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Effects of grassland set-asides on selected soil properties in the Fraser River Delta of British Columbia Yates, Dru Everett 2014

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  EFFECTS OF GRASSLAND SET-ASIDES ON SELECTED SOIL PROPERTIES IN THE FRASER RIVER DELTA OF BRITISH COLUMBIA by Dru Everett Yates B.Sc., The University of British Columbia, 2010  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE  REQUIREMENTS FOR THE DEGREE OF  MASTER OF SCIENCE in The Faculty of Graduate and Postdoctoral Studies  (Soil Science)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) April, 2014   © Dru Everett Yates, 2014   ii  Abstract Grassland set-asides (GLSAs) have been used to encourage environmental stewardship on agricultural land in the Fraser River delta of British Columbia (BC) since 1994. Through this Grassland Set-aside Stewardship Program, farmers plant a mixture of grasses and legumes in place of harvestable crops for a minimum of one full year and the farmers then receive payment for establishing these short-term grasslands. Grassland set-asides are typically established on degraded fields. Although improving long-term soil quality is a key objective in the GLSA Program, evaluations of GLSA management effects on the soil have been few and limited in scope. The objectives of this study were to determine the effects of GLSA management and GLSA age on selected soil properties in agricultural fields in the Fraser River delta. Three GLSA field sites – ranging in age from two, three, and six years – were compared to three adjacent cropped potato fields for the following soil properties: total soil C and N, mechanical resistance, bulk density, aeration porosity, and aggregate stability. Relative to the Cropped treatment, the GLSA treatment did not result in an increase in total soil C or N, but did result in lower soil mechanical resistance in the upper 30 cm depth, and higher aeration porosity, and aggregate stability. The differences observed between the Cropped and GLSA treatments were most pronounced on the site with the six-year-old GLSA, indicating reduced compaction and improved soil structure as a GLSA ages. Baseline measurements of the soil prior to GLSA establishment are recommended to track changes to the soil over time and to improve the efficacy of GLSA management as a remediation strategy by pinpointing underlying soil issues that could be addressed through other corrective management (i.e. sub-soiling, liming, etc.). Soil mechanical resistance, aeration porosity, aggregate stability, pH, salinity, and mineralizable N are suggested as valuable, responsive indicators of GLSA management effects on the soil.  iii  Preface This thesis represents original, unpublished work by the author, Dru Yates. I was the lead investigator for the project described in Chapter 2 where I was responsible for all major areas of research question formation, data collection, data analysis, and thesis composition. Drs. Art Bomke, Gary Bradfield, and Sean Smukler and Ms. Christine Terpsma all contributed to thesis edits. Mr. David Bradbeer was involved in the initial formation of the research questions and objectives. Dr. Maja Kržić was the supervisory author on this project and was involved throughout the project, from research question formation through to thesis edits.             iv  Table of Contents Abstract ......................................................................................................................................................... ii Preface ......................................................................................................................................................... iii Table of Contents ......................................................................................................................................... iv List of Tables ................................................................................................................................................ vi List of Figures .............................................................................................................................................. vii List of Symbols and Abbreviations ............................................................................................................... ix Acknowledgements ....................................................................................................................................... x Chapter 1 – General Introduction ................................................................................................................. 1 1.1. Grassland Set-asides ..................................................................................................................... 1 1.1.1. History of Grassland Set-asides in the Fraser River delta ..................................................... 4 1.1.2. Soil and agriculture in the Fraser River delta ........................................................................ 7 1.2. Grassland Set-aside Effects on Soil Properties ............................................................................. 9 1.2.1. Grassland Set-aside Effects on Soil Physical Properties ........................................................ 9 1.2.2. Grassland Set-aside Effects on Soil Chemical Properties .......................................................... 15 1.3. Summary of General Introduction .............................................................................................. 19 1.4. Study Objectives and Hypotheses .................................................................................................... 21 Chapter 2 – Effects of Grassland Set-asides on Selected Soil Properties in the Fraser River delta of British Columbia ..................................................................................................................................................... 23 2.1. Introduction ..................................................................................................................................... 23 2.2. Materials and Methods .................................................................................................................... 26 2.2.1. Study Sites ................................................................................................................................. 26 2.2.2. Sampling and Laboratory Analyses ........................................................................................... 27 2.2.3. Statistical Analysis ..................................................................................................................... 32 2.3. Results .............................................................................................................................................. 32 2.3.1. Total Soil C and N Contents ....................................................................................................... 32 2.3.2. Soil Mechanical Resistance ....................................................................................................... 33 2.3.3. Soil Bulk Density and Aeration Porosity .................................................................................... 38 2.3.4. Aggregate Stability .................................................................................................................... 41 2.4. Discussion ......................................................................................................................................... 44 2.4.1. Total Soil C and N Contents ....................................................................................................... 44 2.4.2. Soil Mechanical Resistance ....................................................................................................... 48 2.4.3. Soil Bulk Density and Aeration Porosity .................................................................................... 49 2.4.3. Aggregate Stability .................................................................................................................... 52 2.5. Management Implications and Conclusions .................................................................................... 55 v  Chapter 3 – General Conclusions and Recommendations for Future Research ......................................... 57 3.1. General Conclusions ......................................................................................................................... 57 3.2. Recommendations for Future Research .......................................................................................... 60 References .................................................................................................................................................. 67 Appendix A – Additional Figures ................................................................................................................. 77 Appendix B – Additional Tables .................................................................................................................. 81 Appendix C – ANOVA Tables ....................................................................................................................... 82 Appendix D – Soil Quality Report Card ....................................................................................................... 86               vi  List of Tables  Table 1.1: Outline of the six cropping systems evaluated during a four-year rotation period in a study by Riley et al. (2008). ......................................................................................................................................  12 Table 2.1: Soil classification, texture class, and drainage characteristics of soil series present at the study sites (according to Luttmerding, 1981). .....................................................................................................  29 Table 2.2: Description of three study sites located in the Municipality of Delta, British Columbia (BC) ..  29 Table B.1: Soil chemical data for the 0-15 cm depth at each site; each analyzed sample was a composite of sixteen separate samples (four transects, with two sub-samples per transect, for two depths of sampling: 0-7.5cm and 7.5-15 cm). This soil fertility assessment was provided through Pacific Soil Analysis Inc. Richmond, BC ........................................................................................................................  81 Table C.1: ANOVA Table for completely randomized factorial experimental design with subsampling for assessment of grassland set-aside management effects on total soil C content in the Fraser River delta of BC ...............................................................................................................................................................  82 Table C.2: ANOVA Table for completely randomized factorial experimental design with subsampling for assessment of grassland set-aside management effects on total soil N content in the Fraser River delta of BC ...........................................................................................................................................................  82 Table C.3: ANOVA Table for completely randomized factorial experimental design with subsampling for assessment of grassland set-aside management effects on soil C:N ratio in the Fraser River delta  of BC ...........................................................................................................................................................  83 Table C.4: ANOVA Table for completely randomized factorial experimental design with subsampling for assessment of grassland set-aside management effects on soil bulk density in the Fraser River delta of BC. ..............................................................................................................................................................  83 Table C.5: ANOVA Table for completely randomized factorial experimental design with subsampling for assessment of grassland set-aside management effects on aeration porosity in the Fraser River delta of BC ...............................................................................................................................................................  84 Table C.6: ANOVA Table for completely randomized factorial experimental design with subsampling for assessment of grassland set-aside management effects on mean weight diameter in the Fraser River delta of BC ..................................................................................................................................................  84 Table C.7: ANOVA Table for completely randomized factorial experimental design with subsampling for assessment of grassland set-aside management effects on stable aggregates in four aggregate size classes (2-6, 1-2, 0.25-1, and <0.25 mm) in the Fraser River delta of BC. .................................................  85       vii  List of Figures Figure 2.1: Layout of the three study sites showing the pairing of two management types, grassland set-aside (GLSA) and Cropped.  The numbers beside the GLSA labels indicate the age of the grassland set-aside at the time of sampling (i.e., GLSA-6yr = six year old grassland set-aside field) ..............................  30 Figure 2.2: Total soil carbon (C) content at three soil depths in grassland set-asides (GLSAs) and cropped fields in the Fraser River delta of British Columbia. Sites are identified by the age of the grassland set-aside on each site. Error bars represent standard error of the mean (n = 4). Bars with the same letter are not significantly different following Holm-Bonferroni correction (P < 0.05). Capital letters indicate differences between the three sites in the absence of a significant interaction between management type and site...............................................................................................................................................  34 Figure 2.3: Total soil nitrogen (N) content at three soil depths in grassland set-asides (GLSAs) and cropped fields in the Fraser River delta of British Columbia. Sites are identified by the age of the grassland set-aside on each site. Error bars represent standard error of the mean (n = 4). Bars with the same letter are not significantly different following Holm-Bonferroni correction (P < 0.05) ...................  35 Figure 2.4: Soil carbon to nitrogen (C:N) ratio at three soil depths in grassland set-asides (GLSAs) and cropped fields in the Fraser River delta of British Columbia. Sites are identified by the age of the grassland set-aside on each site. Error bars represent standard error of the mean (n = 4). Bars with the same letter are not significantly different following Holm-Bonferroni correction (P < 0.05) ...................  36 Figure 2.5: Soil mechanical resistance on sampled grassland set-aside (GLSA) and cropped fields in the Fraser River delta of British Columbia. Error bars represent standard error of the mean (n = 4) and are only shown on means that are significantly different between two management treatments within each site, following Holm-Bonferroni correction (P < 0.05) ...............................................................................  37 Figure 2.6: Bulk density at three soil depths in grassland set-asides (GLSAs) and cropped fields in the Fraser River delta of British Columbia. Sites are identified by the age of the grassland set-aside on each site. Error bars represent standard error of the mean (n = 4). Bars with the same letter are not significantly different following Holm-Bonferroni correction (P < 0.05). Capital letters indicate differences between the three sites in the absence of a significant interaction between management type and site...............................................................................................................................................  39 Figure 2.7: Aeration porosity at three soil depths in grassland set-asides (GLSAs) and cropped fields in the Fraser River delta of British Columbia.  Sites are identified by the age of the grassland set-aside on each site. Error bars represent standard error of the mean (n = 4). Bars with the same letter are not significantly different following Holm-Bonferroni correction (P < 0.05). Capital letters indicate differences between the three sites in the absence of a significant interaction between management type and site...............................................................................................................................................  40 Figure 2.8: Mean weight diameter (MWD) of soil in grassland set-asides and cropped fields in the Fraser River delta of British Columbia. Sites are identified by the age of the grassland set-aside on each site. Error bars represent standard error of the mean (n = 4). Bars with the same letter are not significantly different following Holm-Bonferroni correction (P < 0.05). Capital letters indicate differences between the three sites in the absence of a significant interaction between management type and site. ............  41 Figure 2.9: Fraction of total soil sample present in four aggregate size classes (2-6, 1-2, 0.25-1, and <0.25 mm) as determined on sampled grassland set-asides (GLSAs) and cropped fields in the Fraser River delta of British Columbia. Sites are identified by the age of the grassland set-aside on each site. Error bars represent standard error of the mean (n = 4). Bars with the same letter are not significantly different following Holm-Bonferroni correction (P < 0.05). Capital letters indicate differences between the three sites in the absence of a significant interaction between management type and site .............................  43 viii  Figure A.1: Long-term monthly average precipitation for Delta, BC. Values taken from Environment Canada National Climate Data and Information Archive, Delta Ladner South. .........................................  77 Figure A.2: Map highlighting the study area and three study sites; grassland set-aside treatment is blue, cropped treatment is red (Source Map: Bing Aerial Imagery Package, ArcMap 10.1) (Esri, 2012). ..........  78 Figure A.3: Drainage ditch separating the three-year-old grassland set-aside (left) from the cropped counterpart (right). ....................................................................................................................................  79 Figure A.4: Illustration of the grassland set-aside management treatment – this is a four-year-old set-aside that was not included for assessment in this study. ........................................................................  79 Figure A.5: Illustration of the cropped management treatment – a field previously cultivated with a potato crop and left bare throughout the winter ......................................................................................  80                ix   List of Symbols and Abbreviations BC  British Columbia CRP  Conservation Reserve Program DF&WT  Delta Farmland and Wildlife Trust GLSA  grassland set-aside MAP  mean annual precipitation MWD  mean weight diameter PCP  Permanent Cover Program                x  Acknowledgements I would like to recognize the National Science and Engineering Research Council, the Delta Farmland & Wildlife Trust, Noel & Valerie Roddick, the Canadian Society of Soil Science, and the Faculty of Land and Food Systems for their financial contributions to this project.  Thank you to Shabtai Bittman and Derek Hunt for making chemical analysis possible on the LECO-analyzer. Credit goes to Dr. Tony Kozak for his consultation on statistics and Dr. Sandra Brown for helpful conversations and insights along the way. This project also would not have been possible without the farmers. Thank you Stan and Hugh Reynolds, Ken and Duncan Montgomery, Trevor Harris, Ab Singh, Brent Harris, Danny Chong, Rod Swenson, and Jack Zellweger for giving me access to your fields and for sharing your experiences with the grassland set-asides.   Many thanks to my committee members, Dr. Gary Bradfield, Dr. Sean Smukler, and Dr. Art Bomke, for their guidance in experimental design and interpretations, and for ultimately helping me to pull my findings together into useful recommendations. I am very grateful to David Bradbeer and Christine Terpsma for their commitment to the farming community in Delta. Their dedication to making the DF&WT Programs the best they can be made this collaborative, applied project possible. A huge, sincere thank you to my supervisor, Dr. Maja Kržić. She has been a true mentor to me from the outset of this project. Her efforts to encourage me to develop many skills and explore learning opportunities beyond my thesis have made this degree enriching in ways I never expected.   Last but not least, thank you to Julia Amerongen Maddison, Brittany Armstrong, Emma Holmes, Jeff Anderson, Kiara Jack, Olga Lansdorp, Alisha Hackinen, Fernando Morell, Caitlyn Munn, and Raisa Ramdeen for volunteering their time to assist me in the field and the lab.  Dru Yates April 15, 2014   1  Chapter 1 – General Introduction 1.1. Grassland Set-asides  A set-aside can be simply defined as a previously cropped agricultural field that a farmer puts to fallow, either through seeding or natural regeneration, and then receives payment for fallowing the field. A grassland set-aside (GLSA) more specifically means that the set-aside is established with grassland vegetation. This definition of a GLSA, however, is very general; set-aside management schemes are employed around the world, and the specific methods of GLSA field management and the objectives behind GLSA implementation are quite location dependent. There are some commonly shared characteristics of GLSAs, focused on a theme of minimalistic intervention. For example, a set-aside field must have living vegetative cover – vegetative cover can be established through natural regeneration or as a sown seed mix, but bare fallowed fields do not qualify (DF&WT, n.d.; Rolfe, 1993; Sotherton, 1997; Chalmers et al., 2001; Eggenschwiler et al., 2009). Chemical sprays or fertilizer applications are generally not allowed, while mowing may or may not be allowed at specified intervals (Sotherton, 1997; Chalmers et al., 2001). A parcel of land that is in set-aside for a minimum of one year is often termed a “rotational” set-aside, while a “non-rotational” or “permanent” set-aside is a field set-aside for more than one year (Anon., 1990; Bracken & Bolger, 2006).  The inclusion of payment to the farmer is essentially what differentiates GLSAs from “grass leys” or “fallowed fields”. In this thesis, studies involving grass leys and seeded, fallowed fields will be discussed alongside studies on GLSAs, as they are managed similarly from an ecological perspective.   Grassland set-asides are used in various agricultural policy and conservation programs around the world. Perhaps most notably, GLSAs were part of the Common Agricultural Policy (CAP) in the European Union (EU) from 1988 to 2008. The primary objective of these set-aside schemes was to decrease the existing 2  surplus in cereal crop production by incentivising farmers to have grasslands in place of cereal crops on their fields (Sotherton, 1998; Chalmers et al., 2001). Farmers were initially offered financial compensation for their voluntary participation, which became compulsory participation in 1992 (European Commission, n.d.). Grassland set-asides were removed from the CAP in 2008, as the surplus of cereal crops became less of an issue and the economic benefits of the GLSAs were no longer justified (European Commission, 2009).  While it was crop production regulation that initiated the policy of set-aside schemes in Europe, evidence of the value of GLSAs to habitat creation and wildlife conservation has been building. Ecological research has particularly focused on the effects of GLSAs on bird populations. Numerous studies have shown a positive relationship between GLSAs and bird abundance and/or diversity, with evidence of breeding space creation, build-up of small mammal densities, increased plant and invertebrate diversity, and overall preferred habitat on the GLSAs (Henderson et al., 2000; Firbank et al., 2003; Bracken & Bolger, 2006).  Environmental objectives have become central in existing set-aside schemes in other European countries outside of the EU, as well as in the United States and Canada. The United States Department of Agriculture implemented the Conservation Reserve Program (CRP) in 1985, primarily to address soil erosion challenges and also to reduce habitat loss (Skold, 1989; Dunn et al., 1993). Through the CRP, farmers can receive payments for keeping environmentally sensitive areas out of crop production by planting these areas with “permanent vegetative cover” for a minimum of 10 years. While the CRP is not specific to grassland cover (the program includes riparian areas, waterways, buffer strips, and windbreak trees), grassland establishment accounts for millions of hectares of CRP land (Johnson, 2005). Land-use changes from cropped fields to grasslands through the CRP have been found beneficial to many 3  grassland bird populations (Johnson, 2000; Johnson, 2005), and CRP grasslands also promote restoration of soil quality (Baer et al., 2000).  In Canada, there are three notable programs that fund farmers to convert environmentally sensitive cropland to perennial grassland vegetation – two of which are past programs, and one which is actively signing contracts.   In 1988, Agriculture & Agri-food Canada implemented the Permanent Cover Program (PCP), in which farmers in Alberta and Saskatchewan could cease cultivation of marginal prairie land and plant perennial vegetation in exchange for payment. Continuing along the theme of the United States’ CRP, the central goal was to reduce soil degradation (Vaisey et al., 1996). The PCP was extended in 1991 to include Manitoba and the Peace River region of BC; new contracts were closed in 1993 (Rolfe, 1993). Through the PCP, farmers signed contracts of either 10 or 21 years, to put prairie land under long-term grassland cover (Rolfe, 1993). Although the original intent of the PCP was to address soil quality issues, habitat protection also became part of the program. The signing of contracts to the PCP was short-lived, but the contracts were designed to have long-term impacts on the land. The PCP lands are reported to have enhanced wildlife habitat, reduced soil degradation (specifically erosion), and reduced federal payments to farmers through other agricultural compensation programs for annual crop production (e.g., Guaranteed Revenue Insurance Program, Net Income Stabilization Account, and Crop Insurance) (Vaisey et al., 1996). All contracts through the PCP have now been completed.  Between 1992 and 1994, Ontario had a similar PCP, funded through a provincial Land Management Assistance Program (NSCP, n.d.). In the Ontario PCP, farmers signed contracts of five, 10, or 15 years, promising to establish long-term vegetative cover of either grasses or trees on sensitive cropland, 4  depending on the ecosystem needs (NSCP, n.d.). Again, the program was developed in response to soil degradation concerns, and no new contracts have been signed since 1994 and all past contracts have also now been completed.  The only currently active Canadian set-aside scheme is the Grassland Set-aside Program run by the Delta Farmland and Wildlife Trust (DF&WT) in Delta, BC. It is an agri-environmental stewardship program that focuses on soil quality and habitat provision on agricultural lands. In contrast to the other Canadian programs, the contracts are only one to four years in length, allowing GLSAs to be incorporated into a field’s crop rotation more frequently, but giving the grassland vegetation less time to establish. In this GLSA Program, a set-aside is defined as a field that a farmer plants with a mixture of grasses and legumes as a type of “fallow” for a minimum of one full year; the farmer is then the farmer then receives a cost-share payment to recover a portion of the expenses for establishing the GLSA and losing the harvest of an arable crop for that year of fallow (DF&WT, n.d.). The GLSA seed mix consists of: 25% orchard grass (Dactylis glomerata), 28% tall fescue (Festuca arundinacea), 30% short fescues (Festuca rubra var. commutata and F. rubra var. rubra), 15% timothy (Phleum pratense), and 2% red clover (Trifolium pratense). Fertilization and mowing are not permitted on the set-asides; in rare cases, fertilization and mowing may be required in the first contract year to assist in successful establishment. The GLSAs are implemented in the Fraser River delta of BC to provide habitat to wildlife, increase soil organic matter, and help farmers transition to organic production (DF&WT, 2012).   1.1.1. History of Grassland Set-asides in the Fraser River delta  The GLSA Program in Delta, BC is run by the DF&WT, which is a non-profit organization that administers stewardship programs focused on the simultaneous enhancement of wildlife habitat and agricultural 5  production in Delta. The DF&WT provides cost-share funding to farmers to implement a number of different management programs that promote farmland preservation and wildlife habitat.   The GLSA Program was initiated by the DF&WT in 1994, as an attempt to re-create lost habitat following the expansion of the Vancouver International Airport (DF&WT, 2008). The two main objectives of the GLSA Program are to: (1) provide habitat to wildlife and (2) improve long-term soil quality (Merkens, 2005). Farmers receive $250 – 300 per acre put into set-aside, and are eligible to participate in the program for up to four years (with some extensions granted). The area under GLSAs ranged from 200 to 260 hectares during the period 1996 to 2013 (C. Terpsma, personal communication, 2014). Often, marginal lands with a variety of issues, such as salinity or drainage problems, are selected by farmers to be placed in the GLSA Program (Temple, 1994; DF&WT, 2002). This aligns with the findings of a 2008 survey in Denmark (Odgaard et al., 2013), where set-aside locations were strongly correlated with areas of poor growing conditions (e.g., low soil fertility, poor drainage, steep slopes). The GLSA Program encourages farmers to practice environmental stewardship in Delta, BC by offering farmers financial incentives to manage their land with long-term environmental objectives in mind, even in cases where farmers are tenants with short-term (<10 year) leases (Fraser, 2004).   After the GLSA Program had been active for a few years, it was discovered that the standard seed mix did not establish well in especially poor sites in Delta. Principe (2001) performed a study to help develop an optimal seed mix for the GLSAs, which would be able to withstand issues such as high weed pressure, high salinity, and extended soil water saturation. The author found that degraded sites suffering from particularly wet and saline conditions could benefit from a "restoration mix" composed of timothy (Phleum pretense), tall fescue (Festuca arundinacea), creeping bent grass (Agrostis stolonifera), meadow foxtail (Alopecurus pratensis), and reed canary grass (Phalaris arundinaceae) to establish vegetative 6  cover, in place of the standard DF&WT seed mix. This study led to an inclusion of more tall fescue in the DF&WT seed mix.  The first objective of the GLSA Program in Delta, BC – habitat provision – has been comprehensively evaluated over the years. The Fraser River delta is an important stopover along the Pacific Flyway for migratory birds, and in the winter the region supports some of the highest densities of migratory waterbirds and raptors in all of Canada (Norecol et al., 1994). Local studies have shown the GLSAs to be successful in habitat provision for grassland songbird species and overwintering raptor species (DF&WT, 1994; DF&WT, 2002; Merkens, 2005; DF&WT, 2012). Grassland set-asides in this region contain relatively high densities of Townsend’s vole (Microtus townsendii) populations, and are preferentially used by several species of raptor birds, including including the grassland-dependent Short-eared Owl (Asio flammeus), which is listed as a species of Special Concern under the Species at Risk Act (Summers, 1999; Merkens, 2002; Huang et al., 2010).   Local studies focused on the second objective of the GLSA Program – improvements to soil quality – have been limited. Hermawan & Bomke (1996), Principe (2001), and Armstrong (2013) have evaluated the impacts of GLSAs on various soil properties in the Fraser River delta with varying results. The GLSA improved surface aggregate stability and increased soil organic matter over a two-year period compared to a cropped treatment (Hermawan & Bomke, 1996). Similarly, greater aggregate stability under one-year-old GLSAs compared to adjacent harvested potato fields was reported by Armstrong (2013), but there were no differences in soil organic matter, bulk density, pH, soil texture, or trace elements between GLSA and potato fields. Principe (2001), on the other hand, found no difference in aggregate 7  stability in a comparison of samples taken before GLSA establishment and samples taken after one year of GLSA growth.   These three local studies of soil under GLSA management provide some much-needed information to the DF&WT and to farmers, but they were limited in scope. Hence, there are numerous unanswered questions regarding the effects of GLSA on soil quality in the Fraser River delta, including the potential influence of GLSA age on soil properties.  Grassland set-asides can be established for as many as four to six years, but only the first two years of growth have been evaluated to date. It is important for the effects of GLSA management on soil to be evaluated to determine how the GLSA Stewardship Program is meeting its objective of improving long-term soil quality. This lack of local soil studies in the Fraser River delta underlines the need for local assessment of the effects of GLSA management on multiple soil physical, chemical, and biological properties.  1.1.2. Soil and agriculture in the Fraser River delta  The Fraser River delta is located in the southwest corner of BC between Vancouver and the US Border. This region contains some of Canada’s most productive farmland (Klohn Leonoff Ltd., 1992), due to a mild maritime climate, one of the longest frost-free periods in Canada, fertile medium-textured soils, and flat topography. This region is also characterized by large amounts of winter rainfall and naturally poorly drained soils (Bertrand et al., 1991). The region has a humid maritime climate with a mean annual temperature of 9.6°C and a mean annual precipitation of 1008 mm (Environment Canada, 2013) (Fig. A.1).   8  This particular combination of climate and soil characteristics makes this prime agricultural area vulnerable to compaction and structural degradation (de Vries, 1983; Bertrand, 1991; Temple, 1994). According to a 1992 survey of farms in the Fraser River delta, one-third of farms have soil quality problems associated with poor structure and low organic matter content, with other reported soil quality problems of soil salinity and low pH (Klohn Leonoff Ltd., 1992). Leaving fields without any vegetative cover during the wettest part of the year (fall/winter) leads to degradation of surface soil structure, formation of crust, and water ponding. This in turn prolongs wet conditions, increasing susceptibility to further soil structure damage from mechanical cultivation and potentially delaying spring seeding and shortening the growing season. Insecure land tenure also generally results in reduced incentives to improve land productivity (Panayotou, 1993), and in the municipality of Delta, BC more than 50% of farmland consists of private or provincial land that is leased to farmers (StatsCan, 2011). In 1992, 44% of this rented land was on a year-to-year leasing system (Klohn Leonoff Ltd., 1992). Bomke and Temple (1990) used 30 years of soil data to show the decline of organic matter in five rented fields in the Fraser River delta. The authors concluded that under the short-term leases of these rented fields, farmers could not afford to invest in long-term management schemes that would improve the soil, and that this resulted in declining soil organic matter.  Potatoes are the main cash crop in this region, grown on approximately 22% of the agricultural land base in Delta, BC (StatsCan, 2011), and producing potatoes requires intensive cultivation practices. Potato quality is judged largely by potato size and shape; tillage is used to break apart soil aggregates and promote uniform soil structure, permitting the potatoes to grow consistently in the preferred “rounded” shape (D. Bradbeer, personal communication, 2011). Potatoes therefore typically require more soil cultivation than other annual crops in the region, which could be problematic for the physical integrity of the soil in the Fraser River delta in the long-term.  9   In general, soil degradation in this region has been attributed to bare soils over the winter, heavy farm equipment on wet soils, waterfowl traffic during winter months, insecure land tenure, and a history of low organic matter additions to the soil. For a soil conservation program to be successful, it needs to address the market pressures, wildlife habitat needs, and inherently poor drainage of the region.  1.2. Grassland Set-aside Effects on Soil Properties  Grassland set-asides are managed to encourage extensive vegetative cover and to exclude mechanical cultivation, thereby reducing disturbance to the soil structure and increasing additions of organic matter. This style of management has led land managers to believe that there is great potential for GLSAs to improve soil quality. Research has been done around the world to quantify the effects of GLSAs on physical, chemical, and biological soil properties. Although not all of these studies look holistically at soil quality on their own, looking at these studies together demonstrates an overall improvement in soil quality parameters under set-aside management. These studies also show that soil quality improvements generally become more pronounced the longer a set-aside is in place.   1.2.1. Grassland Set-aside Effects on Soil Physical Properties  One of the central reasons behind planting GLSAs, from a soil quality perspective, is to prevent the physical degradation of agricultural soils, and to improve overall soil structure. Soil structure is an important soil property to manage because it directly influences soil water movement and retention, erosion, surface crusting, susceptibility to compaction at depth, nutrient recycling, root penetration, and crop yield (Bronick and Lal, 2005). Aggregate stability – a measure of the ability of soil peds to resist destruction – is often used to quantify soil structure (Six et al., 2000). Aggregate stability has been 10  identified as a soil property that is strongly affected by management practices (Karlen and Stott, 1994; Karlen et al., 1999), and is a common component of studies evaluating soil physical properties under set-aside management.   Fullen & Booth (2006) compared aggregate stability and runoff on set-aside fields, permanent grassland fields, and bare soil plots in Shropshire, UK over a 10-year time period. The experimental plots were located in a region with a temperate climate (620 mm mean annual precipitation (MAP) on a sandy loam. Runoff measurements were higher on the bare plots relative to the set-aside and grassland fields, and consistently in excess of 1 – 2 t ha-1 a-1, which is the erosion rate considered tolerable under British standards for arable soils (Evans, 1981; Morgan, 1986). The set-asides had more runoff than the grassland fields, but runoff levels were still consistently below the tolerable erosion rate. Aggregate stability, measured using a simulated rainfall method, was significantly higher in the grassland and set-aside fields than in the bare plots, with the percentages of water-stable aggregates being 89.0% for grasslands, 80.8% for set-asides, and 60.4% for bare plots. Overall, the set-asides exhibited low erosion susceptibility and superior structure to the bare fields.  Of the three studies in the Fraser River delta that have focused on the impacts of GLSA management on soil, all have included aggregate stability. During the early establishment of the GLSA Program in Delta, BC, aggregate stability was assessed by Hermawan & Bomke (1996) comparing grass ley plots to cash cropped plots with clover as a winter cover crop. The study was located on a silty clay Humic Luvic Gleysol under a humid maritime climate (MAP 1167 mm). Aggregate stability measurements were taken when the grass leys were one and two years old. The grass ley plots had higher mean weight diameter (MWD) when compared to the cash crop with winter cover at every sampling time, indicating that grass ley management led to aggregate stability improvements after only one and two years of ley. Seasonal 11  variation in aggregate stability was also much lower in the grass ley soils. In a later study in the Fraser River delta, Armstrong (2013) also found that one-year-old GLSAs had higher aggregate stability compared to harvested potato fields. In this study, multiple fields containing different Gleysolic soil types were sampled in an attempt to capture some of the variability between GLSA sites. In contrast, Principe (2001) tracked changes in aggregate stability on a newly planted GLSA over time and did not detect an increase in aggregate stability as the GLSA aged. Samples were taken on an Orthic Gleysol before seeding the GLSA in the spring, and then again the following spring after one year of GLSA growth, with no significant differences found.  Soil bulk density – a measure of the mass of solids relative to total soil volume – is another physical property commonly used to assess GLSA impacts on soil. Bulk density provides information on compaction and aeration of the soil, both of which play important roles in root penetration and water retention/drainage. Another use for bulk density data is to convert nutrient concentration values to content (Doran and Parkin, 1996).  Riley et al. (2008) assessed aggregate stability and bulk density under GLSA management, by comparing six different cropping systems with 4-year crop rotations, including varying years of grass ley (Table 1.1). The study was done in Norway on loam under a humid continental climate (600 mm MAP). Using long-term experimental sites, these 4-year cropping systems were established from 1988 to 2003. For the samples taken in 2003 from the 0-15 cm depth, aggregate MWD was not significantly different among the cropping systems. However, the cropping system with the most grass ley in the rotation (CS6) had the highest proportion of the aggregates in the 2-6 mm size class, while the arable system with annual ploughing (CS1) had the lowest proportion of aggregates in this size class. Soil bulk density from the 0-30 cm depth was highest in 2003 under annual ploughing (CS1) at 1.43 Mg m-3, which represented a 12  significant increase from 1.29 Mg m-3 in 1988. The system with most grass leys (CS6), on the other hand, had the lowest bulk density (at 1.26 Mg m-3) in 2003. The authors concluded that rotations with 50% of grass ley would be optimal for maintaining/improving soil structure in these arable loam soils in humid continental Norway.  Table 1.1: Outline of the six cropping systems evaluated during a four-year rotation period in a study by Riley et al. (2008).   Cropping system Rotation year CS1 CS2 CS3 CS4 CS5 CS6 1 2 3 4 Wheat Oats Barley Potato Wheat Oats Barley Potato Wheat Oats/peas Barley 1st yr. Ley Wheat Barley 1st yr. ley 2nd yr. ley Wheat Barley 1st yr. ley 2nd yr. ley Barley 1st yr. ley 2nd yr. ley 3rd yr. ley Other management Autumn ploughing No till, harrowing only Spring ploughing; cattle slurry applied; organic Spring ploughing; cattle slurry applied Spring ploughing; cattle slurry applied; organic Spring ploughing; cattle slurry applied; organic  In the United States, Karlen et al. (1999) determined aggregate stability and bulk density in paired Conservation Reserve Program and cropland sites in Iowa, Minnesota, North Dakota, and Washington. The six CRP sites sampled ranged in age from 2.5 to 6 years, and soil texture and climate differed between site pairs. Conservation Reserve Program sites in Iowa had 24.6% of water stable soil aggregates, compared to 19.2% in the cropland sites. In Minnesota, the gravimetric mean aggregate diameter was significantly higher in CRP samples than cropland samples, at 2.08 mm and 0.64 mm, 13  respectively. The North Dakota sites showed no significant differences, and the Washington sites were not analyzed for aggregate stability. For bulk density, only three sites showed significant differences between the CRP and cropped treatments. Surface bulk density was significantly lower at the CRP sites in Iowa and in Minnesota; one of the Washington sites had significantly higher bulk densities in the CRP than the cropland sites. The authors attributed the inconsistency in bulk density results to differences in soil texture, CRP age, and sampling technique between paired sites. On sites with similar soil properties in Nebraska, Baer et al. (2000) also found that soil bulk density was not significantly different between newly planted and 10-year-old CRP treatments. The grassland CRP fields were on silty clay loam (730 mm MAP). The 0-year-old CRP had been seeded in the fall of 1997, and was sampled in the spring of 1998 before the seeds germinated, and so was recently managed for cash crops.  In contrast to the Conservation Reserve Program studies in the US, Pranagal et al. (2007) consistently observed significant decreases in soil bulk density over time under fallow fields in Poland. Soil bulk density was determined annually on a naturally fallowed field and two adjacent cropped fields over 10 years on a loamy sand Podzol in a temperate and transitional climatic zone in Poland (542 mm MAP). A loamy sand Podzol was left to fallow, following natural succession, for 10 years. The fallow field was initially higher in soil bulk density than the two cropped fields, but after four years of grass-dominated fallow, bulk density was lower on fallow plots (1.56 Mg m-3) compared to the cultivated fields (1.67 and 1.74 Mg m-3). The trends observed after the first 4 years were intensified as time progressed. The average bulk density for all 10 years of the fallow plots was 1.44 Mg m-3, which was significantly lower than the 1.63 and 1.61 Mg m-3 in the cultivated soils, with notable decreases in bulk density in the fallow occurring between years five and six. Corresponding with the decrease in bulk density, porosity increased significantly in the fallowed soils. Field air permeability was twice as large in the fallowed soils as in the cultivated soils. Overall, Pranagal et al. (2007) determined that the physical condition of the soil 14  had improved under the fallow compared to the conventionally cultivated fields, with more improvements becoming evident given more time under fallow management.  Mechanical resistance is another measure of soil compaction. Through its relative ease to obtain measurements, soil mechanical resistance allows researchers to better capture the spatial variability in the soil. Mechanical resistance can be used to identify particular depths of compaction, such as a compacted plow pan formed from multiple years of mechanical cultivation. High mechanical resistance values indicate high levels of compaction, with 2500 kPa commonly cited as the critical value that is limiting to root growth (Greacen et al., 1969; Busscher et al., 1986; Carter, 2002).  In an assessment of the effects of GLSA management on soil mechanical resistance in the Fraser River delta, Hermawan (1995) found that, following sub-soiling, GLSA management had reduced the mechanical resistance of a one-year-old GLSA below 30 cm relative to neighbouring cropped soils on a Humic Luvic Gleysol. However, the soils were quite wet during subsequent sampling of the two-year-old GLSA and most of the differences in mechanical resistance had disappeared, making the effects of multiple years of GLSA management on mechanical resistance unclear.   Often studies focused on the impacts of agricultural practices on soil structure also evaluate soil organic matter content, because soil organic matter is one of several important cementing agents in the formation of stable aggregates (Tisdall & Oades, 1982; Six et al. 2004; Verchot et al., 2011). Studies by Fullen & Booth (2006), Riley et al. (2008), and Hermawan & Bomke (1996) all found an increase in organic matter content under GLSA management. Fullen & Booth (2006) found that soil organic matter data closely followed the trends in the erodibility data. Soil organic matter content increased consistently over time on the set-aside plots, which corresponded with increasing aggregate stability measurements and decreasing runoff rates. Soil organic matter (expressed as percent by weight) on the 15  bare plots significantly decreased from 2.54% in 1985 to 2.04% in 1991, whereas on the plots that were converted to GLSAs soil organic matter significantly increased  from 2.43% in 1993 to 3.11% in 2001. Riley et al. (2008) observed that the annually ploughed cropping system had lower soil organic matter in the final 2003 measurement than the cropping systems with >50% of set-asides. Hermawan & Bomke (1996) determined soil organic C and aggregate stability and found a positive correlation between the two soil properties. Organic C content of the 2-6 mm aggregate size class was consistently higher under grass ley than under clover, with an overall increase from 17.25 g kg-1 to 22.70 g kg-1 after two years of grass. The clover cover following spring cash crop production did not increase soil organic C levels.  1.2.2. Grassland Set-aside Effects on Soil Chemical Properties  Soil organic matter plays an integral role in soil quality due to its effects on nutrient availability, soil water storage, and soil structure (Brady and Weil, 2007). Carbon (C) and nitrogen (N) make up a large part of soil organic matter, and are generally used to indicate soil organic matter quantity, while the carbon-to-nitrogen ratio (C:N) can be used to measure the soil organic matter quality. In the context of grassland vegetation, the extensive root system can contribute substantially to overall soil C and N contents through root decay and chemical/biological processes within the rhizosphere (Gebhart et al., 2004).   Using six sites around England with a range of soil types, Chalmers et al. (2001) compared soil mineral-N on annually ploughed fields to GLSAs with three cover types: perennial rye-grass, perennial rye-grass/white clover, and natural regeneration. Overall, the soil mineral-N concentrations of the GLSAs were generally lower or comparable to soil mineral-N concentrations of the annually ploughed fields over five years of sampling. The only exceptions were high soil mineral-N values under perennial rye-16  grass/white clover cover in the fifth year of growth. Chalmers et al. (2001) concluded that the fields under GLSA management were at a reduced risk for nitrate leaching in these six major arable regions in England.  On shorter term, rotational set-asides in England, Webster and Goulding (1995) found similar evidence for reduced nitrate losses. On sandy clay loam, the following four treatments were applied: ploughed and sown with winter wheat (harvested), ploughed and maintained bare, ploughed and sown with ryegrass (mowed), and naturally regenerated set-aside. After one year of each treatment, the values for total inorganic N leached, were 77 kg N ha-1  (bare), 52 kg N ha-1  (rye grass), 50 kg N ha-1  (winter wheat), and 19 kg N ha-1  (natural regeneration). Since ammonium levels were very low in these sandy clay loam soils, nitrate was the dominant inorganic N form.  During the year, nitrate concentrations in the collected leachate solutions from the naturally regenerated set-aside treatment were consistently lower than in the other ploughed treatments, but the difference was only occasionally significant (believed by the authors to be due to inherent high variation in the ceramic cup sampling method used). The high total inorganic-N loss from the bare field was attributed to the absence of plant N assimilation, emphasizing the value of plant cover in reducing N leaching, particularly in regions with high precipitation such as England (Webster and Goulding, 1995).  Hamer et al. (2008) evaluated soil microbial communities and nutrient cycling in a six-year-old, naturally regenerated set-aside and an intensively cultivated field on loamy sand soil in north east Saxony, Germany. They found that soil pH, organic C, total N, and gross N mineralization were all significantly higher and NO3-N content was lower in the set-aside relative to the intensive arable plots. The authors determined that intensive cultivation would result in reduced soil productivity, if the observed trends in soil chemical properties continued. They concluded that conversion to set-aside would be a reasonable 17  management alternative to conventional cultivation. The most prominent effect observed after six years of naturally regenerated set-aside was an increased potential to release N compared to the cultivated fields.  An assessment by Gebhart et al. (1994) of grassland CRP fields in the United States showed an increase in soil organic-C content after five years of established grassland vegetative cover. In this study, samples were taken from the 5-10 cm depth on fields from Texas, Nebraska, and Kansas with varied soil and climatic conditions. Gebhart et al. (1994) observed an overall increase of 21% in soil organic C on these CRP fields compared to samples from adjacent cropland.   The study by Karlen et al. (1999) carried out on six CRP fields showed that soil organic C was significantly higher on CRP fields relative to adjacent cropped field at only one of six study sites. The CRP treatments had significantly greater soil microbial C (ranging from I7 to 64% greater) relative to the cropped fields.  Greater total N was only observed in two CRP sites relative to the cropland soils. Nitrate concentrations were lower in all CRP soils, ranging from 18% to 74% lower than in the cropland soils. Karlen et al. (1999) hypothesized that this could be due to inputs of nitrate from fertilizers or manures on the croplands. No significant differences in C:N ratios were found between CRP and cropland sites in any of the six paired sites. Only one site had lower soil pH in the cropped field, possibly due to nitrification of fertilizer applied on the cropland.  Baer et al. (2000) evaluated total soil C and N on grassland CRP fields on silty clay loam in Nebraska (730 mm MAP). Comparisons were made between native grassland, long-term CRP fields (10-years-old), and short-term CRP fields (fields previously cropped, seeded in fall 1997, and sampled in spring 1998 before 18  germination). Total C and N were similar on the long-term and short-term CRP fields, while active pools of soil C and N increased on the long-term CRP fields. Soil microbial C was greater under long-term than the short-term CRP fields, with native grassland having higher soil microbial C than both CRP treatments. Carbon mineralization rates followed a similar trend, with rates of 0.14, 0.40, and 0.84 g m-2 d-1 for short-term CRP soils, long-term CRP soils, and native grassland soils, respectively. The higher C-mineralization rates in the older CRP fields compared to the recently cultivated CRP fields could be a reflection of increased microbial activity in the presence of more labile soil C. Inorganic N and nitrate availability in the long-term CRP soils were lower in the long-term than the short-term CRP soils, making the long-term CRP soils more similar to the native grassland soils in terms of inorganic N and nitrate levels.  Armstrong (2013) determined soil organic matter content on four one-year-old GLSAs and four recently harvested potato fields in the Fraser River delta. The sampled fields were all located on soils from different Gleysolic great groups. No differences in soil organic matter content were found between treatments, with high variability and a small sample size cited as possible reasons for this result.  Quantity and quality of soil organic matter was evaluated by Masciandaro et al. (1998) under native grasslands, three-year-old set-asides, and intensively cultivated plots. The study was carried out at the following two locations: (1) central-west Italy on a sandy soil with a humid Mediterranean climate (mean annual precipitation of 850 mm) and (2) central-west Spain on a silt loam soil with continental climate (500 mm MAP). In the Italian plots soil organic C was greater in set-asides (1.02%) relative to cultivated soils (0.57%); in the Spanish plots soil organic C was also greater in set-asides (0.81%) relative to cultivated soils (0.42%). In both Italy and Spain, cultivated and set-aside soils were lower in soil organic C, total N, humic C, and easily degradable organic substrates than the grassland. Soil organic matter was 19  analyzed further using pyrolysis-gas chromatography to measure organic matter “quality” through chemico-structural changes. The pyrolysis gas chromatography degrades the soil organic matter into fragments of organic matter, which are indicative of the content of stable, humified organic matter resistant to biodegradation. This analysis showed the highest index of organic matter mineralization in the native grassland and lowest index in the cultivated treatment for both the Italian and Spanish plots. This means that soil organic matter degradation was the most intense in the cultivated soil, while the set-aside showed signs of recovery on the path to the grassland state. Masciandaro et al. (1998) postulated that the large increase in soil organic matter content in the set-asides at both sampled locations was most likely related to the absence of tillage.   1.3. Summary of General Introduction  A grassland set-aside is a form of fallow management in agriculture, in which the farmer establishes grassland vegetation on an agricultural field in exchange for payment.  Overall, there has been a shift away from using GLSAs as an economic tool as the environmental benefits of GLSAs have gained recognition. The GLSA Program in the Fraser River delta provides a local example of GLSAs being used as a tool for environmental stewardship on degraded agricultural land. The main objectives of this program are to provide wildlife habitat and to improve soil quality in the Fraser River delta. Although the Fraser River delta contains some of the best agricultural land in all of Canada, the region is also susceptible to soil degradation, with market pressures and short land tenure making it difficult for farmers to manage for soil quality in the long term. The cost-share provided through the GLSA Program creates an immediate incentive for farmers to invest in the long-term environmental stewardship of the land (Fraser, 2004). GLSAs are established on some of the poorest sites in the region which exhibit signs of soil degradation, with the hope that a lack of cultivation and additions of grassland biomass under GLSA 20  management will help to remediate degraded soils by minimizing soil disturbance and maximizing the return of organic matter to the soil.  Generally, GLSAs improve soil quality relative to soils under continuous agricultural production. The GLSA management often has positive effects on soil physical properties, leading to decreased soil bulk density and mechanical resistance, and better aggregate stability. Grassland set-asides have had mixed effects on soil chemical properties, with varied results for forms of soil C and N, C:N ratio, and pH. Overall, soil organic C appeared to be consistently higher in the GLSAs compared to their cultivated field counterparts, while nitrate-N values were lower under set-aside cover than under cultivation. Additionally, this review of other studies reveals that the positive impacts of GLSA management on the soil generally increase with time. In other words, the longer a GLSA persists in a field, there is an increased likelihood that the soil will develop physical, chemical, and biological properties indicative of a healthy, productive soil.  This literature review reveals some trends in the effects of GLSAs on soil properties, but there is still a great deal of variability between set-aside schemes based on local growing conditions, soil type, and GLSA management regulations. This variability was particularly noted in the experiments involving multiple research sites, with a range of soil types and climatic conditions. This variation makes location-specific evaluation of the impacts of GLSAs on soil quality necessary in effectively assessing and managing GLSA programs around the world.   In the Fraser River delta, only a few studies focused on the effects of GLSA management on soil properties (Hermawan and Bomke, 1996; Principe, 2001; Armstrong, 2013). Soil quality is determined by a range of soil physical, chemical, and biological processes, yet only two soil properties – soil aggregate 21  stability and organic matter – have been evaluated in more than one of these past studies. My study includes multiple selected soil physical and chemical properties to provide a more comprehensive assessment of GLSA management effects. Furthermore, my study investigates the impact of GLSA age on soil properties. No previous studies have evaluated soil properties under GLSAs of different ages in this region, and this will be the first time that a GLSA older than two years will be included in a soil assessment. This information will allow for the DF&WT and participating farmers in the Fraser River delta to know if the GLSA Program is meeting its objective of improving long-term soil quality.   1.4. Study Objectives and Hypotheses  This study assesses the effects of grassland set-aside management on selected soil properties on agricultural land in the Fraser River delta, BC. The research done was informed by two key study objectives, which were created in collaboration with the DF&WT.   Objective 1: Compare the effects of grassland set-aside and cropped management in the Fraser River delta on the following selected soil properties: total soil C and N, C:N ratio, mechanical resistance bulk density, aeration porosity, and aggregate stability. Hypothesis under Objective 1: Relative to cropped management, grassland set-aside management will result in: higher total soil C and N, a higher C:N ratio, lower mechanical resistance, lower bulk density, higher aeration porosity, and higher aggregate stability.  Objective 2: Compare the age effects of grassland set-aside management in the Fraser River delta using set-asides of different ages: two, three, and six years old. 22  Hypothesis under Objective 2: The differences between GLSA and cropped management treatments will become more pronounced as the GLSA age increases, with the selected soil properties most affected by the six-year-old GLSA, followed by the three-year-old GLSA and then the two-year-old GLSA.   The long-term goal of this study is to help meet the GLSA Program objective of improving soil quality in the Fraser River delta. An evaluation of GLSA effects on the soil is important in ensuring success for Delta’s GLSA Program for two main reasons. Firstly, for the GLSA Program to have an effect on soil at a regional scale, farmers need to participate in the program and plant set-asides. While the ecological benefits to wildlife are a positive part of the GLSA Program, it is the prospect of improvements to the soil (and subsequent improvements to crop yield) that will likely be the key incentive for farmers to participate in the GLSA Program. It is the intent of the GLSA Program for farmers to be able to improve the condition of their soil for crop growth without having to take on the full costs of forfeiting their harvest(s); however, evidence is required to validate the claim that GLSA management will improve soil quality. Secondly, an evaluation of GLSA effects on the soil will provide valuable information to the DF&WT. Quantifying the impact of GLSA management on the soil and recognizing the general trends will allow the DF&WT to respond to known challenges related to soil quality under GLSA management, and to adapt and improve the GLSA Program accordingly.    23  Chapter 2 – Effects of Grassland Set-asides on Selected Soil Properties in the Fraser River delta of British Columbia1  2.1. Introduction  Agricultural programs that incentivize farmers to practice conservation exist in many forms on farmland around the world. The set-aside scheme within the Common Agricultural Policy in the European Union and the Conservation Reserve Program in the United States both stand out as large-scale programs in which farmers have been paid to substitute arable cropping with uncultivated grassland vegetation. In the Fraser River delta of British Columbia (BC), environmental stewardship on farmland has been encouraged through farmer participation in the Grassland Set-aside Program run by the Delta Farmland and Wildlife Trust (DF&WT, 2012). Through this program, a grassland set-aside (GLSA) is defined as a field that a farmer plants with a mixture of grasses and legumes as a type of “fallow” for a minimum of one full year; the farmer then receives a cost-share payment to recover a portion of the expenses for losing the harvest of an arable crop for that year of fallow (DF&WT, n.d.). The two main objectives of the GLSA Program are: (1) to provide habitat for wildlife, and (2) to improve long-term soil quality (Merkens, 2005). This study is an evaluation of the GLSA Program in the Fraser River delta in relation to the second objective.  The Fraser River delta is located in the southwest corner of BC between Vancouver and the US border. This region contains some of Canada’s most productive farmland, due to a mild maritime climate, one of the longest frost-free periods in Canada, fertile medium-textured soils, and flat topography. This region is also characterized by large amounts of winter rainfall and naturally poorly                                                           1 A version of this chapter will be submitted for publication. Authors: Yates, D., M. Krzic, D. Bradbeer, C. Terpsma, S. Smukler, and A. Bomke. Effects of grassland set-asides on selected soil properties in the Fraser River delta of British Columbia.  24  drained soils. This particular combination of climate and soil characteristics makes this prime agricultural area vulnerable to compaction and structural degradation (de Vries, 1983; Bertrand, 1991; Temple, 1994). According to a 1992 survey of farms in the Fraser River delta, one-third of farms have soil quality problems associated with poor structure and low organic matter content, with other reported soil quality problems of soil salinity and low pH (Klohn Leonoff Ltd., 1992). Soil degradation in this region has been attributed to bare soils over the winter, heavy farm equipment on wet soils, waterfowl traffic during winter months, insecure land tenure, and a history of low organic matter additions to the soil.   The Grassland Set-aside Program has been put into effect in an effort to address some of these challenges to long-term soil quality in the Fraser River delta. Typically, marginal lands with a variety of soil degradation issues, such as salinity or drainage problems, are selected by farmers to be placed in the GLSA Program (Temple, 1994; DF&WT, 2002). Fields are typically kept in the GLSA Program for two to three years. Insecure land tenure reduces the incentive for farmers to practice conservation, but issuing a cost-share payment to tenant farmers who plant GLSAs creates incentives for crop management systems that protect soil fertility in the long term (Fraser, 2004). The GLSAs are managed to encourage extensive vegetative cover and to exclude mechanical cultivation, with the intention of reducing disturbance to the soil structure and increasing additions of organic matter that are not harvested from the field.   Several studies (Karlen et al., 1999; Baer et al., 2000; Hamer et al., 2008) have shown that soil properties have improved under GLSA management relative to pre-GLSA establishment conditions or adjacent cropped areas, with effects on soil properties generally becoming more pronounced the longer a set-aside is in place (Fullen et al., 2006; Pranagal et al., 2007; Riley et al., 2008). There is still a great deal of variability among set-aside schemes based on local growing conditions, soil type, and GLSA management 25  regulations. This variation makes location-specific evaluation of the impacts of GLSAs on soil quality necessary in effectively assessing and managing GLSA programs.   Only a limited number of studies have evaluated the effects of GLSA on soil properties in the Fraser River delta. On a Humic Luvic Gleysol of Westham Island, BC, Hermawan and Bomke (1996) found greater aggregate stability and higher organic C content in the 2-6 mm aggregate size fraction under GLSA management compared to adjacent plots with a cash crop and winter cover crops. On an Orthic Gleysol in Delta, BC, Principe (2001) did not detect a difference in aggregate stability after one year of GLSA growth relative to before GLSA establishment. In the most recent local study, Armstrong (2013) compared one-year-old GLSAs to recently harvested potato fields in Delta, BC, measuring earthworm abundance, aggregate stability, soil texture, soil organic matter, pH, and trace elements. The only difference between the GLSA and comparative potato fields was higher aggregate stability under the GLSAs.  Even though one of the main objectives of the GLSA Program is to improve soil quality, very few soil properties have been measured under GLSA management. There have also been no studies evaluating the influence of GLSA age on soil properties in the Fraser River delta. The objective of this study was to evaluate the effects of GLSA management versus arable cropping management on selected soil properties (i.e., total soil C and N, mechanical resistance, soil bulk density, aeration porosity, aggregate stability) two, three, and six years after GLSA establishment.     26  2.2. Materials and Methods  2.2.1. Study Sites  This study was carried out in the Municipality of Delta, BC (49°05’N, 123°03’W) located in the Fraser River delta. The region has a humid maritime climate with a mean annual temperature of 9.6°C and mean annual precipitation of 1008 mm (Environment Canada, 2013). Approximately 52% of this precipitation falls in the winter months between November to February. The Fraser River delta is a low-lying region at an elevation of 2 m above sea level. Study sites were located on silty loam to silty clay loam Gleysols (Table 2.1), developed from surficial fluvial deltaic deposits (Luttmerding, 1981).   The three study sites were located within about 10 km of each other (Fi. A.2) and each site included the following two management types – an established grassland set-aside (GLSA) and a potato crop (referred to from now on as “Cropped”) (Fig. 2.1). All Cropped fields were harvested in fall 2011 and left bare until sampling in spring 2012. The Cropped fields did not have grassland set-asides on them for at least six years prior to establishment of this study in the spring of 2012. The exact cropping histories of the Cropped fields, prior to the 2011 potato crop, are unknown, but likely included potatoes, beans, peas, barley, and/or cole crops. Generally, conventional potato farmers in the Fraser River delta apply on average about 90 kg N ha-1, 100 kg P ha-1 and 150 kg K ha-1 in the form of chemical fertilizers at seeding time in the spring. Tillage practices on the potato fields generally included: disking once or twice, rotovating once or twice, one pass with the plow, pulvi-mulching multiple times, and rotovating again prior to seeding. The GLSAs included in this study were all part of the Grassland Set-aside Stewardship Program run by the DF&WT. All GLSAs had been established using the following seed mix provided by the DF&WT: 25% orchard grass (Dactylis glomerata), 28% tall fescue (Festuca arundinacea), 27  30% short fescues (Festuca rubra var. commutata and F. rubra var. rubra), 15% timothy (Phleum pratense), and 2% red clover (Trifolium pratense). The GLSAs did not have any fertilizer application and were not mowed following their seeding. The GLSAs included in this study were of different ages, established in the fall of the following years: 2006 (six years old at sampling), 2009 (three years old), and 2010 (two years old). Further details about each site can be found in Tables 2.1, 2.2, and B.1. Figures A.3, A.4, and A.5 in Appendix A contain sample images of the two management treatments.  2.2.2. Sampling and Laboratory Analyses  At each site, four 10-m long transects were established, within each of the two management type plots, using a stratified random method (i.e., each plot was divided into four quadrants and one transect was placed in each quadrant based on randomly generated GPS coordinates). Soil sampling and measurements were done during April and May 2012.  No sampling and measurements were done within 10 m of the edges of each plot to avoid areas where edge effects may have interfered with the experimental treatments.   All soil samples were taken at two randomly selected points along each transects. Samples for total C and N were taken from the 0-7.5, 7.5-15, and 15-30 cm depths, air-dried, ground, and sieved to ≤2 mm.  Total soil C and N were determined by dry combustion method (Nelson and Sommers, 1982) using an automated elemental analyzer (LECO CNS-2000, Leco Corp., St. Joseph, MI).  Soil mechanical resistance (Bradford, 1986) was recorded at 1.5 cm intervals down to a depth of 60 cm using a hand-pushed 13-mm-diameter 30° cone penetrometer with an attached data logger (Agridry Rimik PTY Ltd., Toowoomba, QLD, Australia). Measurements were made at six random locations along each transect.  Any organic matter present on the surface was scraped away before readings were 28  taken. Soil water content was also determined alongside mechanical resistance to correct the mechanical resistance readings to a single soil water content. This correction was done using a method outlined by Busscher and Sojka (1987), in which a logarithmic empirical relationship is applied to bulk density, gravimetric water content, and mechanical resistance. This correction makes it possible to compare absolute mechanical resistance values that are independent of the original soil water content. Corrections were adjusted to a reference water content of 0.34 kg kg-1, an average soil water content for all measurements of soil mechanical resistance.   Soil samples for aeration porosity and bulk density determination were collected using a double-cylinder drop-hammer sampler and 7.5 cm-diameter by 7.5 cm-deep cores. Soil cores were taken at the 0-7.5, 7.5-15, and 15-30 cm depths, wrapped with plastic bags and elastic bands to keep the cores intact, and stored at 4°C until analysis. Aeration porosity (i.e., soil pores having diameter > 50 m) was determined using a water tension table technique (Danielson and Sutherland, 1986). Soil cores were gradually saturated from the bottom up over 24 h in a tub of water. Cores were then weighed and placed on a tension table that was prepared with a tension medium of silicon carbide sand (grit 400). After placing cores on the table, tension was set to -6 kPa of matric potential. This tension corresponds to the air entry value for soil pores greater than 50 µm in diameter – also known as macropores. The water-filled pore-space was calculated by determining the mass per volume of water that was retained in the soil at -6 kPa relative to the total soil volume. 29  Table 2.1: Soil classification, texture class, and drainage characteristics of soil series present at the study sites (according to Luttmerding, 1981).  Soil series Subgroup Great Group Texture class Drainage Characteristics Blundell Rego Gleysol: saline and peaty phase Gleysol Silt loam Poor to very poor Crescent Orthic Gleysol Gleysol Silt loam (surface) Silty clay loam (subsurface) Moderately poor to poor Delta Orthic Humic Gleysol: saline phase Humic Gleysol Silt loam (surface) Silty clay loam (subsurface) Poor Seaview Rego Gleysol: saline phase Gleysol Silt loam  Poor to very poor Westham Rego Humic Gleysol Humic Gleysol Silt loam (surface) Silty clay loam (subsurface) Poor   Table 2.2: Description of three study sites located in the Municipality of Delta, British Columbia (BC).  Site1  Latitude and Longitude Management Type  Area (ha) Soil Series Notable field history2 I 49°10’N, 123°06’W GLSA-2yrs  15.4 (GLSA)  Crescent Westham -no record of set-aside management on the GLSA plot since 2000 Cropped 14.6 (Cropped)  Crescent Westham -no record of set-aside management on the Cropped plot since 2000 II 49°07’N, 123°14’W GLSA-3yrs  10.5 (GLSA)  Blundell Crescent -in 2000, 7.3 ha of the GLSA plot were put in set-aside for two years (2000-2001) Cropped 6.8 (Cropped) Crescent Delta -in 2004, 3.2 ha of the Cropped plot were put in set-aside for two years (2004-2005) III 49°09’N, 123°18’W  GLSA-6yrs  6.7 (GLSA)  Crescent Seaview Westham -the GLSA plot was originally 16.2 ha in 2006, but 9.5 ha were removed before sampling in 2012; the remaining 6.7 ha were left due to continued signs of poor drainage, high weed pressure, and salinity issues Cropped 21.9 (Cropped) Crescent Westham -no record of set-aside management on the Cropped plot since 2000  1Field ID used by the Delta Farmland & Wildlife Trust for the grassland set-asides: Site I = GLSA 10-02; Site II = GLSA 09-01; Site III = GLSA 06-02. 2Based on records from the Delta Farmland & Wildlife Trust since 2000.   30                            Figure 2.1: Layout of the three study sites showing the pairing of two management types, grassland set-aside (GLSA) and Cropped.  The numbers beside the GLSA labels indicate the age of the grassland set-aside at the time of sampling (i.e., GLSA-6yr = six year old grassland set-aside field).     GLSA-2yr Cropped Site I GLSA-6yr Cropped Site III GLSA-3yr Cropped Site II 31  Bulk density was determined from the same undisturbed soil cores used for aeration porosity. The soil cores were dried at 105°C for 24 h and weighed to find the oven-dry mass of soil. A correction was made for coarse fragments by sieving the samples to remove particles >2 mm in diameter. Assuming a particle density of 2.65 g cm-3 of the volume, weight of coarse fragments were calculated and subtracted from each core sample. Bulk densities of the soil samples were then calculated on a coarse fragment-free basis as the mass of oven-dry soil per volume of soil at field moisture (Blake and Hartge, 1986).  Samples for the aggregate stability assessment were collected with a hand trowel from the 0 – 7.5 cm depth. Any organic matter present on the surface was scraped away before samples were taken.  Two composite samples, each consisting of four individual subsamples, were collected along each transect. Samples were stored at 4°C until being passed through a 6-mm sieve and collected on a 2-mm sieve. Aggregate stability was measured using a variation of the wet-sieving method (Nimmo and Perkins, 2002). Immediately before wet-sieving, a pre-sieved 2-6-mm sample (of about 15 g) was placed on top of three nested sieves with openings of 2, 1, and 0.25 mm and moistened in a humidifier for 30 minutes to minimize disruption of the aggregates by the release of trapped air.  Samples were wet-sieved in a motorized apparatus for 10 minutes. The apparatus had a vertical stroke of 2.5 cm, an oscillating action through an angle of 30°, and a rate of 30 strokes per minute. After the sieves were removed from the water, the material retained on each sieve was oven-dried at 105°C for 24 hours and weighed. A correction was made to account for non-aggregate particles by crushing all material and washing the finer material through the sieve. Non-aggregate particles retained were weighed and their mass was subtracted from the total size fraction mass to determine the true mass of aggregates. The mass for each size fraction was expressed as a percentage of the total non-aggregate particle-free sample mass. Aggregate stability was expressed as the mean weight diameter (MWD) (van Bavel, 1949), which is the summation of a series of Di  Wi products (where Di is the mean diameter of each size fraction and Wi is 32  the proportion of the sample weight occurring in the corresponding size fraction).  The summation was carried out over all four size-fractions, including the one that passed the 0.25-mm sieve ().   Gravimetric water content was also determined on a field moist subsample for each aggregate stability measurement.  2.2.3. Statistical Analysis  Data were analyzed separately for each depth of sampling as a two-factorial experiment in a completely randomized design involving two management treatments (GLSA and Cropped), three sites (characterized by the age of the GLSAs – 2, 3, and 6 years old), and four pseudo-replicates (represented by four transects per management treatment). The general linear model procedure was used in the SAS package (SAS Institute Inc., 2007). The Holm-Bonferroni correction for multiple comparisons was used to evaluate significant differences between treatment means (Abdi, 2010). Significance was determined at P < 0.05.   2.3. Results  2.3.1. Total Soil C and N Contents  Management type did not alter the total C determined at the 0-7.5 cm depth at any site (Fig. 2.2a). The average total soil C was greater on Site-6yrs (1.71 kg m-2) than on Site-2yrs (1.37 kg m-2). Management appeared to influence total soil C At the 7.5-15 cm and 15-30 depths differently at the three sites (Fig. 2.2b and c). At both of these depths of sampling,  the site where GLSA was in place for 6 years had lower total soil C under GLSA relative to the Cropped treatment, while there was no difference in total C between GLSA and Cropped treatments at the sites where GLSA was in place for 2 and 3 years. At the MWD WDi ii1433  7.5-15 cm depth, total soil C content for Cropped-6yrs (1.74 kg m-2) was 44% higher than GLSA-6yrs (1.21 kg m-2) (Fig. 2b), and at the 15-30 cm depth total soil C content for Cropped-6yrs (1.79 kg m-2) was 50% higher than GLSA-6yrs (1.19 kg m-2)  (Fig. 2.2c). (See Table C.1 for ANOVA tables.)  For all three sampling depths at the site where GLSA was in place for 6 years, total soil N was lower under GLSA relative to the Cropped treatment, whereas at the sites where GLSA was in place for 2 and 3 years there was no difference in total soil N at any depth between GLSA and Cropped treatments (Fig. 2.3a, b and c). The total soil N content for Cropped-6yrs was higher than GLSA-6yrs by 26% at 0-7.5 cm (Fig. 2.3a), 46% at 7.5-15 cm (Fig. 2.3b), and 41% at 15-30 cm (Fig. 2.3c). (See Table C.2 for ANOVA tables.)  The C:N ratio did not differ at any of the three depths due to site or management treatments (Fig. 2.4). (See Table C.3 for ANOVA tables.)  2.3.2. Soil Mechanical Resistance  Grassland set-aside management reduced mechanical resistance within  the 0 -15 cm depth at all sites. At the 15-30 cm depth, the interaction between management treatment and site did have a significant effect on mechanical resistance, with GLSA-6yrs lower than its Cropped counterpart (Fig. 2.5c). At sites where grasslands were kept in place for two and three years (Fig. 2.5 a and b), soil mechanical resistance was generally similar between the two management treatments. The difference in soil mechanical resistance between the two management treatments was more pronounced on the site where GLSA was in place for six years (Fig. 2.5c); in this case, the Cropped treatment had consistently greater soil mechanical resistance than the GLSA throughout the top 30 cm depth.  There was a significant site effect at 30-40 cm, with lower mechanical resistance averages at Site 2yrs relative to the other two sites.  34     Figure 2.2: Total soil carbon (C) content at three soil depths in grassland set-asides (GLSAs) and cropped fields in the Fraser River delta of British Columbia. Sites are identified by the age of the grassland set-aside on each site. Error bars represent standard error of the mean (n = 4). Bars with the same letter are not significantly different following Holm-Bonferroni correction (P < 0.05). Capital letters indicate differences between the three sites in the absence of a significant interaction between management type and site. A AB B 00.511.522 yrs 3 yrs 6 yrsTotal Soil C (kg m-2) Site (GLSA age) a) 0-7.5 cm GLSACroppeda a b a a c 00.511.522 yrs 3 yrs 6 yrsTotal Soil C (kg m-2) Site (GLSA age) b) 7.5-15 cm a a b a a c 00.511.522 yrs 3 yrs 6 yrsTotal Soil C (kg m-2) Site (GLSA age) c) 15-30 cm 35   Figure 2.3: Total soil nitrogen (N) content at three soil depths in grassland set-asides (GLSAs) and cropped fields in the Fraser River delta of British Columbia. Sites are identified by the age of the grassland set-aside on each site. Error bars represent standard error of the mean (n = 4). Bars with the same letter are not significantly different following Holm-Bonferroni correction (P < 0.05).  a a b a a c 00.050.10.150.22 yrs 3 yrs 6 yrsTotal Soil N (kg m-2) Site (GLSA age) a) 0-7.5 cm GLSACroppeda a b a a c 00.050.10.150.22 yrs 3 yrs 6 yrsTotal Soil N (kg m-2) Site (GLSA age) b) 7.5-15 cm a a b a a c 00.050.10.150.22 yrs 3 yrs 6 yrsTotal Soil N (kg m-2) Site (GLSA age) c) 15-30 cm 36    Figure 2.4: Soil carbon to nitrogen (C:N) ratio at three soil depths in grassland set-asides (GLSAs) and cropped fields in the Fraser River delta of British Columbia. Sites are identified by the age of the grassland set-aside on each site. Error bars represent standard error of the mean (n = 4). Bars with the same letter are not significantly different following Holm-Bonferroni correction (P < 0.05).  .a a a a a a 0246810122 yrs 3 yrs 6 yrsC:N ratio Site (GLSA age) a) 0-7.5 cm GLSACroppeda a a a a a 0246810122 yrs 3 yrs 6 yrsC:N ratio Site (GLSA age) b) 7.5-15 cm a a a a a a 0246810122 yrs 3 yrs 6 yrsC:N ratio Site (GLSA age) c) 15-30 cm 37                                  Figure 2.5: Soil mechanical resistance on sampled grassland set-aside (GLSA) and cropped fields in the Fraser River delta of British Columbia. Error bars represent standard error of the mean (n = 4) and are only shown on means that are significantly different between two management treatments within each site, following Holm-Bonferroni correction (P < 0.05). a) Site 2 yrs b) Site 3 yrs c) Site 6 yrs GLSA Cropped 38  At all three sites there was an increase in mechanical resistance at 30-35 cm. No significant differences in mechanical resistance were detected below 40 cm  2.3.3. Soil Bulk Density and Aeration Porosity  Management type did not affect soil bulk density at any of the three sites (Fig. 2.6).  At all three depths of sampling, there was an overall site effect with lower average soil bulk density at Site-6yrs relative to the average bulk density on the two other sites. The bulk density averages for Site-2yrs and Site-3yrs were consistently similar to one another. (See Table C.4 for ANOVA tables.)  For aeration porosity, the influences of site and management treatments were different at all three sampled depths. At the 0-7.5 cm depth, the two management treatments displayed different effects among the three sites (Fig. 2.7a); at the site where GLSA management was in place for 6 years, aeration porosity was greater under GLSA (0.10 m3 m-3) relative to the Cropped treatment (0.04 m3 m-3). At the sites where GLSA was in place for 2 and 3 years, there were no differences in aeration porosity between GLSA and Cropped treatments. At the 7.5-15 cm depth, an overall site effect on aeration porosity was observed (Fig. 2.7b). The greatest average aeration porosity (0.09 m3 m-3) was observed on Site-6yrs, while the average aeration porosity was similar on Site-3yrs and Site-2yrs. At the 15-30 cm depth, an overall management effect on aeration porosity was observed (Fig. 2.7c). The average aeration porosity for the GLSA treatment (0.08 m3 m-3) was higher than that in the Cropped treatment (0.06 m3 m-3). (See Table C.5 for ANOVA tables.)  39   Figure 2.6: Bulk density at three soil depths in grassland set-asides (GLSAs) and cropped fields in the Fraser River delta of British Columbia. Sites are identified by the age of the grassland set-aside on each site. Error bars represent standard error of the mean (n = 4). Bars with the same letter are not significantly different following Holm-Bonferroni correction (P < 0.05). Capital letters indicate differences between the three sites in the absence of a significant interaction between management type and site. A A B 00.20.40.60.811.21.41.62 yrs 3 yrs 6 yrsBulk Density (Mg m-3) Site (GLSA age) a) 0-7.5 cm GLSACroppedA A B 00.20.40.60.811.21.41.62 yrs 3 yrs 6 yrsBulk Density (Mg m-3) Site (GLSA age) b) 7.5-15 cm A A B 00.20.40.60.811.21.41.62 yrs 3 yrs 6 yrsBulk Density (Mg m-3)  Site (GLSA age) c) 15-30 cm 40   Figure 2.7: Aeration porosity at three soil depths in grassland set-asides (GLSAs) and cropped fields in the Fraser River delta of British Columbia.  Sites are identified by the age of the grassland set-aside on each site. Error bars represent standard error of the mean (n = 4). Bars with the same letter are not significantly different following Holm-Bonferroni correction (P < 0.05). Capital letters indicate differences between the three sites in the absence of a significant interaction between management type and site. a a b a a c 00.020.040.060.080.10.122 yrs 3 yrs 6 yrsAeration Porosity (m3  m-3) Site (GLSA age) a) 0-7.5 cm GLSACroppedA A B 00.020.040.060.080.10.122 yrs 3 yrs 6 yrsAeration Porosity (m3  m-3) Site (GLSA age) b) 7.5-15 cm a a a a a a 00.020.040.060.080.10.122 yrs 3 yrs 6 yrsAeration Porosity (m3  m-3)  Site (GLSA age) c) 15-30 cm 41  2.3.4. Aggregate Stability   Management only appeared to have an effect on MWD at Site 6yrs (Fig. 2.8). At the site where GLSA was in place for 6 years, MWD was greater in the GLSA (1.59 mm) relative to the Cropped treatment (0.84 mm) by 89%. At the sites where GLSA was in place for 2 and 3 years, there was no difference in MWD between GLSA and Cropped treatments. (See Table C.6 for ANOVA tables.)     Figure 2.8: Mean weight diameter (MWD) of soil in grassland set-asides and cropped fields in the Fraser River delta of British Columbia. Sites are identified by the age of the grassland set-aside on each site. Error bars represent standard error of the mean (n = 4). Bars with the same letter are not significantly different following Holm-Bonferroni correction (P < 0.05). Capital letters indicate differences between the three sites in the absence of a significant interaction between management type and site.   The interaction between management treatment and site was also evident in the 2-6 mm aggregate fraction (Fig. 2.9a), with results similar to those for MWD. At the site where GLSA was in place for 6 years, the fraction of aggregates in the 2-6 mm size class was greater under GLSA (0.32 kg kg-1) than the a a b a a c 00.20.40.60.811.21.41.61.82 yrs 3 yrs 6 yrsMean Weight Diamater (mm)  Site (GLSA age) GLSACropped42  Cropped treatment (0.14 kg kg-1). At the sites where GLSA was in place for 2 and 3 years, there was no difference between GLSA and Cropped treatments.   There was no interaction between management treatment and site for the 1-2 mm aggregate size fraction. The lowest mean for the 1-2 mm aggregate fraction was observed on Site-3yrs (0.08 kg kg-1), with higher means on both Site-6yrs and Site-2yrs (Fig. 2.9b). GLSA management at the three sites resulted in a higher average proportion of the 1-2 mm size fraction (0.12 kg kg-1) relative to the Cropped management (0.09 kg kg-1).  There was also no interaction between management treatment and site for the 0.25-1 mm aggregate size fraction (Fig. 2.9c). Site-2yrs had the highest average proportion of this size fraction (0.09 kg kg-1), followed by Site-6yrs (0.07 kg kg-1), with the lowest average on Site-3yrs (0.05 kg kg-1). Management treatment also affected the 0.25-1 mm size fraction, with the GLSA plots having a lower average (0.07 kg kg-1) than the Cropped plots (0.08 kg kg-1).  Within the <0.25 mm aggregate size fraction, the effect of management varied among sites (Fig. 2.9d). At the site where GLSA was in place for 6 years, the fraction of aggregates was smaller under GLSA treatment (0.49 kg kg-1) than the Cropped treatment (0.69 kg kg-1). At the sites where GLSA was in place for 2 and 3 years, there was no difference between GLSA and Cropped treatments. (See Table C.7 for ANOVA tables.) 43    Figure 2.9: Fraction of total soil sample present in four aggregate size classes (2-6, 1-2, 0.25-1, and <0.25 mm) as determined on sampled grassland set-asides (GLSAs) and cropped fields in the Fraser River delta of British Columbia. Sites are identified by the age of the grassland set-aside on each site. Error bars represent standard error of the mean (n = 4). Bars with the same letter are not significantly different following Holm-Bonferroni correction (P < 0.05). Capital letters indicate differences between the three sites in the absence of a significant interaction between management type and site.a a b a a c 00.10.20.30.40.50.60.70.82 yrs 3 yrs 6 yrsFraction of total soil (kg kg-1) Site (GLSA age) a) 2-6 mm GLSACroppedA B B 00.10.20.30.40.50.60.70.82 yrs 3 yrs 6 yrsFraction of total soil (kg kg-1) Site (GLSA age) b) 1-2 mm A B C 00.10.20.30.40.50.60.70.82 yrs 3 yrs 6 yrsFraction of total soil (kg kg-1) Site (GLSA age) c) 0.25-1 mm a a b a a c 00.10.20.30.40.50.60.70.82 yrs 3 yrs 6 yrsFraction of total soil (kg kg-1) Site (GLSA age) d) <0.25 mm 44  2.4. Discussion  2.4.1. Total Soil C and N Contents  When sites were left under GLSA for two and three years there were no differences in total soil C and total N between the two management types. This was true for all three depths of sampling. Maintaining GLSAs for two or three years, as is commonly done in the Fraser River delta, did not increase soil C and N as compared to the adjacent, conventionally cropped fields. At Site-6yrs, total C and N were consistently lower under GLSA-6yrs than under the neighbouring Cropped treatment, the only exception to this being at the 0-7.5 cm depth where total soil C was not significantly different between the two management types. It is possible that the inputs of C from roots and litter under six years of GLSA management would be most pronounced in the top 7.5 cm resulting in similar total soil C in the two management treatment types.  Because there were no differences between Cropped and GLSA management on the sites containing younger GLSAs, the lower total soil C and N on GLSA-6yrs compared to its Cropped counterpart is particularly interesting. This is unexpected because the assumption is that aboveground litter and underground root biomass from the grasses on the GLSAs will cause soil organic matter to increase with time (Anderson and Coleman, 1985). This surprising result may be indicative of underlying site history effects on the soil that I did not measure directly. In the Fraser River delta, GLSAs are generally planted on degraded sites that are in need of remediation. The GLSA-6yrs plot was kept in the GLSA Stewardship Program for an unusually long time for this program, because it was severely degraded and needed improvements regarding poor drainage, weed infestation, and salinity (H. Reynolds, personal communication, 2012). Since the GLSA-6yrs plot was the most degraded of all sites included into this study, this site would likely then require the longest time to recover and to show increases in total soil C 45  and N. In addition, the GLSA-6yrs plot contains Seaview soil, which is strongly affected by excess salts and has particularly poor drainage characteristics (Luttmerding, 1981). This pre-existing salinity issue on the six-year-old GLSA could therefore also be a result of inherent Seaview soil conditions, rather than solely a result of degradation from poor past management. Elevated salinity could limit the deposition of organic matter into the soil in the years leading up to the establishment of the GLSA, as well as limit the accumulation of soil organic matter during GLSA growth. It is possible that total soil C and N at the time of GLSA establishment on the severely degraded GLSA-6yrs  plot may have been lower compared to the younger GLSAs at the other two sites. Having initial soil measurements at the time of GLSA establishment would help to further explore the effect of GLSA management and age on total soil C and N.   Differences in nutrient inputs at GLSA and Cropped plots could also be affecting the total soil C and N observed in this study. The plots with the GLSA did not receive any fertilizers or organic amendments; the source of C and N on these plots were above- and below-ground residues of the plant species included into the GLSA. The Cropped plots, on the other hand, had chemical fertilizers applied to the potato crop in the year before sampling, in addition to applications of manure and chemical fertilizers for other commercial crops that preceded potatoes. The Cropped plots also would have had some organic matter inputs from the crop residues left following the potato harvest in the fall. Potatoes leave behind some of the most biomass on the fields following harvesting compared to other annual crops common to the Fraser River delta, and this potato biomass would be deposited on the soil surface or within the potato plant’s 15-20 cm rooting depth (K. Jack, personal communication, 2014). Residual fertilizer and crop residue effects are another aspect of site history that could be elevating total soil C and N levels on the Cropped plots more than I was expecting at the outset of this study.    46  Similarly to my study, an evaluation of six grassland Conservation Reserve Program (CRP) fields from different soil types and climatic conditions in Iowa, North Dakota, Minnesota, and Washington conducted by Karlen et al. (1999) also showed that differences in site characteristics and management histories can obscure the effects of grassland set-asides on soil C and N. They compared soil organic C and total N on the CRP fields (ranging in age from 2.5 to 6.5 years) to neighbouring cropped fields. Only one site showed a significantly greater soil organic C on the CRP field compared to the adjacent cropped field. Differences in total N were only observed in two locations, with higher soil N in the CRP sites relative to the cropland soils in both cases. Overall, CRP management appeared to have some effect on soil C and N, but the variability amongst locations in this study made it difficult to reach a general conclusion about the effects of grassland CRP management on soil organic C and total N. In addition, Karlen et al. (1999) pointed out that total organic C and total N may increase too slowly to be effective indicators of soil quality changes under grassland set-asides.  They suggested that active or labile C and N fractions may be more sensitive and therefore more appropriate for detecting management impacts.   A different evaluation of grassland CRP management by Baer et al. (2000) also found that grassland vegetation did not increase total soil C and N over time. Ten- and 0-year-old grassland CRP fields on a silty clay loam in Nebraska (730 mm MAP) did not differ in total soil C and N (Baer et al., 2000). The CRP fields were planted with perennial grasses representative of dominant tallgrass prairie species (Andropogon gerardii, Andropogon scoparius, Panicum virgatum, and Sorghastrum nutans); the 0-year-old CRP had been seeded in the fall of 1997, and was sampled in the spring of 1998 before the seeds germinated. The sampled fields were put into the CRP because of concerns of soil degradation, but there are no baseline measurements to assess initial levels of degradation at the time of planting of the 10-year-old grass field.  Although Baer et al. (2000) concluded that total soil C and N were similar on the ten- and 0-year-old grassland fields, this conclusion is unclear for similar reasons to my study – without 47  knowing the initial levels of soil degradation that may have existed on the 10-year-old grass field, it is difficult to conclude whether or not the grassland CRP age had an effect on total soil C and N.    In contrast to my results, other studies have observed significantly higher soil C and/or N under GLSA management in comparison to intensively cultivated plots (Gebhart et al., 1994; Masciandaro et al., 1998; Fullen et al., 2006; Hamer et al., 2008; Riley et al., 2008). For example, a soil assessment by Gebhart et al. (1994) in the United States showed higher soil organic C content on five-year-old grassland CRP fields compared to adjacent cropland. In that study, samples were taken on fields from varied soil and climatic conditions in Texas (fine sand, 430 mm MAP), Nebraska (fine sand, 480 mm MAP), and Kansas (silt loam, 500 mm MAP).  The cropland and CRP land within each location were determined to be similar to one another with respect to cropping history prior to CRP initiation; however, CRP grassland vegetation, cropland fertilization, and commercial cropping all varied with location. In spite of these differences across locations, soil organic C levels under CRP management were overall 21% higher than under cropland at a 0-40 cm sampling depth. Gebhart et al. (1994) attribute the observed differences to elimination of tillage, reduced soil erosion, release of root exudates, root decay/turnover, and accumulation of surface litter associated with the CRP grass plants.   There were no significant differences in C:N ratio either between the two management treatments or among the three GLSA sites of differing ages.  The C:N ratios were between 8:1 and 13:1, and these values fit within the common range of cultivated surface horizons and do not exceed the decomposition-limiting ratio of 25:1 (Brady & Weil, 2007). This finding is interesting in light of some concerns expressed by farmers in the Fraser River delta who took part in GLSA Program regarding the low N availability for the subsequent crop following the incorporation of the GLSA biomass.  Total soil C and N in my study were obtained when the GLSA vegetation was still standing. To directly address 48  farmers’ concerns about potentially low N availability following GLSA biomass incorporation, the measurements of total soil C and N should be done immediately after the incorporation and also during the growing season of the commercial crop that is grown immediately after the GLSA. Large amounts of mineralizable N could accumulate under grassland growth and impact crops grown immediately after cultivation of a GLSA (Curtin and Campbell, 2006); therefore, an assessment of mineralizable N before GLSA incorporation into the soil could provide a valuable measurement of the active fraction of soil organic N under GLSA management.   2.4.2. Soil Mechanical Resistance  The Cropped treatments, which were left bare during the winter months, showed overall higher soil mechanical resistance relative to the GLSA treatments at the 0-15 cm depth. This may be a reflection of surface crusting on the Cropped plots, where the bare soil was exposed to the destructive effect of heavy rainfall and ponding during the winter, in contrast to the GLSA soils which were protected by grassland vegetation. The undisturbed roots and soil fauna in the GLSA treatments would enable the formation of aerating channels and biopores which would contribute to the reduction of compaction at this 0-15 cm depth. At the 15-30 cm depth, only the six-year-old GLSA had lower mechanical resistance than its Cropped counterpart. The six-year-old GLSA would have had more time for roots channels and biopores to penetrate into the soil than at the sites with the two- and three-year-old GLSAs. These results lend support to the hypothesis that GLSA management can reduce soil compaction, particularly over time.   All three sites showed an increase in soil mechanical resistance at about 30-35 cm depth, which is most likely an indication of a plow pan formed by years of cultivation to this depth. The plow pan area was 49  not significantly affected by GLSA management at any of the sites, possibly because the grass and clover root systems are not prolific or strong enough to have an impact at that depth. Even within the expected restrictive plow pan zone, the mechanical resistance data in this study all fall below the commonly cited critical value of 2500 kPa (Greacen et al., 1969; Busscher et al., 1986; Carter, 2002) for limiting root growth. In a study comparing the effects of cover crops and tillage treatments on a silty clay loam soil in the Fraser River delta, Krzic et al. (2000) also obtained mechanical resistance values consistently below 2500 kPa in the spring of 1995, prior to spring tillage.      2.4.3. Soil Bulk Density and Aeration Porosity  Average soil bulk density was consistently lower on Site-6yrs than on the other two sites. At the same time, average aeration porosity was greater on the Site-6yrs than on the other two sites. On sites that had GLSA for two and three years, there were no differences in either soil bulk density or aeration porosity. In the Fraser River delta, GLSAs are typically planted on degraded sites with drainage and compaction issues. The three sites included into this study were no exception. This was particularly true for GLSA-6yrs, which was strongly degraded prior to GLSA establishment and the site was kept under GLSA for the unusually long period of six years to allow it to recover. Based on the soil bulk density and aeration porosity data obtained in this study it appears that the six-year-old GLSA was showing signs of improvements to compaction and poor drainage. Aeration porosity of 0.10 m3 m-3 has been cited as a critical value for root growth (Greenwood 1975, Greenland 1981). Only GLSA-6yrs had aeration porosity above or at that critical value, while aeration porosity values under the other management-site treatments were below it.   Aeration porosity refers to pore spaces filled with air at soil water suction equivalent to 0.6 m, or in other words to the macropores. This property can provide a more detailed picture of the soil’s water 50  retention, aeration/drainage, and degree of compaction than the soil porosity (Danielson and Sutherland, 1986). Macropores strongly influence root distribution and soil air and water movement (Bouma and Dekker 1978; Dohnal et al. 2009), and their presence is particularly important for adequate aeration and drainage in fine to moderately textured soils such as the Gleysols of the lower Fraser River delta. Macroporosity was found to be responsive to changes in tillage and crop management on an Orthic Humic Gleysol in Ontario (Reynolds et al., 2007). Additionally, macroporosity developed by decayed roots and enhanced earthworm activity, as might be found in grassland set-asides, seems to be important in creating continuous, large pores that connect the soil surface with the sub-soil to enable drainage of surface water (Ehlers, 1975; Lal, 1991).  The higher aeration porosity associated with the six-year-old GLSA might be attributable to the creation of macropores by fibrous root systems and a lack of soil disturbance. Macropore and biopore destruction has been documented under conventional mouldboard plough tillage on moderate to fine textured soils (Grandy et al. 2006; Reynolds et al. 2007), and the two younger GLSA treatments and Cropped treatments have all been more recently exposed to conventional tillage than GLSA-6yrs. The aeration porosity values in my study were lower than reported by Krzic et al. (2000) on a Humic Gleysol in Delta, BC where aeration porosity values under a sweet corn crop grown on conventional and no tillage with spring barley and winter wheat cover crops were consistently above the critical value of 0.10 m3 m-3. The lower aeration porosities in my study relative to Krzic et al. (2000) could be due to pre-existing degradation and compaction on the GLSA plots, and more intensive tillage practices associated with potatoes on the Cropped plots.  A trend of decreasing bulk density with increasing number of years under set-aside vegetation was observed by Pranagal et al. (2007) on a loamy sand Podzol in a temperate and transitional climatic zone 51  in Poland (542 mm MAP). Soil bulk density was determined annually on a naturally fallowed field and two adjacent cropped fields over 10 years. The fallow field was initially higher in soil bulk density than the two cropped fields, but after four years of grass-dominated fallow, bulk density was lower on fallow plots (1.56 Mg m-3) compared to the cultivated fields (1.71 Mg m-3). This decreasing trend in bulk density on the fallow intensified as time progressed and as perennial brushwood and forest plants, such as Betula pendula and Sorbus aucuparia, overtook the herbaceous species. I did not sample each field annually to track changes over time, so it is possible that the chronosequence in my study does not capture the specific changes in soil bulk density over time under each treatment.   Contrary to these findings by Pranagal et al. (2007), Baer et al. (2000) did not observe a reduction in bulk density on older vs. younger set-aside soils. Baer et al. (2000) compared 10-year-old grassland CRP sites and 0-year-old CRP sites (seeded to grassland CRP, but sampled before seed germination) on silty clay loam in Nebraska (730 mm MAP), and found that soil bulk density was not significantly different between the two management types. Although the Nebraskan climate is drier than Delta’s, the conditions of the study by Baer et al. (2000) were similar to my study in the moderate texture of the soils tested and the consistently grass-dominated vegetation. Also, in both studies, bulk density measurements were taken at only one point in time, comparing different fields of different ages rather than comparing multiple measurements over time on one field.   Grassland set-aside management had a more pronounced effect on soil aeration porosity than bulk density. The GLSAs enhanced the presence of macropores, especially at the oldest GLSA. Therefore, given sufficient time, GLSA management could ameliorate the compaction caused by continuous cropping and cultivation on these moderately textured soils by increasing the proportion of macropores.  52  2.4.3. Aggregate Stability  Similarly to soil bulk density and aeration porosity data, the only improvements to aggregate stability were observed on the six-year-old grassland set-aside. The MWD was 89% higher under GLSA than Cropped managements at Site-6yrs, which might have been due to shorter length of time under GLSA management on the other sites. Of the three GLSAs, the oldest six-year-old GLSA had significantly higher MWD (and the largest, 2-6 mm, aggregate size class) than two younger GLSAs, indicating that two to three years of GLSA management were insufficient to increase aggregate stability as determined by MWD.  The continuous grass-dominated vegetation on GLSA-6yrs would have provided a consistent source of plant above- and belowground biomass and root exudates, all of which could contribute to the formation of large (2-6 mm) stable aggregates. Plant-derived soil organic matter, fine plant roots, and fungal hyphae are largely responsible for stabilizing macro-aggregates, while micro-aggregates are formed and stabilized through organic ligands, which are often microbially derived (Tisdall and Oades, 1982; Six et al., 2004; Verchot et al., 2011). The Cropped soils, on the other hand, were largely devoid of plant-derived organic matter inputs as they were left bare of vegetation through the winter months.  In the 1-2 mm and <0.25 mm aggregate size classes, there were some significant differences observed involving both site effects and management effects; however, the differences were very small with no clear trends, making the results for these two aggregate size classes difficult to explain. The proportion of soil in the smallest aggregate size class (<0.25 mm) showed the opposite trend compared to the largest aggregate size class, which is also not surprising. The higher proportion of these small aggregates on the Cropped fields and younger GLSAs compared to the oldest GLSA is likely due to heavy cultivation during the management of a potato cash crop leading to destruction and fragmentation of the larger stable macroaggregates into smaller stable aggregates. This link between tillage and aggregate destruction is well documented in the literature (Carter, 1992; Rasmussen, 1999; Tebrugge and During, 53  1999; Bisonette et al., 2001; Pagliai et al., 2004; Bronick and Lal, 2005; Botinelli et al., 2013). For example, Haynes and Swift (1990) found an increasing proportion of aggregates in the <0.25 mm size class as time under cropping increased compared to grass pasture on a silt loam in New Zealand. Given the connection between annual cultivation and aggregate destruction, the lower proportion of <0.25 mm aggregates on GLSA-6yrs demonstrates that over time GLSA management may be able to ameliorate damage done to soil structure by cultivation.  While significant improvements to aggregate stability under GLSA management were not observed on sites where GLSA were in place for two and three years, another study carried out on a Humic Luvic Gleysol in the Fraser River delta found aggregate stability improvements in a shorter time period. Hermawan and Bomke (1996) compared aggregate stability on grass ley plots to cash cropped plots with a clover as winter cover crop. Aggregate stability measurements were taken when the grass leys were one and two years old. The grass ley plots had higher MWD values when compared to the cash crop with winter cover at every sampling time, indicating that grass ley management led to aggregate stability improvements after only one year. In a later study in the Fraser River delta, Armstrong (2013) also found that one-year-old GLSAs had higher aggregate stability than recently harvested potato fields. In that study, multiple fields were sampled in an attempt to capture some of the variability between GLSA sites. In contrast, Principe (2001) did not detect an increase in aggregate stability on a one-year-old GLSA on an Orthic Gleysol in the Fraser River delta. Samples were taken before seeding the GLSA in the spring, and then again the following spring after one year of GLSA growth. In all three of these past assessments of aggregate stability, the leys/set-asides were seeded with the same species of plants as the GLSAs in my study. Principe (2001) started with a baseline average MWD of 3.1 mm before GLSA establishment; Hermawan and Bomke (1996), on the other hand, had a baseline average MWD of 1.1 mm, indicating poor surface soil structure before GLSA establishment, which could have made it easier 54  for the GLSAs to have a positive impact on aggregate stability. The soils in my study have MWD values similar to those of Hermawan and Bomke (1996) and Armstrong (2013). However, I do not have baseline measurements for the GLSA treatments in my study. Given that GLSAs are typically established on degraded fields, it could be that the two- and three-year-old GLSAs had lower MWD values than their Cropped counterparts upon establishment. Significant improvements to aggregate stability may have been detectable on the two younger GLSAs had they been sampled over time.  Improvements to aggregate stability under GLSA management have been demonstrated in other parts of the world (Haynes et al., 1991; Karlen et al., 1999; Fullen et al., 2006; Riley et al., 2008), with observations of higher aggregate stability under GLSA treatments compared to annually cropped or bare soil plots. Generally, the effects of GLSAs on aggregate stability are primarily attributed to the reduction of tillage disturbance and increased organic matter additions of the grassland vegetation, with some emphasis on the inputs and processes within the grass rhizosphere. For example, Haynes et al. (1991) suggest that their observations of higher aggregate stability during grazed pasture compared to arable cropping could be due to the production of binding carbohydrates by a larger microbial biomass in the pasture rhizosphere.  In my study, significant improvements to aggregate stability were achieved under GLSA management on Site-6yrs. Higher MWD for the six-year-old GLSA indicates that improvements to aggregate stability occurred under GLSA management over time by increasing the proportion of large aggregates (2-6 mm) and provide a couple reasons for this (degraded site, in the longest, protection by vegetation). In a region like the Fraser River delta, where soil crusting/pooling and compaction have been cited as critical components of soil degradation (Bertrand et al., 1991; Klohn Leonoff Ltd., 1992), enhancements to surface soil structure could contribute to improving overall soil quality and crop productivity. 55   Site history related effects and the lack of true replicates for GLSAs of different ages made it difficult to meet the research objective of assessing the age-effect of GLSA management on the soil. Although I could not fully address this objective due to limitations in the sites selected for sampling in this study, I still found evidence of GLSA management effects on the soil, particularly in the soil physical properties.  2.5. Management Implications and Conclusions   In the Fraser River delta, grassland set-asides are typically established on fields that exhibit some form of soil degradation contributing to poor crop productivity. The GLSAs are used to remediate the soil through organic matter additions and a reprieve from mechanical cultivation disturbance. My results indicate that GLSA management can benefit the soil in the Fraser River delta, with soil physical properties showing the most improvements. Lower soil mechanical resistance in the upper 30 cm depth, higher aeration porosity, and higher aggregate stability were observed under GLSA management compared to the cropped potato treatment. The GLSAs did not show an increase in total soil C or N compared to the cropped fields, nor was there a trend of increasing soil C or N with GLSA age. Significant differences between the Cropped and GLSA treatments in soil mechanical resistance, aeration porosity, and aggregate stability were only consistently evident on the site with the oldest, six-year-old GLSA. This result is noteworthy, as the majority of GLSAs in the GLSA Stewardship Program in the Fraser River delta are typically in place for less than three years. It is difficult for farmers to maintain land in the GLSA Program for longer than this due to financial pressures, and other local studies have shown soil improvements under GLSA management within only three years.    Based on the findings of my study, farmers may want to supplement the establishment of GLSAs with other management (i.e. sub-soiling, ditch pumping, liming, etc.)  to help correct underlying drainage, salinity, acidity, or fertility issues that may limit the potential for remediation under GLSA management 56  in a short period of time. Further studies are needed to determine how long the observed positive effects on mechanical resistance, aeration porosity, and aggregate stability (seen particularly after six years of GLSA management) will persist in the cropping systems of the Fraser River delta after the GLSAs are put back into cultivation. It would also be beneficial to take baseline measurements of soil properties before GLSAs are established to: (1) directly track changes to the GLSA soils over time, and (2) inform farmers of additional measures that might be needed to increase the efficacy of GLSA management as a soil remediation strategy.     57  Chapter 3 – General Conclusions and Recommendations for Future Research Grassland set-asides in the Fraser River delta are established on agricultural land to both provide wildlife habitat and improve soil quality. The effects of GLSA management on the soil are not as commonly evaluated in the Fraser River delta as the effects of GLSA management on wildlife habitat, and the few soil studies that have been done have been limited in terms of the number of soil properties included. Although grassland set-asides are currently often established on degraded fields, there is little information on how effective this GLSA management strategy is at remediating the soils. In my study, the effects of GLSA management on the soil were assessed by comparing multiple physical and chemical soil properties on three GLSAs of different ages to neighbouring cultivated potato fields. This study will help the DF&WT and farmers to make management decisions related to the GLSAs based on more complete soil data. The findings of my study will help the DF&WT to evaluate the efficacy of the GLSA Program in meeting the program objective of improving long-term soil quality in the region, and adapt the program as necessary. These findings will also help farmers to better understand what changes to expect in their soils under GLSA management.  3.1. General Conclusions  Of the soil chemical properties included in my study, total soil C and N content did show some significant differences between GLSA and Cropped treatments, but only between GLSA-6yrs and its cropped counterpart. The total soil C content for Cropped-6yrs was higher than GLSA-6yrs by 44% at 7.5-15 cm and 50% at 15-30 cm, and the total soil N content for Cropped-6yrs was higher than GLSA-6yrs by 26% at 0-7.5 cm, 46% at 7.5-15 cm, and 41% at 15-30 cm. The lower total C and N contents under GLSA management were not expected. It was expected that the inputs of soil organic matter from grass litter, decaying roots, and root exudates in the GLSAs would result in higher C and N contents compared to the bare cropped plots. It was also expected that C and N would increase with the age of the GLSAs, but the 58  opposite was observed. These surprising results were likely due to site-specific effects that I did not measure, such as exceptionally high soil degradation on the site prior to GLSA establishment and/or residual effects from past fertilization on the neighbouring Cropped treatment. It is also likely that the inherently poor drainage and high salinity of the GLSA-6yrs soils could have lowered plant productivity and reduced organic matter deposition into the soil. Unfortunately, no soil data were collected at the time of GLSA establishment and this is something that would be helpful to have to explain (or confirm) the findings of my study (see 3.2. Recommendations for Future Research).   Improvements to soil physical properties due to GLSA management were shown by significant differences between GLSA and Cropped management for soil mechanical resistance, aeration porosity, and aggregate stability. Soil bulk density did not show any significant management effects, but the GLSA age effect was significant at all three measured depths. Mechanical resistance, a generally more sensitive measure of soil compaction than bulk density, showed differences related to the two management treatments in the upper 30 cm depth, with lower mechanical resistance under GLSA management compared to Cropped management across all sites from 0-15 cm, and lower mechanical resistance under GLSA-6yrs compared to Cropped-6yrs from 15-30 cm. Aeration porosity was more than twice as high at the 0-7.5 cm depth, and at 15-30 cm was 33% higher under GLSA-6yrs compared to Cropped-6yrs. Aggregate MWD under GLSA-6yrs was higher than Cropped-6yrs by 89%. The observed changes to soil mechanical resistance, aeration porosity, and aggregate stability under GLSA management can all be considered as beneficial to agricultural soil quality. Decreased mechanical resistance, increased aeration porosity, and increased aggregate stability are all associated with improved gas diffusion, hydraulic conductivity, and resistance to compaction.   59  The pattern of results on soil mechanical resistance, aeration porosity, and aggregate stability shows greater differences between GLSA and Cropped treatments in the oldest six-year-old GLSA than in the younger two- and three-year-old GLSAs. For mechanical resistance, only GLSA-6yrs was consistently lower than its cropped counterpart from the 15-30 cm depth; for aeration porosity, only GLSA-6yrs was higher than its cropped counterpart at the 0-7.5 cm depth; and for aggregate stability, only GLSA-6yrs was higher than its cropped counterpart. However, it is difficult to attribute this trend of improved soil physical properties solely to GLSA age given that other unmeasured site effects could be causing the observed differences.  For example, the six-year-old GLSA was in the GLSA Program longer than usual because it has historically been a problematic site (H. Reynolds, personal communication, 2014). Inherent drainage and salinity issues associated with the location and Seaview soil series, which were limiting crop productivity. This is a demonstration of the site-specific differences present in my study, and these site-specific effects are a reflection of the shortcomings of using pseudoreplicates – there is a greater degree of uncertainty about observations being tied to treatment effects. Due to the lack of true replicates of GLSAs of different ages, I was not able to fully address the second objective of this study: to compare the age effects of grassland set-aside management in the Fraser River delta.  The trend of improved soil physical properties on GLSA-6yrs observed in my study also does not mean that GLSA management had no effect on the soil before six years. Mechanical resistance was reduced in the 0-15 cm layer in all three sites, indicating an effect on soil strength as early as two years after GLSA establishment. In addition, my project was not designed to quantify the exact GLSA effects since their establishment as I did not have baseline values from before the GLSAs were planted. Other local studies have found evidence of positive GLSA impacts after only one or two years of GLSA management, particularly with improvements to aggregate stability (Bomke and Hermawan, 1996; Principe, 2001; Armstrong, 2013). The trend observed in my study does not indicate that GLSAs must be in place for a 60  minimum of six years for them to be of any benefit; however, the six-year-old GLSA exhibited improved soil physical properties, despite the fact that total soil C and N were lower than in the neighbouring Cropped treatment.    The results of this study provide justification for using GLSA management to improve soil structure, aeration, and drainage. The findings of this study also indicate that certain agricultural fields may warrant more time under GLSA management than the average length of two years due to poor growing conditions inherent to the site, such as salinity, poor natural drainage, low elevation, low soil organic matter, acidity, etc.  3.2. Recommendations for Future Research  In my study, I was able to compare GLSAs to cropped fields. However, this experimental design did not allow me to directly assess the effects of GLSA management on each individual GLSA field, as I did not have baseline measurements of GLSA soil properties when they were first seeded and established. Grassland set-asides are typically planted on degraded fields, and so a comparison between this initial degraded field and the established GLSA would provide a more accurate measurement of GLSA effects on the soil than the comparison of GLSAs to productive, cropped fields that I was able to do. I was not able to directly measure the changes to the soil that may have occurred between the time of GLSA establishment and GLSA termination. In the future, it would be valuable to take baseline measurements of soil properties before the GLSAs are seeded to directly track changes to soil properties over time.   Evaluating fields before GLSA establishment can also provide valuable management information to farmers. It is generally difficult for farmers to extend their participation in the GLSA Program beyond the 61  current average of two years. A site assessment could help farmers to identify problems with drainage, compaction, salinity, fertility, etc. Farmers could supplement the establishment of a set-aside with other corrective management, which could make the GLSA more effective and reduce the amount of time to achieve the desired soil remediation effects. For example, in a study of 21 different set-aside fields Principe (2001) found that areas with drainage, salinity, and acidity issues going in to the GLSA Program had poor growth of set-aside vegetation. Vegetative growth did not improve during three years of GLSA growth, which Principe (2001) attributed to the underlying, prohibitive soil quality issues that were not addressed. In another example, Hermawan (1995) found that a one-year-old GLSA had reduced the mechanical resistance of the GLSA below 30 cm relative to neighbouring cropped soils on a Humic Luvic Gleysol, after the soils had been sub-soiled to disrupt a severely compacted plow pan and assist in drainage. Hermawan (1995) noted that without the sub-soiling it is doubtful the set-aside would have been so effective in reducing soil mechanical resistance at depth, especially within such a short period of time.      I recommend that these soil assessments prior to GLSA establishment involve a basic soil fertility analysis, which would include soil pH, electroconductivity, organic matter, N, P, K, and Na. This would provide a useful baseline of soil chemical information. Knowing the nutrient status of the field would indicate if fertilization during seeding is needed to help the GLSA to establish well.  Measurements of pH would indicate the need for liming, and electroconductivity and Na could indicate any salinity or drainage problems that could be corrected through sub-soiling, drainage tiles, or ditch-pumping. I also recommend mineralizable N – which is a measure of the active fraction of soil organic N – as a valuable indicator of soil fertility.  Mechanical resistance measurements would be an effective physical indicator of drainage issues related to crusting or compaction at depth, which might require surface tillage or sub-62  soiling. Based on my study, aeration porosity and aggregate stability are also useful indicators of GLSA impacts on soil physical quality. These two properties are more challenging to process than the other suggested soil properties, but could be assessed through student projects done in collaboration with the DF&WT. As part of this recommendation for baseline soil assessments, I am working to put together a “Soil Test Report Card” for the DF&WT (Appendix D). This report card will include a list of the recommended soil properties as well as critical values for certain properties, for easy recording and interpretation of these suggested soil properties.  It is important to note that this evaluation of soil properties while the GLSAs were still growing only describes one part of the story of how GLSA management affects the soil. The next part of the story is how GLSA management then influences the growing conditions for the crops that will be planted after incorporation of GLSA vegetation back into the soil. An evaluation of soil properties following GLSA incorporation into the soil, and then performing a crop yield evaluation, would help demonstrate this. The persistence of any improvements to soil quality into the following year(s) of cultivation is of key importance, not only to the farmers but also the long-term soil quality in the region. For example, Low (1972, 1974) determined that aggregate stability within the top 15 cm of soil can increase for periods of up to 100 years under grassland vegetation, but just one year of cultivation following that 100-year grassland period can decrease aggregate stability by approximately 40%. If all of the soil quality improvements brought about to a degraded site by six years of GLSA management are undone after one year of crop production, other soil remediation and/or conservation practices may need to be adopted to supplement the GLSAs.   The uncertainty about how GLSA management effects on the soil might carry over to influence the productivity of subsequent crops warrants further investigation. One related concern that has been 63  brought up in the past by farmers participating in the Grassland Set-aside Stewardship Program is that nitrogen availability immediately following incorporation of the GLSA vegetation into the soil is lower than expected (D. Bradbeer, personal communication, 2011). The concern is that the grassland vegetation is high in C and, upon incorporation into the soil, causes the soil C:N ratio to become high enough to limit soil N availability. An evaluation of soil quality parameters following GLSA incorporation, and continuing into the growing season, would help to address this concern. Assessing mineralizable N in particular could help indicate levels of future soil N availability.  When possible, I also recommend measuring soil properties on multiple GLSA fields, rather than just focusing on the effects of GLSA management on one field. GLSAs in the Fraser River delta appear to be quite variable in the ways they establish after seeding, and doing more to capture the spatial variability between GLSAs would help to make more accurate generalizations about the effects of GLSAs on soil in this region. One of the key shortcomings to my study was the lack of true replicates of GLSAs of different ages. In evaluating the effects of GLSA age, having replicate fields of different ages would increase the certainty that differences in soil properties between GLSAs of different ages are a result of GLSA age, and not a result of variation between other confounding site conditions.  Having regular site assessments of fields before GLSAs are planted, as previously mentioned, would also help to make the selection of multiple fields for future studies easier. It is difficult to know how long each field will remain in the GLSA Program, and having standard baseline soil assessments would make more fields available to study GLSA effects over time.   The results for total soil C and N content were unexpected, and deserving of further research. The hypothesis was that GLSA management would have higher total soil C and N than the Cropped fields, and that the C and N content (particularly the total C content) would increase with the age of the GLSAs. 64  In reality, there were largely no differences between management treatments, except for on Site-6yrs which generally showed higher soil C and N under the Cropped treatment relative to the GLSA. In addition, these differences seemed to be more related to site history than to the treatments.  In other studies of GLSAs, some differences between set-aside and cropped treatments were evident in specific fractions of soil C and N (i.e. microbial C, nitrate-N, and humified organic matter), in spite of a lack of significant differences in total soil C and N content between treatments (Karlen et al., 1994; Masciandaro et al., 1998; Baer et al., 2000). Karlen et al. (1999) determined that total organic C changed too slowly to detect changes due to management practices in the grassland Conservation Reserve Program. An analysis of different fractions of soil C and N, rather than total contents, could provide more details about the impacts of GLSAs on soil nutrients and fertility in the Fraser River delta.  A closer look at various fractions of soil organic matter would also provide information about soil aggregation under GLSA management. Principe (2001) states that the main factor of soil structure that land managers in Delta, BC can influence directly are the organic cementing agents. Hermawan and Bomke (1996) sampled organic C directly from the 2-6 mm aggregate size class and found a positive correlation between organic C and MWD. In my study, I did not measure soil organic matter in the aggregate samples to correlate with the stable aggregate data, but I found aggregate stability was highest under the oldest GLSA which did not match up with my results for soil C. I may have seen more similarities between aggregate stability and soil C if I had looked at labile forms of C instead of total C. The labile fraction of organic C, consisting largely of polysaccharides from microbial and root exudates, contributes more to aggregate stability than the humic fraction of soil C (Harris et al., 1966). Further studies to correlate different chemical properties and biological properties (i.e. polysaccharides, fungal hyphae, root biomass) with soil aggregation would provide insight into the processes behind aggregation in GLSA soils of the Fraser River delta. 65   In my study, I did not assess any biological soil properties. As GLSAs alter plant community composition relative to the adjacent arable sites, the habitat for soil organisms may also be altered. Studies on the impact of GLSAs on populations of soil organisms would provide valuable information on predicting changes to nutrient availability, agricultural pests/diseases, and trophic networks. In the literature, the response of soil organisms to GLSA management appears to be quite variable and idiosyncratic. Soil microbes can be particularly variable, with some ecosystems shown to be sensitive to differences in land management (Filser et al., 2002; Hamer et al., 2008), exhibiting microbial community differences after only two years of set-aside cover (Hedlund, 2002), while other studies have found no changes to microbial structure under GLSA management in the short-term (Maly et al., 2000; Buckley and Schmidt, 2003). Interactions between factors specific to a given study – such as soil type, conditions at sampling time, and spatial variation – make changes in microbial populations in response to management treatments hard to predict and make it necessary to conduct local soil biological assessments. Soil invertebrate assessments have shown a clearer trend than microbial assessments, with generally greater invertebrate numbers and diversity observed on GLSAs compared to bare or intensively cultivated fields (Firbank et al., 2003; Hedlund et al., 2003; Riley et al., 2008; Sadej et al., 2012). In the Fraser River delta, Armstrong (2013) found no differences in earthworm abundance and presence between one-year-old GLSAs and recently harvested potato fields. Armstrong (2013) did find that the variation of total earthworm abundance across the two treatments was best correlated with soil organic matter (positive correlation), phosphorus (negative correlation), zinc (negative correlation), and percent silt (negative correlation). High variability and a small sample size were cited as possible reasons for the lack of differences in earthworm counts, and it would be valuable to further investigate whether or not GLSAs impact earthworms in the Fraser River delta. There also appears to be an interest in the Delta farming community in the effects of GLSA management on wireworm populations (the larval form of 66  insects from the Family Elateridae) in the soil (D. Chong and T. Harris, personal communication, 2012), due to the damage that wireworms can do to subsequent crops – potatoes in particular.  Another possibility for future research is to evaluate the effects of GLSA management on Spetifore soils. The Fraser River delta contains soils of the Spetifore series, which are characterized by a unique combination of high salinity and low pH (Luttmerding, 1981). This makes Spetifore soils difficult to manage as farmland, and in my study I avoided fields with Spetifore or Spetifore-complex soils because of how different they are from the other Gleysolic soils in the area. However, there is potential for GLSAs to have a positive impact on the salinity and pH of Spetifore soils. In an effort to improve crop productivity, some farmers in the region are adding drainage structures (i.e., drainage tiles and pump-houses) and/or establishing GLSAs on fields containing Spetifore soils. Drainage improvements are meant to help to flush some of the salts out of the field, and my study indicates that GLSA management could potentially assist drainage through improvements to soil structure and aeration porosity. Additions of organic matter from the grassland vegetation could also affect the soil acidity, as soil organic matter acts as a buffer (Brady and Weil, 2007). A study that focuses on Spetifore soils (or other similarly salt-affected soils, such as the Seaview soil present on the six-year-old GLSA field in my study) exclusively could explore how GLSA management might function as a soil remediation strategy of Spetifore soils in the Fraser River delta.   67  References Abdi, H. 2010. Holm's Sequential Bonferroni Procedure. Pages 1-8 in Neil Salkind (ed.) Encyclopedia of Research Design. Sage, Thousand Oaks, CA.  Anderson, D.W. and Coleman, D.C. 1985. The dynamics of organic matter in grassland soils. Journal of  Soil and Water Conservation, 40: 211-216.  Anonymous. 1990. Set-aside. Leaflet SA1 (Rev 3). MAFF Publications, London, UK. 23 pp.  Armstrong, B. 2013. 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Plant and Soil, 177: 203–209.          77  Appendix A – Additional Figures     Figure A.1: Long-term monthly average precipitation for Delta, BC. Values taken from Environment Canada National Climate Data and Information Archive, Delta Ladner South.  020406080100120140160180Precipitation (mm) 78                                Figure A.2: Map highlighting the study area and three study sites; grassland set-aside treatment is blue, cropped treatment is red (Source Map: Bing Aerial Imagery Package, ArcMap 10.1) (Esri, 2012).  79   Figure A.3: Drainage ditch separating the three-year-old grassland set-aside (left) from the cropped counterpart (right).    Figure A.4: Illustration of the grassland set-aside management treatment – this is a four-year-old set-aside that was not included for assessment in this study.  80      Figure A.5: Illustration of the cropped management treatment – a field previously cultivated with a potato crop and left bare throughout the winter.81  Appendix B – Additional Tables  Table B.1: Soil chemical data for the 0-15 cm depth at each site; each analyzed sample was a composite of sixteen separate samples (four transects, with two sub-samples per transect, for two depths of sampling: 0-7.5cm and 7.5-15 cm). This soil fertility assessment was provided through Pacific Soil Analysis Inc. Richmond, BC.  Site Management Type pH EC (mmhos/cm) Lime req’t (tonne/ha) Total OM (%) Total N (%) C:N Avail. P (ppm) Avail. K (ppm) Avail. Ca (ppm) Avail. Mg (ppm) Avail. Na (ppm) Avail. Cu (ppm) Avail. Zn (ppm) Avail. Fe (ppm) Avail. Mn (ppm) Avail. B (ppm) I GLSA-2yrs 5.4 0.68 2.5 2.4 0.14 10.1 179 275 1700 245 25 9.5 6.9 160 31 0.5 Cropped 5.7 1.00 2.1 2.4 0.14 10.1 118 335 1600 320 26 10 6.5 250 45 0.4 II GLSA-3yrs 5.2 0.90 3.5 2.9 0.17 9.9 174 270 1650 185 22 7.5 3.6 245 18 0.4 Cropped 5.9 0.76 2.1 2.3 0.15 8.7 236 330 1950 195 20 7 5.2 200 29 0.4 III GLSA-6yrs 5.5 1.10 2.1 2.6 0.15 10.2 72 240 1600 260 42 8.5 3.2 235 35 0.3 Cropped 5.8 0.86 2.1 3.6 0.17 12.3 174 260 2350 160 60 13 3.5 110 52 0.4       82  Appendix C – ANOVA Tables Table C.1: ANOVA Table for completely randomized factorial experimental design with subsampling for assessment of grassland set-aside management effects on total soil C content in the Fraser River delta of BC.    Total soil C (0-7.5 cm) Total soil C (7.5-15 cm) Total soil C (15-30 cm) Source df F value p-value df F value p-value df F value p-value Management 1 0.07 0.794 1 2.49 0.1319 1 3.24 0.0889 Site 2 4.87 0.0204 2 1.09 0.3578 2 2 0.1644 Site X Management 2 2.11 0.1498 2 8.53 0.0025 2 5.22 0.0162 Experimental Error 18 6.48 <.0001 18 17.88 <.0001 18 6.24 <.0001 Sampling Error 23    21    24    Total 46     44     47       Table C.2: ANOVA Table for completely randomized factorial experimental design with subsampling for assessment of grassland set-aside management effects on total soil N content in the Fraser River delta of BC.    Total soil N (0-7.5 cm) Total soil N (7.5-15 cm) Total soil N (15-30 cm) Source df F value p-value df F value p-value df F value p-value Management 1 0.33 0.5703 1 3.95 0.0624 1 2.49 0.1316 Site 2 2.97 0.0769 2 2.32 0.1274 2 2.91 0.0803 Site X Management 2 4.89 0.0202 2 13.31 0.0003 2 5.65 0.0125 Experimental Error 18 3.91 0.0011 18 4.47 0.0004 18 8.85 <.0001 Sampling Error 24    24    22    Total 47     47     45          83  Table C.3: ANOVA Table for completely randomized factorial experimental design with subsampling for assessment of grassland set-aside management effects on soil C:N ratio in the Fraser River delta of BC.    C:N ratio (0-7.5 cm) C:N ratio (7.5-15 cm) C:N ratio (15-30 cm) Source df F value p-value df F value p-value df F value p-value Management 1 0.9 0.3546 1 0.08 0.7839 1 0.56 0.4657 Site 2 0.64 0.54 2 0.19 0.8307 2 0.18 0.8391 Site X Management 2 0.61 0.5519 2 0.18 0.8393 2 0.48 0.6249 Experimental Error 18 2.94 0.0074 18 2.85 0.0087 18 2.13 0.0423 Sampling Error 24    24    24    Total 47     47     47       Table C.4: ANOVA Table for completely randomized factorial experimental design with subsampling for assessment of grassland set-aside management effects on soil bulk density in the Fraser River delta of BC.    Bulk Density (0-7.5 cm) Bulk Density (7.5-15 cm) Bulk Density (15-30 cm) Source df F value p-value df F value p-value df F value p-value Management 1 2.07 0.167 1 0.41 0.5281 1 0 0.9689 Site 2 9.25 0.0017 2 8.11 0.0031 2 11.55 0.0006 Site X Management 2 0.29 0.7511 2 0.79 0.4677 2 1.13 0.3448 Experimental Error 18 2.55 0.0166 18 4.11 0.0008 18 2.62 0.0144 Sampling Error 24    24    24    Total 47     47     47            84  Table C.5: ANOVA Table for completely randomized factorial experimental design with subsampling for assessment of grassland set-aside management effects on aeration porosity in the Fraser River delta of BC.    Aeration Porosity (0-7.5 cm) Aeration Porosity (7.5-15 cm) Aeration Porosity (15-30 cm) Source df F value p-value df F value p-value df F value p-value Management 1 4.88 0.0405 1 4.1 0.058 1 6.05 0.0243 Site 2 1.74 0.204 2 5.19 0.0166 2 0.54 0.5936 Site X Management 2 10.34 0.001 2 2.03 0.1609 2 0.29 0.7528 Experimental Error 18 5 0.0003 18 1.05 0.4464 18 0.92 0.5693 Sampling Error 21    24    22    Total 44     47     45       Table C.6: ANOVA Table for completely randomized factorial experimental design with subsampling for assessment of grassland set-aside management effects on mean weight diameter in the Fraser River delta of BC.    Mean weight diameter (0-7.5 cm) Source df F value p-value Management 1 15.58 0.0009 Site 2 4.07 0.0348 Site X Management 2 6.11 0.0094 Experimental Error 18 2.11 0.0444 Sampling Error 24    Total 47        85  Table C.7: ANOVA Table for completely randomized factorial experimental design with subsampling for assessment of grassland set-aside management effects on stable aggregates in four aggregate size classes (2-6, 1-2, 0.25-1, and <0.25 mm) in the Fraser River delta of BC.    2-6 mm size fraction (0-7.5 cm) 1-2 mm size fraction (0-7.5 cm) 0.25-1  mm size fraction (0-7.5 cm) <0.25  mm size fraction (0-7.5 cm) Source df F value p-value df F value p-value df F value p-value df F value p-value Management 1 11.4 0.0034 1 12.54 0.0023 1 7.63 0.0128 1 19.83 0.0003 Site 2 3.65 0.0466 2 7.93 0.0034 2 41.67 <.0001 2 7.11 0.0053 Site X Management 2 5.82 0.0112 2 0.58 0.5723 2 2.58 0.1032 2 4.71 0.0226 Experimental Error 18 2.25 0.032 18 1.36 0.2373 18 1.7 0.1181 18 1.6 0.1412 Sampling Error 24    24    22    24    Total 47     47     45     47               86  Appendix D – Soil Quality Report Card    Soil Quality Report Card – DRAFT TEMPLATE Grassland Set-aside Stewardship Program  Field Site: Site and Sampling Sketch:          Date: (insert specific management and farmer observation questions here, possibly with check-boxes...) Farmer observations including: crop history for the past 5 years (if known), crop performance, soil behaviour (ie. ponding, crusting, wildlife use), drainage management...     Additional Site Notes:       Management Implications:   **Attach all data sheets and lab results to this page** 87  Soil Quality Report Card – DRAFT TEMPLATE CONT’D  (This section will consist of a page or two of brief descriptions of the recommended soil quality indicators, including any critical values, notes on interpretation, notes on sampling technique, etc...)  Recommended Soil Properties and Critical Values:    Basic soil fertility test (analyzed through TerraLink or Pacific Soil Analysis Ltd.)   Most important: pH, EC, total OM, total N, P, K, Na   Mechanical Resistance    Mineralizable N   Aeration Porosity   Aggregate Stability   Etc.         

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