level taxonomic resolution differed significantly between fruit types (F3,19=1.78; P=0.019) and sample dates (F1,19=4.11; P<0.001), but not between treatment levels (F1,19=0.34; P=0.953). Quince plots sampled in November 2016 differed from all other plots and markedly differed from the same Quince plots sampled in June 2017 (Figure 21). Several nematode genera were only present in quince plots in June 2017 (Cephalobus, Aphelenchoides, Tylencholaimus}, genera that were more abundant in quince plots in November 2016 include Scutellonema and Tylenchus. These patterns generally reflect temporal patterns across all fruit types. The presence of Criconemoides sp., Meloidogyne sp., Paraty/enchus sp., Pratylenchus sp., Tylenchorynchus sp. and Xiphinema sp. in some plots are of concern since these plant-parasitic nematodes cause significant damage at high population rates to the roots of trees, which can lead to substantial economic losses. Monitoring is recommended to the grower for these plots due to the high numbers of these pests. r~=orm:Log(X+ 1) semblance: $ 17 Bray.Curtis similarity - --- 20 Stress: 0.19 FruitDate A quinceNOV • 'Y peachNOV • plumNOV • apricotNOV 4 quinceJUN • peachJUN • plumJUN ... • .!_apricot~ • ... • • • • • • • • •• • • • • • • • • • • • •

Figure 21 Nonmetric multidimensional scaling ordination showing the resemblance between plots of different fruit types (symbols) and sampling dates (colour) based on their nematode genus composition.

3.5.2. Faunal profile A faunal profile can be defined as "a graphical representation of the condition of the food web in relation to its structure and enrichment as indicated by weighted nematode faunal analysis". Food webs can be defined in the following terms and under the following conditions: their qualification as 'basal' indicates a food web that is stressed due to a limitation of resources, and adverse environmental conditions. A 'structured' classification describes food webs in which resources are reasonably plentiful, or where recovery from stress is happening. An 'enriched' state entails a disturbance of the food webs concerned, with an increased number and variety of resources becoming available, due to organism death or turnover, or due to advantageous shifts in the environment. Accordingly, in referring to 'enriched' and 'structured' conditions, one is not referring to soil chemical or physical characteristics, but to biological characteristics specifically referring to the soil food web. Thus, a soil can be 'healthy' in terms of chemical and physical soil characteristics, but ·unhealthy' when taking the biology

26 component into account the biology component. The nematode faunal analysis was calculated for each fruit type plot at each sampling date. An explanation for the quadrants is given in Figure 22.

Sector A: Soil community enriched but unstructured Sector B: Soil community enriched and structured Sectgr <::: !Resource limited Sector D: Resource depleted with minimal structure

• Maturing • N-enriched • N-enriched • Bacterial • Bacterial • Conducive • Regulated

Figure 22 Interpretation of the nematode fauna! analysis in Figure 24 and implied condition of the soil food web (after Ferris 2001). Figure 23 indicates the changes in the nematode faunal profile for each fruit type after seven months (November to June). The soil food web conditions during the first sampling session (Circles) indicated varying results across all the quadrants. When taking into account the low numbers of nematodes, these values prove to be misleading since such low numbers of nematodes in the soil food web cannot lead to conditions of soil food web structure and adequate enrichment.

The results for sampling in June 2017 is indicated by the squares as well as the yellow circles. The circles indicate that the data points are clustered more closely together than during the previous round of sampling. The fauna! analysis results indicate that the treatments were not successful since not only did the treatments improve their soil health status, but so did all the controls and the conventional orchards, where nothing was done.

Nematode numbers were generally very low which may limit the ability to accurately determine changes in the soil food web due to treatment effects. It has been shown in previous experiments that it may take up to 5 years to indicate treatment effects after mulch applications.

27 Figure 23 Nematode fauna! comparison between treatment and control plots in December 2016 and July 2017 in a) quince, b) peach, c) plum and d) apricot plots.

Nematode numbers were generally very low, which may limit the ability to accurately determine changes in the soil food web due to treatment effects. It has been shown in previous experiments that it may take up to 5 years to indicate treatment effects after mulch applications.

28 3.6. Collembola

Collembola (springtails, Figure 24) are an important group soil mesofauna that contribute to the decomposition of organic matter. Collembola were sampled from litter bags at organic and conventional apricot sites and then identified to the finest possible taxonomic level by Charlene Janion-Scheepers.

Figure 24 Collembola sampled from apricot sites A: Brachystomel/a sp., B: Seira sp. , C: Entomobrya sp., D: Hypogastrura sp. The analyses are still ongoing, but preliminary results suggest that Collembola abundances may be lower in apricot than in peach or plum plots and may also be lower in control versus treatment plots in apricot (Figure 25).

·~~ 2~ 0. -;;"' "ii 20 ::, ....·;; =o Total abundince 15 .5: • Toul species 0...... D § 10 z

Pe.-i(h htterbag Sum apnco t control Sum apricot Plum Utterbl>g lilhHbag t1t!~tftlft11l litte,l,i:g Figure 25 Abundance and species richness of Collembola from litterbag samples in different orchard plots

29 Extractions using a second method (Tullgren extraction) suggests that some Collembola genera were super abundant in the conventionally managed apricot plots, but absent or far less abundant in organically managed orchards (Figure 26).

600 - SOO --

400

QJ u s:: ~ 300 "O s:: Plum Tu llgren ::s ' .Q Conv. Apricot Tullgren et 200 - Apricot Tullgren

100 n y 0 - - ~ .---

30 3.7. Insects 3.7.1 . Small pitfall traps The family composition of insect communities sampled with small pitfall traps differed significantly between dates (F,.20=11 .10; P<0.001), but not between treatment levels

(F,.20=0.69; P=0.719) or fruit types (F3,20=1.30; P=0.152). The most discriminating families between the December 2016 and June 2017 sampling were ants, true bugs of the family Pyrrhocoridae and beetles of the families Curculionidae and Tenebrionidae (Figure 27).

o,, •• a) b)

01 1 °'1 ~ 06 ti .. • " ! ~ rof , j 01

O> _L 0 1

0 . .. 0 . .. N f.. :i ot ·- c) d) T ,o •• • !~ .. .,. .. l ! ~.. 0 --• ... , • . .:.. !: ~ i: ..... o... Figure 27 Mean and 95% Cl for a) Pyrrhocoridae, b) Tenebrionidae, c) Curculionidae and d) Formicidae across all organically managed fruit types in November 2016 and June/July 2017. 3.7.2. Large pitfall traps Beetle abundance and family richness was higher in treatment compared to control plots in three of the four fruit types (exception peach) in December 2016, but not in June 2017 (Figure 28). Both metrics were not generally lower in the conventionally compared to the organically managed plots.

31 a) Coleoptera abundance (individuals) so 45 "'40 ] 35 ] 30 :;:; 25 C: .: }0 ~ 15 r- 10 5 0 I 1. I 1.1. 111 I Control T1 e<1tmem (onventional Con trol lreatmeni- Conventional

)016 2017

a Apritot • f'pach Plum QtUll(P

b) Coleoptera richness (families)

10 ~ 8 C:"' .c: ~ (, ro 0 '1

) 0 1111 I 1111 111. I Control rreaItment Conventional lontrol Treatment Conventional 2016 2017

a Aprioot • PeaCh Plum • nwnce

Figure 28 Coleoptera a) abundance and b) family richness in control and treatment plots of all fruit types per sampling date.

More detailed analyses of the feeding guild distribution in beetle communities of apricot plots suggest that the treatment plots have a more diverse range of feeding guilds compared to the conventional and organic control plots (Figure 29).

Saprophagous a) b) 6"<> c)

Phytophagous 79%

Phytophagous 67%

Figure 29 Percentage of beetle individuals in different feeding guilds in a) organically managed control, b) organically managed treatment and c) conventionally managed apricot plots.

32 It is notable that a new species from the beetle family Curculionidae (Subfamily Entiminae, genus Afrophloeus) was discovered and is currently described. Hymenopteran abundance was always higher in control plots compared to treatment plots in the same fruit type in December 2016, but not in June 2017 when abundances were generally very low (Figure 30). Hymenoptera family richness did not reflect this pattern and was not generally lower in conventionally managed plots.

a) Hymenoptera abundance (individuals) 900 800 ..!!! 700 (1) ~ 600 :2: 500 "O !: 400 I§ 300 ~ 200 100 0 11 I Control ·TreatmPnt·- Conventional Control Treatment Conventional 2016 2017

• Apricot • PeJch • Plum • Quince

b) Hymenoptera richness (families)

1 0 I Control Treatment Conventional Control Trecltmenl Conventional

2016 2017

• Apricot • Peach • Plurn Qumce

Figure 30 Hymenoptera a) abundance and b) family richness in control and treatment plots of all fruit types per sampling date.

33 3.7.3. Grasshoppers Grasshoppers (Orthoptera) were sampled in November 2016 and eight species were recorded from the organically managed plots, with samples being dominated by a single species (Aiolopus meruensis 76% of all individuals). Aiolopus meruensis is a widespread, cosmopolitan species with generalist feeding habits and strong flight. There were significantly fewer grasshoppers observed in quince plots compared to plum, peach and apricot (chi2=8.53, P=0.036, Figure 31).

0 -,-- '

"'<') -,--. 0 <') -:--. .' "'0 .' C . (0 "'N -0 C :, .D< _,__' 0 N D "'- I __._' 0 - ' ' --'--'

Apncot Peach Plum Quince

Crop

Figure 31 Box and whisker plot of the abundance of grasshoppers per fruit type.

34 3.7.4. Web-building spiders and prey

Web-building spiders contribute significantly to the suppression of important pests in fruit tree orchards and therefore play a key role among the natural enemy fauna. There is a strong relationship between structural properties of habitats and their richness and abundance, due to the construction of retreats and capture webs attached to structural elements. The species richness of web-building spiders was more than twice as high in organically managed orchard sites compared to conventionally managed sites (Figure 32, f 4,2s=7.55; P<0.001).

0 10

Cl)

0 5

0 + 1 l orchard Figure 32 Boxplot (median ± 75 and 25 quartiles as boxes, min and max values as whiskers) of species richness (S) of web building spider communities in different fruit orchard sites.

35 The ground cover management treatment did not affect the species richness of spiders significantly. The species richness was lowest in the canopy and higher under the canopy and in the working rows (Figure 33, F2.2s=38.25; P<0.001). 15

10 7;- t . ~ . ) ~! ·• • ~. ) . l .~.! .. - ' - .·"11·.,· ...

0 0

>, >, "O a_ a_ ((I 0 0 C: C: 2 ()"' l3 ~ :;; "O ~ C ::> microhabitat Figure 33 Box plot of species richness (S) web building spider communities in the canopy, under the fruit tree canopy, and in the working rows between trees.

The species composition of web-building spider communities differed significantly between fruit types (Figure 35, F4.2s=6.25; P<0.001), microhabitats (F2.2s=16 .32; P<0.001) and dates (F1.2s=6.21 ; P<0.001 ). Spider communities in the canopy of fruit trees were characterized by high abundances of Neoscona sp. , morphospecies 2 and Gandanameno sp. In 2016 (Figure 34a). Only morphospecies 2 remained a discriminating species for canopy spider communities in 2017 (Figure 34b). In contrast, communities under the canopy and in the working rows were characterized by higher abundances of Larinia bifida in 2017. Apricot (including the conventional plots) and plum spider communities were characterized by high abundances of Metalepthyphantes familiaris in 2016 and higher abundances of Gandanameno sp. In 2017. Spider communities in peach and quince plots on the contrary had higher abundances of Tidarren sp. In 2017.

36 a) 2DSI•~• 0 1• y ------.....,____ y • • y Tidarren sp. I y\ U/oborus sp A •• • A

• _ _ Neoscona A • y •• / A y A Gandanameno sp. (Msp. 2) \ • PlumCanopy Metele~yphantas y • y PlumUnder canopy familiaris·, / • PlumWork road • QuincesCanopy "---- , y QuincesUnder canopy • ------• QuincesWork road • PeachCanopy b) 2D Stress: 0.16 • PeachUndercanopy • Peachwork road ApricotCanopy ~,.-.--~~ y ApricotUnder canopy ApricotWork road 1 Agynate habra A Apricot conventionalCanopy \ Gandaname o sp. I•Apr icot conventionalUnder canopy I ahnta tabulico/a\ \ T A A • Apricot conventionalWork road .• ,?- -- (Msp. 1!.\, A arinia bifida --,.-1a:'-- Crozelulus / . ' (M:sp. 2) A 50 A "ffclt~n sp. uf borus sp. 1 \ A

~ - • T. A ...... __ ------,, •

Figure 34 Non-metric multidimensional scaling ordination based on Bray-Curtis similarities and web building spider species data in different fruit types and microhabitats for a) 2016 and b) 2017. Vectors are added for spider species with multiple correlation coefficient >0.3 to axis scores of study sites. The composition of prey in spider webs differed significantly between fruit types (F4.46=4.07; P<0.001), microhabitats (F2.4s=7.75; P<0.001) and dates (F1,4s=5.19; P<0.001). Most Hemipteran prey was caught in spider webs in peach plots with very low numbers of Hemiptera prey in conventionally managed apricot plots (Figure 35a). Beetle predation was lowest in quince plots and highest in plum plots (Figure 35b).

37 2.0 a)

1.5

:, w 1.0 :c

0.5

0 g f. e t f I l ii 3 2.5 ! b) i

2.0

1.5

..J 0 0 1.0

0.5

0 - g ~ l f l .. i t -0 ~ ~ } orchard Figure 35 Box and whisker plots for a) hemipteran and b) coleopteran prey by web building spiders per fruit type.

Beetle predation was highest in the canopy or under the canopy, with almost no predation on beetles in the alley (Figure 36). Spider predation differed between dates as some minor prey groups were almost exclusively caught in 2016 (e.g. Acari, lsoptera, Orthoptera) or in 2017 (Dermaptera, Psocoptera). 2.5

2.0

1.5 _, 0 0 1.0

0.5 ±

mlccohat>ltat Figure 36 Box and whisker plots for coleopteran prey by web building spiders per microhabitat.

38 3.8. Damage Assessment

Feeding damage on fruits was only assessed in apricot plots (Figure 37), as damage levels were very low in the other fruits.

Figure 37 Feeding damage by arthropods in apricot orchards

Damage due to beetles was 3-4 times higher in the organically managed apricot plots (Apricots south and north) compared to conventionally managed plots (Figure 38). However, damage due to other arthropod pests (e.g. bollworm or thrips) was only observed in the conventionally managed plots, but at very low damage levels.

• Apricots South • Apricots North • Apricots conv

Q) Ol .Q ~ ~ . 0.. I 1f.~1 . I • • ••

Figure 38 Percentage of damaged fruit in apricot orchards by major source of damage

39 3.9. Grower interviews 3.9.1. Rationale

• The demand for organic fruit is increasing, yet organic producers are few. • Fruit production is increasingly challenging in South Africa due to climate change (drought, increased temperatures) and increased input costs (fuel, labour, pesticides, fertilizers) • Organic fruit production is even more challenging, with limited availability of alternative strategies for pest control, soil nutrient management and weed control. • Fruit growers rely on science to establish organic/more sustainable practices/methods/technologies, but there is limited information about what growers need or want. • To promote organic and/or more sustainable fruit production, one must understand the fruit growers' decisions, and their willingness and capacity to adapt new methods. 3.9.2. Objectives This study aims at understanding fruit growers' realities, management practices, challenges and factors that lead to decisions and development of the orchards. Based on the hypothesis that an improved understanding of the motivation of growers to apply certain management strategies will improve communication between growers and researchers and can lead to a win-win situation for growers and the environment. Further, the study aims at understanding the growers' concerns and priorities with regards to social, economic and environmental aspects of farming, and identifying variables that influence growers' decisions to adopt techniques for environmentally sustainable management and barriers to conversion into organic production. 3.9.3. Management practices and challenges All growers, except one who has a 1 ha orchard, irrigate with drip or micro irrigation using probes to optimise water use. Organic growers are more often located near mountains and in valleys, and therefor use gravity rather than pumping their irrigation water (Table 2) . Those growers who use mulching as a management practice experience a reduced water use since the onset of mulching. The two largest growers, who use nature farming as a philosophy, produce much of their mulch on their land, while organic growers are limited to use cuttings of grass and trees from their orchards. Mulching also reduces the use of pre-emerging weed control for the nature farmers. Conventional farmers use chemicals to control weed and pests, while organic and nature farmers use a diversity of methods to control weeds and pests (Table 5).

40 Table 5 Fruit, orchard characteristics and management practices of the interviewed growers

AREA CODE PRODU CE IRRIGATION PEST POLLINATION SOI L WEED (HA) CONTROL HEALTH CONTROL Weed nets A little mulch, under trees, Mango Micro, by GF120, Natural bees, a few Compost, 01 30 trials with black Citrus gravity sulphur, natural beehives. Natural sheep and enemies habitats chicken plastic btw rows (sun bums manure weed). Mowing.

Apricots GF120, Plums sulphur, Micro and 02 Peaches 14.5 copper, Natural bees, A little mulch, Mowing 4-5 Quinces drip, by gravity bicarbonate natural habitats Compost times/year Lemons soda, natural enemies

Pipes. by 03 Apples Bait traps Natural bees, 6 Grass Mowing 3 gravity beehives cuttings times/year Exit program, Mowing Lemon Micro, Orchard 04 100 Beekeepers in the between rows, Oranges pumped and sanitation, Compost by gravity traps, natural area slashing under enemies trees

GF120, Apples Micro. by sulphur, Mulch (straw Mowing Beekeepers In the 05 Pears 30 gravity and copper, bales), between rows, area slashing under Peaches pumped compost tea, Compost tea natural enemies trees Pest specific as per need, glue Mulch (barley Spray 3 times a Apples Micro, by Rents 2,5 N1 144 bands, mating bales), year (less than Pears pump disruption, beehives/ha for 6 weeks Compost, before). No pre- Natural compost tea emergent enemies

Pest specific as Flower bush Spray program. Apples per need, bait interplant, rents 2-4 Mulch (barley No pre- C1/N2 Nectarines 300 Drip, by pump traps, glue bales), emergent Pears bands, mating beehives/ha for 2-3 weeks Compost where mulch. disruption Mowing.

Spray program. Drip and for prevention Compost, C2 Table grapes 14 micro , by and depending Self pollination artificial Spray round-up pump on weather, fertilizer once per year hormones

Natural bees, trees Peaches Spray paraquat, Apricots Spray program, with nests, sprays Artificial C3 15.5 Drip, by pump paraquat, UDO, flower stems, fertilizer roundup (to Lemon "paint" quek), Citrus other sprays sprays sugar (inteligrow) before budding MCPA. Mowing

Artif. fertilizer, Micro and Spray program Rents 10 chicken Spray under C4 Plums 37 drip, by gravity three times per beehives/ha 2-3 manure trees. Mow and pump season weeks for 1 month compost. a between rows. little mulch

41 The growers are generally open to adopt new techniques such as cover crops, but all express various factors that may be an obstacle. Some express a hesitation due to not wanting to take the risk, unless the technique is well tested and proven beneficial. Others mention that it would depend on the current ground cover and what would be required to introduce a new one, i.e. the soil type, topography, and needs for removal of the current ground cover. Nature farming and conventional growers have little concern with removal of current grasses or weeds, as they can spray and kill off grass and weeds, while organic growers express that they need to acknowledge the natural competition of the current grasses and weeds, as well as the difficulty to get access to organically certified seeds for a cover crop.

The growers express a range of challenges they face in their production (Table 6). All growers except one mention issues related to labour as one of the main challenge. Predominantly the challenge is related to skills of labour and turn-over of staff, and the social challenges to manage labourers who origin from a very different socio-economic and cultural background as themselves. The economic viability, the national economy and politics are also commonly perceived as challenges to the fruit production. Organic growers perceive pests and weeds being amongst the main challenges due to lack of products and methods available to control them, and due to the costs of the products that are available.

Table 6 The main and most uncertain challenges that the growers are facing

AREA CODE PRODUCE MAIN CHALLENGES (MOST UNCERTAIN) (HA)

01 Mango Citrus 30 Labour, Weeds, Polltlcs, Climate Apricots Plums Peaches Quinces 02 14.5 Soil health, National economy, Marketing Lemons 03 Apples Pests, Funding, Labour

04 Lemon Oranges 100 Weeds, Labour intensity, Labours' skills, Funds

05 Apples Pears Peaches 30 Funds, Knowledge

Water, Labour, Chemicals being harmful, Pests and diseases from N1 Apples Pears 144 nurseries

C1 /N2 Apples Nectarines Pears 300 Labour, Climate, Soil health

C2 Table grapes 14 Politics, Electricity costs, Labour, Climate, New varieties

Politics, National economy, Labour, Input costs, Fluctuating C3 Peaches Apricots Lemon Citrus 15.5 demand, Climate C4 Plums 37 Labour, Climate

3.9.4. Education. knowledge and needs

Most of the non-organic growers have agricultural education at college or university level, as well as growing up in a farming family. Most of the organic growers have no agricultural education and did not grow up at a farm, but chose the profession at a later stage in life. Conventional and nature farming growers are mostly part of fruit grower's associations and have consultants that provide advice. Organic growers have an informal network amongst themselves, learn mostly from trial and error and search for advice by reading online. Growers express a variety of needs to continue develop their orchards, and request support from scientists and experts to help mitigating their challenges (Table 7).

42 Table 7 Growers' perceptions of their needs for developing their orchards and what scientists and extensionists can do to support them

What knowledge is needed to continue developing your orchard?

• People, skills and social management, not production management • Better understanding on how the plant works, the physiology of the tree • Development of early maturing varieties • Knowledge on compost • How to convince people to go organic • How to adapt to the climate

What can scientists and extensionists do for you?

• Understand the environment inside the orchard, and the benefits of biodiversity • Renewing the small apple orchard, organically managed • Run trials, invite growers for field days • Publish in magazines and online forums • Develop less harmful sprays • Soil management, cover crops

3.9.5. Perceptions on organic production and barriers to conversion. There is a distinct divide in ideologies and motivations behind choosing organic or non-organic production. Table 8 presents some perceptions expressed by the growers on their choice, and their views on the uother way".

Table 8 Statements regarding drivers and opinions in growers regarding organic vs. conventional agriculture

DRIVER/MOTIVATION TO OPINION ON "THE OTHER METHOD THEIR CHOICE WAY"

nThe only way to farm" "I don't know how they can spray "I don't want to use chemicals and as much as they do" harm people and environment" "The workers have to wear heavy "I wanted to take on the protective gear and take blood challenge and proof that I could tests" do it" Organic "I don't know what they are "I'm proud to be organic" thinking. You see them in church and wonder how they can kill the "The workers shouldn't have to environment" use chemicals" "Nobody wants to take the knock "You taste the difference in the of going through the transition" fruits"

43 "They got to feel it's not the ways to do things" "They are killing the soils"

"Organic is not the way to go. "We must use chemicals, but the Organic produce has huge industry needs to make them less amounts of residues of copper harmful" Nature and sulphur' Farming "We want to spray less and do "Have tried organic but we had more nature farming but it's too much losses, and drifting costly" chemicals from the other fields"

Non- "Organic is like a religion, and organic biodynamic is even more "I'm not prepared to take the risk extreme" "You don't just switch not to spray, I will lose my job" over, you can lose everything"

Conventional "I will give my produce to anyone "I don't want to harm nature, but to eat, because I know what I'm at this stage it's not economical to doing. The residues are very low" be organic" "Everyone in an area have to be organic, or it won't work"

3.9.6. Social, economic and environmental priorities of sustainable agriculture. The motivations behind the fruit growers' choices of production approach (e.g. organic, conventional or nature farming) resonates with the growers over-all perceptions of sustainability. While all growers strive for sustainability of their production, they emphasize on different aspects of the three pillars: social, economic and environmental aspect (Figure 39).

Figure 39 The three pillars of sustainable agriculture. Conventional and nature farming growers strive to be more socially and environmentally responsible (i.e. increase working condition and salaries for staff and spray as little and as precise as possible), but hesitate to compromise economic profit. Conventional growers who have expressed a willingness to produce organic are not willing to "take the knock" in income that is expected during a conversion to organic. Organic growers on the other hand strive for economic profit but won't compromise the environment, due to their ideology and due to the regulations of organic certification. All organic growers compensate for reduced yields by value adding (i.e. drying, juicing, jamming their lower grade products), and diversify business through guest facilities. Organic producers have also expressed a greater social concern, and mention that they can keep staff employed over the entire year due to value adding and diversified

44 business. Also the health concern for staff has been raised by the organic growers as an important motivation behind organic production. 3.9.7. Climate change The overall understanding of climate change and what is causing it is limited amongst the respondents. They however experience a current change and perceive the weather to be more unreliable, more extreme events, less rain, later onset of rain and higher temperatures, and take measures to adapt to the changes (Table 9).

Table 9 Perceived climate change and coping strategies

Perceived changes Coping strategies

Less rain More effective irrigation (drip, probes) More heat Irrigate at night, build new and expand dams and Shift in rainy season, shorter rainy build bore hole season More mulch and compost More unreliable Monitoring changes in pest More extremes Harvest earlier Frequency of hail- and Diversify business thunderstorms increased Turned organic No cooling down in winter

The fruit growers participating in this study present a variety of realities, management approaches, strategies and challenges. They are a diverse group who face a variety of challenges that influence management decisions. Decisions are made with consideration to financial capacity and long-term goals. Furthermore, the growers have different prerequisites for certain produce and management practices, such as land area, location, legislations, soil and vegetation types, topography, elevation, micro climate and water availability. Their ideologies are among the dominant drivers behind their choices of farming, and they are strongly dependent on market. For successful introduction of novel management practices, scientists and extensionists need to engage with the farmers' drivers and constraints, and in some cases reluctances towards practices they have little knowledge about.

45 4. Conclusions 4.1 . Trade-offs & synergies The ,,mow and blow" mulch treatment established in October 2016 in our experimental plots did reduce the weed cover under fruit tree canopies by about 10% relative to the untreated control trees by December 2016 (Figure 408). It also reduced the amount of bare ground by 40% compared to the controls, but had no effect on the availability of soil nutrients, other major soil properties or microbial communities (Figure 40A). Our experiment was probably too short to affect soil properties significantly and repeated mow and blow applications over several seasons would be needed to indicate potential mid- and long-term effects of the treatment on soil properties. Nevertheless, along with the differences in weed and bare ground cover came differences in faunal composition. The treatment plots had higher abundances of Collembola which can act as important decomposers of organic matter, probably and effect of the higher litter availability and more favourable microclimatic conditions in our treatment plots. Treatment plots also had a higher activity of ants (Formicidae), but lower activity of spiders as beneficial predators of potential pest organisms. The average amount of beetle prey in spider webs was more than 35% higher in treated plots compared to the control (Figure 40A), eventhough more herbivorous beetles were active in control plots (Figure 408). This may be particularily relevant as the major insect induced damage on apricot fruits was caused by a chrysomeldi beetle species. Aphid and thrips prey was more commonly observed under control conditions, but the number of plant parasitic nematodes and herbivorous beetles was also higher in those plots. In summary, the tested mow and blow treatment has the potential to reduce weeds and promote selected beneficial animal groups or predation related functions. To understand these effects in greater detail and to elaborate effects on soil properties and microbial communites, longer-term studies with repeated treatment establishment are needed. A second very clear pattern also would warrant further confirmation, the two included conventionally managed orhcard plots provided only a fraction of the potentially positive properties (Figure 40A), but also had much lower values for the potentially negative properties (Figure 408). In essence, these plots were pretty bare of life compared to the organically managed plots with the exception of herbiovorus and predaceous beetles and a high ground coverage with cryptophytes.

A) POTENTIALLY POSITIVE PROPERTIES 8) POTENTIALLY NEGATIVE PROPERTIES control · r,·~-lrnPn~ r..o rive,m onal Control Tn•,1tmr•n1 conv-NH f: 4':,i;I ~r.ror::n •11e:Jd1•,c:rnt•: r1~1•,lb.P u1~,· .1c n ....,~ ,,h.. ll! :>: .. .d"J.• J.p"11:l:bup P"C't •· .,:mni:. v rn .. "

J;. S::: 11 1-c~·.h ,

r ~111 .~ 11 .ml~ : " 'I" ...... , i\· ··,

Figure 40 Relative percentage values of potentially A) positive or B) negative properties in organically managed control and mulch treatment (across all fruits) and conventionally managed apricot plots. Properties include soil properties. microbial and faunal activity, abundance and diversity metrics as well as prey groups of web-building spiders.

46 4.2. Outlook

The project closing meeting (25.-27 October 2017, Stellenbosch, South Africa) was used to discuss progress of the outstanding data analyses from the first sampling campaign and the status of the second sampling campaign. All collaborators and Pl's provided presentations on their data and results. In a second set of sessions, all partners discussed gaps and problems with ongoing analyses and discussed strategies to address any issues in the remaining project months. The following decisions on dissemination were made at the second meeting:

Scientific article topics (authors in brackets have the lead) focusing on fruit type, mulch treatment and seasonal effects on

1.) Microbes & nematodes from the Rhizosphere (WS, AM, CK) 2.) Spiders and their prey (KB, FA) 3.) Multifunctionality & -diversity (KB) 4.) Challenges for food production in the Western Cape (RM)