Productivity, economic performance, and soil quality of conventional, mixed, and organic dryland farming systems in eastern Washington State

Agriculture, Ecosystems and Environment 286 (2019) 106665

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Productivity, economic performance, and soil quality of conventional, mixed, and organic dryland farming systems in eastern Washington State

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Jonathan M. Wachtera, , Kathleen M. Painterb, Lynne A. Carpenter-Boggsa, David R. Hugginsc, John P. Reganolda a

Department of Crop and Soil Sciences, Washington State University, Pullman, WA 99164, USA University of Idaho Extension, PO Box 267, Bonners Ferry, ID 83805, USA c Washington State University, USDA ARS, Land Management and Water Conservation Unit, Pullman, WA 99164, USA b

A R T I C LE I N FO

A B S T R A C T

Keywords: Crop-livestock integration Perennial Organic agriculture Soil quality Economic performance

The global trends of shortening crop rotations, simplifying cropping systems, and segregating livestock from cropping enterprises have generated high yields while creating high environmental costs. Diversification, including integrated crop/livestock systems and the use of cover, forage, and perennial crops, can be used to improve soil health, reduce financial risk, increase yields, and reduce many negative environmental externalities. With such diversification in mind, we conducted a 5-year study examining four contrasting farming systems in dryland eastern Washington State in terms of their impacts on total productivity, economic performance, and soil quality. The four systems were a conventional (CONV) winter wheat/spring wheat/spring pea rotation, typical for the area; a mixed crop-livestock (MIX) winter wheat/spring wheat/grazed winter pea forage rotation; an organic mixed crop-livestock (ORGcrop) rotation of 3 yr perennial alfalfa and grass/grazed pea forage/winter wheat; and an organic hay (ORGhay) continuous perennial alfalfa and grass system. Soft white winter wheat (SWWW) yields were higher following grazed pea forage in MIX (6.2 Mg ha−1) than following harvested pea crop in CONV (5.9 Mg ha−1) despite lower N fertilizer rates in MIX. Following 3 yr of alfalfa and grass hay and no N fertilizer, SWWW yields in ORGcrop (6.2 Mg ha−1) were similar to CONV and MIX yields but averaged 15.5% lower protein concentration. Over the 5-yr rotation, average net returns were ORGhay ($616 yr−1) > ORGcrop (216 yr−1) > MIX (−1 yr−1) = CONV (−13 yr−1), in part due to high hay prices and average grain prices during this period compared to long-term averages. Over the course of the study, total soil profile SOC showed significant negative trends in CONV (−3.1 Mg C ha−1 yr−1) and MIX (−4.1 Mg C ha−1 yr−1) but not in ORGcrop and ORGhay. In surface (0–15 cm) soil, microbial biomass carbon and nitrogen and beta-glucosidase activity were greater in ORGcrop and ORGhay than in CONV and MIX. The landscape position of this study site is of relatively poorer soil quality and results may differ across the heterogeneity of a whole farm field. Overall, ORGhay, ORGcrop, MIX, and CONV in this order produced a gradation of forage production relative to cereal production from greatest to least, and also a gradation of economic and soil sustainability metrics from greatest to least. This study found that integrating perennial crops, such as alfalfa and forage grasses, into organic farming systems can build soil quality, be profitable, and supply nitrogen to succeeding grain crops.

1. Introduction The global trends of shortening crop rotations, simplifying cropping systems, and segregating livestock from cropping enterprises have generated high yields while creating high environmental costs (Foley et al., 2011; Reganold et al., 2011). Interest in diversified, integrated, and alternative cropping systems is growing as researchers and farmers look for ways to sequester carbon, build soil quality, reduce

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environmental impacts, and diversify revenue. Cropping system diversification can be used to increase soil organic carbon (SOC) (McDaniel et al., 2014), improve soil health (Sanderson et al., 2013), reduce financial risk (Helmers et al., 2001), improve resource-use efficiency (Tilman et al., 2002), increase yields (Bennett et al., 2012), and reduce many negative environmental externalities (Davis et al., 2012). Increased crop diversity can include cash crops, cover crops, and/or forage crops. Although not harvested for sale, cover

Corresponding author. E-mail address: [email protected] (J.M. Wachter).

https://doi.org/10.1016/j.agee.2019.106665 Received 7 May 2019; Received in revised form 20 August 2019; Accepted 24 August 2019 Available online 05 September 2019 0167-8809/ © 2019 Elsevier B.V. All rights reserved.

Agriculture, Ecosystems and Environment 286 (2019) 106665

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The conventional system (CONV) uses a typical three-year crop rotation of grains with no animals and is representative of conventional practices in the area. The mixed crop-livestock system (MIX) uses a threeyear rotation that is a hybrid of organic and conventional practices, including livestock and green manures used in organic systems and lesser amounts of synthetic fertilizers and pesticides used in conventional systems. The organic hay (ORGhay) and organic mixed crop-livestock (ORGcrop) systems follow USDA National Organic Certification Standards, as certified by the Washington State Department of Agriculture Organic Program. We hypothesized that, during the 5-year study period, the diversified revenue of the MIX and ORGcrop systems would lead to greater profitability than the less diverse ORGhay and CONV systems. Second, we hypothesized that SOC, potentially mineralizable N, microbial biomass, and enzyme activities would be highest in the ORGhay and ORGcrop systems, followed by MIX, and finally the CONV system.

crops can increase yield potential of following crops while decreasing required N inputs (Franzluebbers, 2007), reducing erosion, and improving soil quality (Drinkwater and Snapp, 2007; Entz et al., 2002). Despite these well-documented benefits, cover crops are often forgone in favor of growing a crop with economic returns, especially in regions where moisture and/or temperatures limit productivity (Thiessen Martens et al., 2015). Grazing a cover crop as a forage crop is one method of earning revenue while also incurring many of the benefits of an ungrazed cover crop (Martens and Entz, 2011; Russelle et al., 2007; Sanderson et al., 2013). Integrating livestock into crop production, commonly called mixed or integrated crop/livestock systems, has the potential to enhance productivity and land-use efficiency (Franzluebbers, 2007), increase farm profitability and diversify income (Allen et al., 2007), improve soil nutrient retention (Acosta-Martínez et al., 2004), manage certain pests and weeds (Hatfield et al., 2007b, 2007a), and encourage perennial forage and cover crops with consequent improvements in soil quality and reduced fertilizer inputs (Bell et al., 2012; Martens and Entz, 2011). Despite higher labor requirements, integrating grazed forage crops into grain cropping systems can produce greater economic returns over operating costs by reducing inputs and producing an alternative revenue source (Sulc and Tracy, 2007). The inclusion of forages in crop rotations has been found to reduce weed pressure (Entz et al., 2002), and increase yields (Entz et al., 2002; Maughan et al., 2009), microbial biomass and enzyme activities (Acosta-Martínez et al., 2010), SOC (Acosta-Martínez et al., 2010; Entz et al., 2002; Maughan et al., 2009), and soil aggregation (Entz et al., 2002; Maughan et al., 2009). In particular, perennial crops and forages in rotation are increasingly recognized as an important strategy for increasing SOC (King and Blesh, 2017). Studies on pasture-crop rotations have shown that SOC increases during the pasture phase (Bell et al., 2012; Römkens et al., 1999), but upon conversion to the cropping phase SOC often begins to decline (Franzluebbers and Stuedemann, 2008; Gentile et al., 2005). A review of SOC in the inland Pacific Northwest found that mixed perennial-annual cropping systems increased mean soil profile organic C stocks by 1.03 ± 0.41 Mg C ha−1 compared to annual cropping systems (Brown and Huggins, 2012). Often relying on both diverse crop rotations and livestock integration, organic systems are gaining in popularity as a way of capturing market premiums and providing environmental benefits (Reganold and Wachter, 2016). Despite lower yields, organic systems are associated with greater SOC, increased soil biological activity, and greater profitability (Fließbach et al., 2007; Gattinger et al., 2012; Gomiero et al., 2011; Mäder et al., 2002; Reganold and Wachter, 2016). The current study examines the potential for these practices in dryland eastern Washington State, one of the most productive wheatgrowing regions in the world (Duffin, 2007; Hall et al., 1999), and a region with a dearth of integrated and organic farms (Borrelli et al., 2010; Hardesty and Tiedeman, 1996; Kirby and Granatstein, 2018). For much of the past century, erosion rates averaged 22–67 Mg ha−1 (Schillinger et al., 2010). Erosion and loss of soil organic carbon due to tillage and steep topography (McCool et al., 2001), soil acidification from use of ammoniacal fertilizers (Brown et al., 2008), and economic viability and lack of diversification due to dependence on few commodity crops (Kirby et al., 2017) are among the top concerns in this region. For any farm to be sustainable, it must produce adequate amounts of high-quality food, feed, or fiber, enhance the natural resource base and environment, be financially viable, and contribute to the well-being of farmers and their communities (Reganold and Wachter, 2016). In April 2012, we initiated a long-term farming systems sustainability assessment experiment on a 2-ha parcel of a commercial grain farm in the Palouse Region of eastern Washington State. Here we report on the first five years (2012–2016) of this long-term study, in which we examined the performance of four contrasting farming systems in terms of their impacts on total productivity, economic performance, and soil quality.

2. Methods 2.1. Site description and experimental design In April 2012, we established research plots on an 80-year old commercial grain farm in the Palouse River Basin of eastern Washington State (46.9 °N; 117.1 °W; 802 m altitude). Four treatments were laid out in a randomized complete block design, with four replicate plots for each of the four farming system treatments (Fig. 1). Prior to establishing our plots, the L-shaped west- and south-facing 2-ha parcel was in a conventional tillage, two- to three-year cereal crop rotation for the previous 30 years. Pre-trial field examinations were done to ensure that all soil-forming factors were the same within each of the four treatment blocks (Reganold, 2013); thus, the plots within each block in 2012 started out with similar soil profiles and properties. The soil type on Blocks 1, 2, and 3 is a Palouse silt loam (Fine-silty, mixed, superactive, mesic Pachic Ultic Haploxerolls) and on Block 4 a Thatuna silt loam (Fine-silty, mixed, superactive, mesic Oxyaquic Argixerolls). Due to the heterogeneity of topography and soil types in the Palouse region (an area of native grassland soils of generally high quality), a typical farm field in this area would be made up of numerous soil types of varying soil quality, with the landscape position of this study site being of relatively poorer soil quality. Treatments consisted of four dryland crop rotations: a conventionally managed 3-year rotation of spring pea (Pisum sativum var. Columbia)-winter wheat (Triticum aestivum var. Madsen)-spring wheat (CONV); an integrated rotation of grazed Austrian winter pea (Pisum sativum var. Granger)-winter wheat-spring wheat (MIX); an organically managed mixed pasture consisting of alfalfa (Medicago sativa var. Ladak), smooth brome (Bromus inermis), and orchardgrass (Dactylis glomerata), from which one cutting of hay was taken each June followed by a grazing in late summer (ORGhay); and an organically managed crop rotation that was transitioned into organic certification under mixed pasture for the first 3 years, followed by grazed spring pea (Pisum sativum var. Columbia)-winter wheat (Triticum aestivum var. Madsen) (ORGcrop). During green manure years and on late-summer hay regrowth, MIX, ORGcrop, and ORGhay were grazed with white Dorper sheep at a rate of 100–150 ewes day−1 ha−1 (Table 1). No grazing occurred on ORGhay and ORGcrop in 2013 and on ORGhay in 2015 due to poor pasture regrowth from low soil moisture. Mean annual rainfall and mean maximum/minimum temperatures during the 5-year study period from 2012 to 2016 were 535 mm and 15.8 °C/3.3 °C, respectively (Fig. 2). 2.2. Total productivity Prior to grain, hay, or forage harvest, total aboveground biomass was collected using six 1-m2 quadrats per plot. Materials were dried with forced air at 60 °C and weighed. Cut hay and grazing forage were 2

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Fig. 1. Layout of study plots. Four treatments were laid out in a randomized complete block design on a 2-ha parcel, with four replicate plots for each of the four farming system treatments: CONV, MIX, ORGcrop, and ORGhay. Eight plots (CONV and MIX) measure 46 × 16 m and 8 plots (ORGcrop and ORGhay) measure 46 × 8 m. White borders denote 7.5-m buffers between organically managed and non-organically managed land to comply with organic certification requirements.

infrared transmission (FOSS 1241 Grain Analyzer, Eden Prairie, MN). Grain, residue, hay, and forage samples were analyzed for total C and N using dry combustion elemental analysis (Costech Elemental Combustion System 4010, Valencia, CA). Hay and forage were analyzed for neutral detergent fiber (NDF) and acid detergent fiber (ADF) (ANKOM 200 Fiber Analyzer, Macedon, NY) (Vogel et al., 1999) and relative feed value (RFV) was calculated as follows (Jeranyama and Garcia, 2004):

resampled following haying/grazing and the difference in mass (preharvest total biomass minus post-harvest remaining biomass) was considered to be the quantity harvested or grazed. Grain crops were threshed to determine yields and harvest index. Grain residue (straw and chaff) were combined. Materials were ground using a Wiley mill (1 mm screen size; Thomas Scientific Model 4 Wiley R Mill, Swedesboro, NJ) and subsampled for analysis. Harvested spring and winter wheat grains were analyzed for protein concentration using near

Table 1 Crop rotations, fertilizer use, and tillage practices during the 5-yr study of the four treatments: CONV, MIX, ORGcrop, and ORGhay. CONV

MIX

ORGcrop

ORGhay

crop harvest fertilizer (kg ha−1) pesticide/herbicide tillage

spring pea crop – yes chisel

spring pea graze – yes chisel

alfalfa + grass none – yes chisel

alfalfa + grass none – yes chisel

crop harvest fertilizer (kg ha−1) pesticide/herbicide tillage

winter wheat crop 100 N/17 P/17 S yes –

winter wheat crop 90 N/17 P/17 S yes –

alfalfa + grass hay – no –

alfalfa + grass hay – no –

crop harvest fertilizer (kg ha−1) pesticide/herbicide tillage

spring wheat crop 90 N/11 P/17 S yes chisel & harrow

spring wheat crop 90 N/11 P/17 S yes chisel & harrow

alfalfa + grass hay & graze – no –

alfalfa + grass hay & graze – no –

crop harvest fertilizer (kg ha−1) pesticide/herbicide tillage

spring pea crop – yes –

winter pea graze – yes –

spring pea graze – no undercutter

alfalfa + grass hay – no –

crop harvest fertilizer (kg ha−1) pesticide/herbicide tillage

winter wheat crop 112 N yes –

winter wheat crop 62 N yes –

winter wheat crop – no undercutter

alfalfa + grass hay & graze – no –

2012

2013

2014

2015

2016

3

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Fig. 2. Monthly total precipitation (mm) and monthly average maximum and minimum air temperature (°C) from 2012 to 2016. Meteorological data from the Palouse Conservation Field Station operated by USDA-ARS in Pullman, WA [108].

RFV = (88.9 – 0.779 x ADF) / (1.29 x NDF)

2.4. Soil quality

(1)

In April of every year, prior to field operations and planting, soil samples were extracted from all plots. Bulk density samples were extracted from each plot for depths 0–7.5 and 7.5–15 cm. Six soil cores (3cm internal diameter PN425 8-inch Wet Sampling Tubes; JMC Soil Samplers, Newton, IA) were extracted without compaction from each plot in an evenly spaced grid pattern. Each core was measured to determine its volume and oven dried for 24 h at 105 °C to determine dry mass and bulk density. Simultaneously, soil samples for analysis were extracted from each plot in an evenly spaced grid pattern, and were broken up into 7 depth increments. Sixteen soil cores (1.75-cm internal diameter PN008 15-inch Wet Sampling Tubes; JMC Soil Samplers, Newton, IA) per plot were extracted for depths 0–7.5 cm, 7.5–15 cm, and 15–30 cm; 8 soil cores per plot were extracted for depth 30–60 cm; and 2 soil cores per plot were extracted for depths 60–90 cm, 90–120 cm, and 120–150 cm. Soils from each depth increment across a plot were composited and stored at 4 °C for further processing. Soil samples were sieved through 2 mm sieve to homogenize. Thirty g of soil were oven dried for 24 h at 105 °C to determine water content. Soil pH was determined in soil suspension (1:1 soil and water) (Thomas, 1996). Air-dried subsamples of soil were ground and analyzed for total C using dry combustion elemental analysis (Costech Elemental Combustion System 4010, Valencia, CA). Soil pH was < 7 for all soils; thus it was assumed that total C measured by combustion was organic C concentration (SOC) (Blanco-Canqui et al., 2017). Bulk density was used to express SOC in terms of volume (kg C cm−1 ha−1) (Brown and Huggins, 2012). Measured bulk density was used for surface depths (0–7.5 and 7.5–15 cm); all other bulk densities used for calculations were from similar depth increment averages for blocks 1, 2, and 3 (Palouse series) and block 4 (Thatuna series) at the nearby Cook Agronomy Farm (T. Brown, unpublished data). Profile SOC stocks were calculated on an equivalent mass basis (Ellert et al., 2001). In April of the final year of the experiment (2016), soil samples extracted as described above were subsampled and analyzed for potential N mineralization (PotN), and subsamples for depths 0–7.5 cm, 7.5–15 cm, and 15–30 cm were analyzed for microbial biomass C (MbioC) and N (MbioN) and dehydrogenase (DHase), acid-phosphatase (APase), and ß-glucosidase (ßGase) activities. PotN was measured as the difference in NH4+ between non-incubated soil and soil after a 14-d anaerobic incubation (Curtin and Campbell, 2007), with modification (Morrow et al., 2016). Twenty-five mL of 1 M KCl were added to 5 g of dry equivalent non-incubated soil, shaken for 30 min, and filtered. For the incubation, 5 g of dry equivalent soil was submerged in 12.5 mL deionized water and incubated at 40 °C for 14 d. To terminate the incubation, 12.5 mL of 2 M KCl were added to the incubated soil and water mixture, the samples shaken, and filtered. All samples were extracted and analyzed in duplicate. Filtrate from incubated and non-incubated soils was analyzed for inorganic N by colorimetry using an Alpkem segmented flow analyzer (Alpkem Corporation, Clackamas,

where RFV is a unit-less measure of forage quality, and NDF and ADF are % neutral detergent and % acid detergent fiber concentrations on a dry mass basis. Crop rotations in these treatments used a limited number of crops (peas, wheat, and alfalfa + grass), but within-year comparisons were made only when crop species, subtype (e.g., winter wheat or spring wheat), and use (e.g., pea used for grain or forage) were the same in two or more treatments. 2.3. Economic performance Annual enterprise budgets were constructed for each plot. Ownership costs consisted of machinery ownership costs (depreciation, interest, taxes, and insurance) (Painter, 2011) and land cost (based on a typical crop-share arrangement for this region, with owners receiving one-third of the crop and paying for one-third of the fertilizer and chemical costs). Ownership of farm machinery was intended to be appropriate for a typical farm of approximately 400 ha in size. Variable costs consisted of input costs (seed, fertilizers, and pesticides), costs of machinery use (fuel, repairs, and labor), and crop insurance. Input prices were based on annual input surveys for the region (Patterson et al., 2015; Patterson and Painter, 2014, 2013, 2012). Machinery use was based on the average tractor speed for a given field operation and the width of the implement. Labor was valued at $20 h−1, which included all applicable taxes. Insurance estimates were based on consultation with regional insurance agents, and were for 85% coverage of expected yields, which is the most common coverage level. Because hay and forage were not insurable in Whitman County at the time of the study, no insurance premiums were included for these crops. Revenue consisted of sales of grain, hay, and forage. Crop prices were based on annual average farmgate prices received for that crop class and quality in Whitman County as reported by the USDA National Agricultural Statistical Service (USDA National Agricultural Statistics Service, 2018). When county averages were not available, state or national averages were used. Grazed forage was valued as if it were cut and baled under a typical custom hay agreement, in which the landowner and custom operator each keeps half of the harvested hay. No additional charges for fencing and livestock handling were included, as these costs would typically be assumed by the custom operator. The first three years, 2012–2014, were considered transition years for ORGcrop and ORGhay, after which these plots were eligible for organic certification. While organic certification costs would be paid in 2015 and 2016, these costs were amortized over the 5-yr experiment duration. Organic hay and forage prices in 2015 and 2016 were assumed to be 20% higher than conventional prices for hay of the same class and quality (Long et al., 2013). National average organic wheat prices were used due to lack of available price data for Whitman County or Washington State. 4

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Table 2 Annual yields (grain crop, forage biomass consumed, or hay biomass harvested), yield quality, total aboveground biomass (harvested mass of grain, forage, or hay + unharvested mass of residue, ungrazed forage, or standing hay), total aboveground biomass N, and aboveground residue C during the 5-yr study of the four treatments: CONV, MIX, ORGcrop, and ORGhay. CONV

MIX

ORGcrop

ORGhay

crop harvest yield (Mg ha−1) quality biomass (Mg ha−1) biomass N (kg ha−1) residue C (Mg ha−1)

spring pea crop 2.1 ± 0.1 3.8% N 4.5 ± 0.2 89.7 ± 4.6 1142 ± 96

spring pea forage forage 1.5 ± 0.1 127 RFV 2.6 ± 0.1 48.1 ± 1.8 545 ± 65

alfalfa + grass establishment none – 1.2 ± 0.2 10.1 ± 0.2 303 ± 26

alfalfa + grass establishment none – 1.2 ± 0.2 10.1 ± 0.2 303 ± 26

crop harvest yield (Mg ha−1) quality biomass (Mg ha−1) biomass N (kg ha−1) residue C (Mg ha−1)

SW winter wheat crop 5.8 ± 0.2 11.0% protein 19.8 ± 1.0 170.4 ± 0.7 6275 ± 857

SW winter wheat crop 6.0 ± 0.2 11.6% protein 20.5 ± 0.6 196.8 ± 0.0 6510 ± 573

alfalfa + grass hay 5.1 ± 0.3 150 RFV 5.7 ± 0.3 103.6 ± 5.3 25 ± 8

regrowth not grazed – 2.0 ± 0.2 21.6 ± 1.8 852 ± 181

alfalfa + grass hay hay 5.1 ± 0.3 150 RFV 5.7 ± 0.3 103.6 ± 5.3 25 ± 8

regrowth not grazed – 2.0 ± 0.2 21.6 ± 1.8 852 ± 181

crop harvest yield (Mg ha−1) quality biomass (Mg ha−1) biomass N (kg ha−1) residue C (Mg ha−1)

SW spring wheat crop 2.3 ± 0.2 12.7% protein 9.7 ± 0.6 116.0 ± 9.9 3278 ± 532

SW spring wheat crop 2.3 ± 0.2 12.3% protein 9.6 ± 0.6 102.0 ± 5.6 3151 ± 430

alfalfa + grass hay 7.1 ± 0.4 122 RFV 7.7 ± 0.4 110.8 ± 7.8 243 ± 55

forage 1.9 ± 0.4 129 RFV 2.2 ± 0.4 56.8 ± 10.8 136 ± 54

alfalfa + grass hay 7.1 ± 0.4 122 RFV 7.7 ± 0.4 11.8 ± 7.8 243 ± 55

forage 1.9 ± 0.4 129 RFV 2.2 ± 0.4 56.8 ± 10.8 136 ± 54

crop harvest yield (Mg ha−1) quality biomass (Mg ha−1) biomass N (kg ha−1) residue C (Mg ha−1)

spring pea crop 0.6 ± 0.0 4.3% N 2.6 ± 0.2 51.4 ± 3.9 875 ± 174

winter pea forage 2.1 ± 0.1 123 RFV 3.2 ± 0.1 55.8 ± 3.1 450 ± 134

spring pea forage 1.5 ± 0.1 112 RFV 2.0 ± 0.1 49.3 ± 3.4 227 ± 123

alfalfa + grass hay 8.4 ± 0.4 160 RFV 9.0 ± 0.4 159.0 ± 8.6 241 ± 50

regrowth not grazed – 1.7 ± 0.3 28.5 ± 4.4 652 ± 265

crop harvest yield (Mg ha−1) quality biomass (Mg ha−1) biomass N (kg ha−1) residue C (Mg ha−1)

SW winter wheat crop 5.9 ± 0.2 10.6% protein 13.8 ± 0.6 138 ± 18 3459 ± 410

SW winter wheat crop 6.4 ± 0.3 10.1% protein 14.9 ± 0.6 143 ± 21 3662 ± 332

SW winter wheat crop 6.2 ± 0.2 9.0% protein 13.9 ± 0.4 118 ± 15 3242 ± 232

alfalfa + grass hay 7.5 ± 0.3 153 RFV 8.1 ± 0.3 134 ± 15 236 ± 55

forage 1.9 ± 0.3 127 RFV 2.5 ± 0.3 55 ± 15 257 ± 127

2012

2013

2014

2015

2016

Values are means ± SE.

p-nitrophenyl phosphate, and incubated for 1 h at 37 °C. Toluene was omitted. Samples then received 1 mL 0.5 M CaCl2 and 4 ml 0.5 M NaOH, were mixed, and then were centrifuged at 1500 RPM for 10 min. Triplicate blanks were carried out in parallel, with disodium p-nitrophenyl phosphate being added after incubation. Absorbance was measured at 405 nm and compared with with p-nitrophenyl standards. ßGase activity was assayed using the same procedure as for APase, but using modified universal buffer at pH 6.0 and p-nitrophenyl glucoside as a substrate.

OR). MbioC and MbioN were measured using chloroform fumigation (Voroney et al., 2008), with modification (Morrow et al., 2016). Triplicates of 10-g dry equivalent samples were incubated for 48 h at 20 °C before being fumigated with chloroform for 24 h under a vacuum. Triplicates of the same soils were incubated for the same period, followed by 24 h under a vacuum with no fumigation. Soils were extracted with 25 mL of nanopure water, shaken for 30 min, centrifuged for 15 min at 5000 rpm, and vacuum-filtered through 0.45 μm nylon filters. Filtrate was frozen until being analyzed for C and N on a high-temperature combustion TOC machine (Shimadzu TOC-V Analyzer with total N unit; Kyoto, Japan). Microbial biomass was the difference in water-soluble C and N between fumigated and non-fumigated samples. Soil enzyme activities were assayed as described by Tabatabai (Tabatabai, 1994), with modification. For DHase, triplicates of 5-g dry equivalent soil samples were brought to 25% gravimetric water content with deionized water and incubated at 35 °C for 12 h. Each sample received 0.5 mL 3% triphenyl tetrazolium chloride and 1 mL 2% CaCO3 and was incubated for 24 h at 35 °C. 10 mL methanol was then added to samples, which were then shaken and centrifuged at 1500 RPM for 10 min. Absorbance was measured at 490 nm and compared with triphenylformazan (TPF) standards. For APase, triplicates of 1-g dry equivalent soil were mixed with 4 mL modified universal buffer at pH 6.5 and 1 mL of 0.05 M disodium

2.5. Statistical analyses Statistical analyses were performed using the PROC MIXED procedure of SAS version 9.2 (SAS Institute Inc., Cary, North Carolina), with farming system (CONV, MIX, ORGcrop, and ORGhay) as the main treatment and fixed effect. Where appropriate, soil depth was included as a fixed effect. Random effects were block, block × farming system, block × depth, and block × farming system × depth interactions (Littell et al., 2006). Annual measurements (profitability, SOC, and soil pH) were analyzed as repeated measures over 5 yr. The selection criteria for covariance structures used in repeated measures analyses consisted of choosing the one that minimized AIC and BIC (Wang and Goonewardene, 2004). Economics repeated measures were analyzed using the CS and AR(1) covariance structures, and SOC, and soil pH 5

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Table 3 Crop prices, sales, operating costs, ownership costs, returns over operating costs, and net returns during the 5-yr study of the four treatments: CONV, MIX, ORGcrop, and ORGhay.

CONV

MIX

ORGcropd

ORGhayd

2012 2013 2014 2015 2016 2012 2013 2014 2015 2016 2012 2013 2014 2015 2016 2012 2013 2014 2015 2016

Crop

Crop pricea $ unit−1

Sales

Operating costsb

Ownership costs $ ha−1

Returns over operating costs

Net returnsc

spring pea SW winter wheat SW spring wheat spring pea SW winter wheat spring pea (forage) SW winter wheat SW spring wheat winter pea (forage) SW winter wheat none hay hay & forage spring pea (forage) SW winter wheat none hay hay & forage hay hay & forage

17.30 cwt−1 7.35 bu−1 7.34 bu−1 14.90 cwt−1 4.85 bu−1 250 ton−1 7.35 bu−1 7.34 bu−1 240 ton−1 4.85 bu−1 – 195 ton−1 197 ton−1 290 ton−1 4.85 bu−1 – 195 ton−1 197 ton−1 200 ton−1 198 ton−1

781 ± 90 1570 ± 86 697 ± 78 180 ± 32 1051 ± 47 242 ± 12 1642 ± 92 672 ± 57 254 ± 14 1133 ± 67 0±0 1478 ± 112 2277 ± 259 237 ± 20 1829 ± 95 0±0 1478 ± 112 2277 ± 259 1974 ± 146 2008 ± 101

462 679 697 428 524 301 660 690 208 475 382 160 161 409 357 382 160 161 159 160

339 ± 30 511 ± 28 223 ± 26 116 ± 11 362 ± 15 234 ± 8 541 ± 30 217 ± 19 220 ± 9 404 ± 22 119 ± 0 679 ± 37 1032 ± 113 432 ± 13 784 ± 31 119 ± 0 679 ± 37 1032 ± 113 855 ± 48 949 ± 47

319 ± 179 891 ± 172 0 ± 157 −248 ± 64 527 ± 94 −58 ± 25 982 ± 184 −17 ± 115 45 ± 27 658 ± 135 −382 ± 0 1318 ± 224 2116 ± 518 −172 ± 39 1472 ± 190 −382 ± 0 1318 ± 224 2116 ± 518 1815 ± 291 1849 ± 202

−20 ± 60 380 ± 58 −224 ± 53 −365 ± 22 165 ± 31 −292 ± 4 441 ± 62 −235 ± 38 −175 ± 5 253 ± 45 −501 ± 0 639 ± 75 1083 ± 146 −604 ± 7 688 ± 64 −501 ± 0 639 ± 75 1083 ± 146 960 ± 98 900 ± 56

Values listed ± SE with the exception of operating costs, which were the same across plots. a Crop prices are reported in standard units for the region: bushels (bu) for spring and winter wheat, hundred-pound weight (cwt) for peas, and 2000-pound ton (ton). b Operating costs are the same across plots for each treatment each year. c Net returns is returns over total costs. d Crop prices for ORGcrop and ORGhay include organic premiums for 2015 and 2016 only.

respectively. This points to the value of returned N from on-site grazing and the use of livestock digestion as a tool for managing nutrient cycling (Martens and Entz, 2011). For the 2014 spring wheat crop, MIX and CONV both received 90 kg N ha−1 based on spring soil tests and similar resulting yields, protein concentration, and biomass (P = 0.959, P = 0.60, and P = 0.089, respectively) suggest that apparent N benefits of the grazed winter pea biomass were not sustained after 2 years. High protein concentrations averaging 12.5% and lower yields than expected, however, suggest these crops were over-fertilized (Koenig, 2005; Mahler and Guy, 2007). Following 4 years of legume crops, winter wheat in ORGcrop receiving no additional fertilizer had similar yield compared to CONV winter wheat that received 112 kg N ha−1. However, protein concentrations below 10% for ORGcrop wheat suggest that N was limiting to yield potential (Brown et al., 2005), a common challenge in organic systems (Miller et al., 2011). With lower protein and lower N demand, soft white wheats used in this study are more suited to a legume-based organic cropping system. More research is needed to determine optimal timing for N availability following alfalfa termination in the dryland Palouse region. In the humid Midwest, cereal crops showed no benefit from additional N fertilizer the first year after alfalfa termination (Yost et al., 2014); however, mineralization can be significantly slower in dryland regions (Angus and Peoples, 2012; Davies and Peoples, 2003). In this study, a pea forage was used between the perennial hay and planting winter wheat to allow more time for mineralization of alfalfa roots and residue, to provide additional N by biological N fixation, and to allow for fall and spring termination of the preceding hay stand. Greater N benefit may have been achieved by grazing more of the hay biomass instead of exporting it as a hay crop. Hay productivity peaked in 2015 despite hot dry conditions that limited yields of other annual crops in this study and the region, supporting the hypothesis that deep-rooted perennial crops can have greater drought tolerance than many annual crops (Lelièvre et al., 2011; Thiessen Martens et al., 2015). In contrast, in 2015 CONV spring pea yields and biomass were 71% and 42% lower, respectively, than the

repeated measures were analyzed using the ANTE(1) and AR(1) covariance structures. Yield comparisons were made between farming systems and years with the same crops. When comparing between years, yield measurements were analyzed using linear contrasts. When fixed effects were found to be significant, treatment means were separated by using a non-adjusted least square means test (Littell et al., 2006). Results were considered statistically significant when P < 0.05. Although not statistically significant, 0.05 < P < 0.10 was considered notably different. 3. Results & discussion 3.1. Productivity Where comparable, yields from MIX were similar to or greater than CONV, and yields from ORGcrop were similar to both CONV and MIX, despite MIX receiving less fertilizer than CONV and ORGcrop receiving no fertilizer. In 2013, winter wheat yields from MIX were notably higher than CONV in 2013 (P = 0.057) and in 2016 MIX winter wheat yielded 7.8% more than CONV (P = 0.008) despite receiving 10 and 50 kg ha−1 less N fertilizer in 2013 and 2016, respectively. In 2016, ORGcrop winter wheat yields did not differ from CONV (P = 0.320) or MIX (P = 0.679), but averaged 15.5% lower protein concentration than CONV and MIX (P = 0.011) (Table 2). This contrasts with global organic wheat yields averaging 73% of conventionally grown wheat (De Ponti et al., 2012). Winter wheat yields in all treatments were higher than the 2013 and 2017 county averages of 5.5 and 5.6 Mg ha−1, respectively (USDA National Agricultural Statistics Service, 2018). Legumes played an important role in N cycling and grain yields in all treatments. Yield results agree with other studies that have found higher grain yields following leguminous green manure crops compared to fertilized grain crops without green manures (Badaruddin and Meyer, 1990; Stark et al., 2006). Grazing legume biomass in MIX returned a portion of N to the soil compared to harvesting a pea crop from CONV, which exported 78 and 24 kg N ha−1 in 2012 and 2015, 6

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Table 4 Average sales, total costs, net returns and return on investment over the 5-yr study of the four treatments: CONV, MIX, ORGcrop, and ORGhay.

CONV MIX ORGcropd ORGhayd

Sales

Operating cost Total costa 5-yr average $ ha−1

Net returnsb

Return on investmentc %

856 ± 286 789 ± 326 1164 ± 559 1548 ± 523

558 467 294 205

−13 ± 170 −1 ± 181 261 ± 417 616 ± 362

−1.5 −0.2 28.9 66.2

± ± ± ±

62 106 61 50

868 790 903 930

± ± ± ±

147 187 260 260

Values listed ± SE. a Total cost is the sum of operating costs and ownership costs. b Net returns are returns over total cost. c Return on investment is calculated as net returns ÷ total cost. d Returns for ORGcrop and ORGhay include organic premiums for 2015 and 2016 only.

2012 CONV spring pea crop (P < 0.001). County average dry bean yields were 35% lower in 2015 than in 2012 (USDA National Agricultural Statistics Service, 2018). 3.2. Economics Differences in profitability were driven by differences in yield, crop value, and operating costs. Over the 5-year rotation returns over operating costs, net returns, and return on investment were ORGhay > ORGcrop > MIX = CONV (Table 3). Treatment, year, and treatment × year were significant effects on sales and net returns (P < 0.001). Overall poor economic performance of MIX and CONV was the result of profitable winter wheat offset by negative returns on spring wheat and forage- and crop-peas. Winter wheat was the only crop with positive net returns for CONV and MIX, averaging $272 ha−1 in net returns for CONV and $348 ha−1 for MIX (Table 4). Winter wheat was most profitable in ORGcrop, followed by MIX, due to organic premiums and no fertilizer costs in ORGcrop and reduced fertilizer costs and higher yields in MIX compared with CONV. Net returns from the 2016 winter wheat crop in ORGcrop were 317% higher than CONV (105% higher without organic premium) and 172% higher than MIX (33% higher without premium) (Table 4). Net returns were higher in all treatments than regional average net returns for soft white winter wheat from 2011 to 2015 of $159 ha−1 due in part to the lower regional average yields over this period (Kirby et al., 2017; Painter, 2016). In CONV and MIX, profitable winter wheat yields were offset by poor yields and economic performance of spring wheat and forage- and crop-peas. The lowest revenue in CONV was for spring peas in 2015 and in MIX was for grazed pea biomass in 2012 and 2015 (Table 3). The lowest net returns for these treatments also included spring wheat, averaging $-229 ha−1, which, while having higher revenue, also had high input costs (Fig. 3). 5-year net returns of $0 ha−1 for MIX and CONV were lower than the average profitability of $28 ha−1 for similar winter wheat-spring wheat-pea rotations in the region (Kirby et al., 2017). Economic performance may improve when spread over other landscape positions (our study landscape position being of relatively poorer soil quality) and over a longer time period, typical of a farm in the Palouse region (Young et al., 2004). Alternative spring crops, such as hard red spring wheat in lieu of soft spring wheat and chickpeas instead of peas, may also improve profitability of these rotations (Kirby et al., 2017). Furthermore, the poor performance of some crops in this study would likely receive some insurance compensation under real farm conditions, but potential insurance payouts are not included in our economic model. High hay prices and low input costs were the drivers of high profitability in ORGcrop and ORGhay. During this study period, high hay prices (135%–110% of long-term average from 2013 to 2015) and volatile wheat prices (129% of long-term average in 2013 and 77% of

Fig. 3. Breakdown of annual operating costs for the four farming system treatments from 2012 to 2016. Annual total operating costs ($ ha−1) are broken down into labor costs, input costs (including seed, inoculants, fertilizers, pesticides, and fuel), and other costs (custom rates, insurance, interest, and overhead). Annual operating costs were the same across plots of the same farming system.

Fig. 4. Long-term price fluctuations for soft white winter wheat and alfalfa + grass hay from 1980–2017. Wheat prices are annual average prices for soft white winter wheat in Portland, OR, minus average shipping costs of $0.61 bu−1 [109]. Hay prices are annual average farmgate prices for mixed alfalfa and grass hay in Washington and Idaho [47]. The period of this study, from 2012 to 2016, is shaded in gray. Dotted lines indicate average prices since 1980 of $157.87 ton−1 for hay and $6.30 bu−1 for wheat. All prices are adjusted for inflation and expressed in 2016 $US.

average in 2016) contributed to the large discrepancy in economic performance between the four farming systems (Fig. 4). Organic price premiums beginning in 2015 for ORGcrop and ORGhay helped to buffer drops in hay and wheat prices in 2016 (88% and 77% of long-term averages, respectively). Overall lower operating costs for ORGcrop and ORGhay were the 7

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P = 0.003) and MIX (7.5–15 and 60–90 cm; P = 0.041 and P = 0.029) were similar to rates reported from 0 to 20 cm for the conversion of native vegetation to agriculture in this region (Brown and Huggins, 2012) (Figure S1). In ORGcrop, a significant negative trend at depth 7.5–15 cm (P = 0.010) did not correspond to a trend in profile SOC (Figure S1). Grazed annual forages in MIX had no effect on SOC compared to CONV systems without grazed forage. An earlier long-term study in this region found greater SOC under a winter wheat-spring peaAustrian winter pea crop rotation compared to a winter wheat-spring pea rotation (Bolton et al., 1985). The plots for this study were located on the upper slope of a hillside, a landscape position that is prone to erosion, an important potential driver of SOC loss (De Jong and Kachanoski, 1988). Rill erosion was observed in CONV, MIX, and ORGcrop, but not in ORGhay during the winter and spring of 2015, and could help explain treatment differences. No significant trends in SOC were found for ORGhay. In a review, Brown and Huggins (2012) found changes in SOC under mixed perennial/annual systems in the Palouse region similar to ORGhay of 0.066 to −0.009 Mg C ha−1 cm−1 yr−1 within the surface 30 cm. In other regions, perennial crops and forages have been found to significantly increase SOC both in surface soil (Blanco-Canqui et al., 2017; Su, 2007) and at depth (Guan et al., 2016), but removing biomass can reduce or eliminate this potential to increase SOC compared to grazing it or leaving it in place (Bell et al., 2012; Franzluebbers and Stuedemann, 2009). In this study, harvesting hay removed roughly 80% of aboveground biomass annually (Table 2) and thereby significantly reduced C inputs at the soil surface. Short-term changes in total SOC are usually small in relation to the background level of total SOC, and a longer study period may be required to measure any meaningful long-term changes (Conant and Paustian, 2002). Soil pH showed significant trends at some depths for CONV, MIX, and ORGcrop, but not for ORGhay. Soil pH was affected by depth (P < 0.001), year (P < 0.001), and depth × year interactions (P < 0.001) (Figure S2). A significant negative trend in soil pH in ORGcrop at depth 7.5–15 cm (P = 0.022) may be attributed to the accumulation and oxidation of organic matter, leaching of NO3− with basic cations, or biological N fixation in this zone (Bowman and Halvorson, 1998; Helyar and Porter, 1989). In CONV and MIX, soil pH increased over time at depth 90–120 cm (P = 0.016 and P = 0.011). Significant loss of topsoil could result in sampling depths that have shifted deeper to higher-pH soil or increases in base saturation over time (Helyar and Porter, 1989). ORGcrop and ORGhay were generally found to have higher MbioC, MbioN, ßGase activity than CONV and MIX at certain depths (Fig. 5). No treatment differences were found in DHase and APase activities. PotN was greater in MIX, ORGcrop, and ORGhay at the 0–7.5 cm depth than in CONV (Fig. 5). At this depth, PotN was 12.8, 18.4, and 14.0 mg N kg soil−1 more in MIX, ORGcrop, and ORGhay compared to CONV. These treatments were more reliant on N mineralization by design, including higher quantities of high-N pea and alfalfa biomass and the use of livestock grazing to cycling N (Martens and Entz, 2011). Microbial biomass has been found to be sensitive to organic matter additions (McDaniel et al., 2014). Large multi-year inputs of legume biomass in ORGcrop and ORGhay are likely driving differences in MbioC and MbioN compared to MIX and CONV. MbioC differed with depth (P = 0.001) and MbioN by treatment (P = 0.009) and depth (P < 0.001) (Fig. 5). At depth 0–7.5 cm, MbioC in CONV was similar to MIX, but was 39% lower than ORGcrop (P = 0.003) and 24% lower than ORGhay (P = 0.038). At depth 0–7.5 cm, MbioN in ORGcrop was similar to ORGhay but 2.5× greater than CONV (P = 0.011) and 3× greater than MIX (P = 0.006). At depth 7.5–15 cm, MbioN in ORGcrop was significantly greater than that in CONV (P = 0.014), MIX (P = 0.032), and ORGhay (P = 0.020). That these differences do not extend below 15 cm suggests that they are influenced predominately by surface inputs of residues and manure, and shallow roots (Acosta-

result of 84% lower input costs and 18% higher labor costs than for CONV and MIX (Fig. 3). Previous studies have similarly found organic systems to have lower input costs and higher labor costs than their conventional counterparts (Davis et al., 2012; Mäder et al., 2002). In this study no fertilizer was applied to ORGcrop and ORGhay systems during the 5-yr study period based on annual soil fertility testing. However, fertilizer must be applied to these systems when needed, and the additional cost of fertilizing these systems will be incurred in the long term (Fuerst et al., 2009; Painter, 2015). Alternate methods for accounting grazing costs could also increase the labor costs for the grazed systems (MIX, ORGcrop, and ORGhay). In this study the labor required for grazing is not reflected in the labor costs; instead grazing labor is wrapped into the custom haying operation that receives half of the crop in exchange for harvesting the hay. The non-custom economics of harvesting hay would effectively double revenue from forage while also increasing labor costs and machinery costs. Grazed annual green manure crops produced negative net returns in all years for MIX and ORGcrop (Table 4). Grazed Austrian winter peas in 2015 for MIX were the only annual forage with positive returns to operating costs. Different methods for valuing grazed forage may alter the profitability of these grazed green manures. For example, while the value of reduced or avoided fertilizer costs is reflected in the following crop year's budget, this value must be considered when looking at the grazed forage budget in isolation (Painter, 1991). Grazing is an important tool for producing revenue from a green manure crop that otherwise would not produce any immediate source of revenue (Martens and Entz, 2011). Organic price premiums increased the profitability of ORGcrop and ORGhay but these treatments remained the most profitable even without organic premiums: 5-yr net returns declined to $127 ha−1 for ORGcrop (51% lower) and $463 ha−1 for ORGhay (25% lower), both still more profitable than CONV and MIX (P < 0.001). In contrast to average breakeven price premiums for organic systems reported elsewhere (Reganold and Wachter, 2016), premiums were not required to make these systems profitable. Additionally, this study finds that alfalfa/grass hay was a productive and profitable crop during the 3-yr transition prior to organic certification, commonly a challenging period for farmers transitioning to organic practices (Caldwell et al., 2014). This is in agreement with other studies that have found perennial legume and grass species to be preferable crops during the organic transition period (Delate and Cambardella, 2004; Gallagher et al., 2010). Interestingly, rather than crop and revenue diversity driving profitability as we had hypothesized, under these market conditions ORGhay was actually the least diverse crop rotation with the best economic performance. Five-year plot yields and returns are not directly comparable to field-scale data or to long-term economic and productivity performance (Young et al., 2004), and discrepancies between plot-scale and fieldscale performance can be especially great in low-input and organic systems (Kravchenko et al., 2017). The research plots of our study are located on south- and west-facing upper slopes, and do not represent the landscape variability of a typical farm field in this area. Greater spatial and temporal coverage, accounting for landscape variability and long-term variability in crop and input prices, may reveal different results regarding the performance of these cropping systems (Davis et al., 2012; Painter et al., 1993). 3.3. Soil quality Total soil profile SOC decreased in CONV (P = 0.02) and MIX (P < 0.001) but showed no significant trends in ORGcrop (P = 0.72) and ORGhay (P = 0.66) (Table 5). The SOC loss of 3.1–4.1 Mg C ha−1 yr−1 in CONV and MIX is more than 3× greater than soil profile SOC changes reported for the region (Brown and Huggins, 2012). Significant negative trends in SOC at specific depths for CONV (15–30 cm; 8

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Table 5 Annual soil profile SOC content (kg C ha−1) for the four treatments from 2012 to 2016. Soil profile are the depths from 0 to 150 cm sampled in this study, and SOC contents are calculated on an equivalent mass basis. 2012

CONV MIX ORGcrop ORGhay

116.6 147.7 131.3 131.3

2013

± ± ± ±

13.4 12.6 11.1 11.1

115.9 143.6 130.4 130.4

± ± ± ±

13.8 13.3 12.2 12.2

2014 Mg C ha−1

2015

116.2 134.8 128.1 128.1

107.3 132.6 129.6 116.2

± ± ± ±

3.2 18.5 21.8 21.8

2016

± ± ± ±

14.2 16.1 14 18.5

105.2 132.7 126.1 131.6

± ± ± ±

14.6 8 11.6 12.1

Trenda Mg C ha−1 yr−1

P value

−3.1 ± 0.9 −4.1 ± 0.9 ns ns

0.02 < 0.001 0.72 0.66

Values are means ± SE. a Slope is given for depths with significant linear trends; "ns" denotes no significant trend.

rotation (Bolton et al., 1985). Average DHase activity at 0–7.5 and 7.5–15 cm depths of 12.30 and 5.99 mg kg soil−1, respectively, are slightly greater than measurements of 4.27–9.58 mg kg soil−1 from other soils in this region (Bolton et al., 1985). ßGase activity was significantly different by treatment (P = 0.011) and by depth (P < 0.001) (Fig. 5). At depth 0–7.5 cm, ßGase activity in ORGcrop was similar to ORGhay and together averaged 169.3 mg kg soil−1 hr−1, 2.1x higher than MIX (P = 0.026 and P = 0.006) and 2.5× higher than CONV (P = 0.013 and P = 0.003). The strong connection between ßGase activity and carbon cycling suggests that the high inputs

Martínez et al., 2007). High MbioN and low Mbioc:MbioN in ORGcrop is likely due to active decomposition of N-rich legume biomass following tillage and hay termination. This study found no significant differences in DHase between treatments at any of the three depth increments, despite its ubiquitous role in microbial activity and previous studies finding it to be sensitive to soil management and organic matter (Chavarría et al., 2016; Chu et al., 2007). DHase activity has been found to be greater under perennial grassland soils than cropped soils (Carpenter-Boggs et al., 2003) and greater under a green manure rotation than a summer fallow

Fig. 5. 2016 soil microbial biomass C (MbioC), microbial biomass N (MbioN), potential N mineralization (PotN), and dehydrogenase (DHase), acid-phosphatase (APase), and ß-glucosidase (ßGase) activities at three depths: 0–7.5 cm (white bars), 7.5–15 cm (light gray bars), and 15–30 cm (dark gray bars). Values are means ± SE. Letters indicate significantly different means (P < 0.05) analyzed by depth. 9

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References

and active turnover of organic materials in ORGcrop and ORGhay are driving these differences. APase activity did not differ significantly between treatments at any of the three depths (Fig. 5). It has been suggested that APase is less sensitive to soil management than other enzyme activities (Raiesi and Beheshti, 2014). But many studies have found significant management effects on APase activity (Bolton et al., 1985; Carpenter-Boggs et al., 2003; Chavarría et al., 2016; Dodor and Tabatabai, 2003), including the correlation of fungal communities with increased APase, which would favor the prevalence of APase in perennial systems such as ORGhay (Bolan and Hedley, 2003; Joner et al., 2000).

Acosta-Martínez, V., Bell, C.W., Morris, B.E.L., Zak, J., Allen, V.G., 2010. Long-term soil microbial community and enzyme activity responses to an integrated cropping-livestock system in a semi-arid region. Agric. Ecosyst. Environ. 137, 231–240. https:// doi.org/10.1016/j.agee.2010.02.008. Acosta-Martínez, V., Mikha, M.M., Vigil, M.F., 2007. Microbial communities and enzyme activities in soils under alternative crop rotations compared to wheat-fallow for the Central Great Plains. Appl. Soil Ecol. 37, 41–52. https://doi.org/10.1016/j.apsoil. 2007.03.009. Acosta-Martínez, V., Zobeck, T.M., Allen, V., 2004. Soil microbial, chemical and physical properties in continuous cotton in integrated crop-livestock systems. Soil Sci. Soc. Am. J. 68, 1875–1884. https://doi.org/10.2136/sssaj2004.1875. Allen, V.G., Baker, M.T., Segarra, E., Brown, C.P., 2007. Integrated irrigated crop-livestock systems in dry climates. Agron. J. 99, 346–360. https://doi.org/10.2134/ agronj2006.0148. Angus, J.F., Peoples, M.B., 2012. Nitrogen from Australian dryland pastures. Crop Pasture Sci. 63, 746–758. https://doi.org/10.1071/CP12161. Badaruddin, M., Meyer, D.W., 1990. Green-manure legume effects on soil nitrogen, grain yield, and nitrogen nutrition of wheat. Crop Sci. 30, 819–825. Bell, L.W., Sparling, B., Tenuta, M., Entz, M.H., 2012. Soil profile carbon and nutrient stocks under long-term conventional and organic crop and alfalfa-crop rotations and re-established grassland. Agric. Ecosyst. Environ. 158, 156–163. https://doi.org/10. 1016/j.agee.2012.06.006. Bennett, A.J., Bending, G.D., Chandler, D., Hilton, S., Mills, P., 2012. Meeting the demand for crop production: the challenge of yield decline in crops grown in short rotations. Biol. Rev. Camb. Philos. Soc. 87, 52–71. https://doi.org/10.1111/j.1469-185X.2011. 00184.x. Blanco-Canqui, H., Francis, C.A., Galusha, T.D., 2017. Does organic farming accumulate carbon in deeper soil profiles in the long term? Geoderma 288, 213–221. https://doi. org/10.1016/j.geoderma.2016.10.031. Bolan, N.S., Hedley, M.J., 2003. Role of carbon, nitrogen, and sulfur cycles in soil acidification. In: Rengel, Z. (Ed.), Handook of Soil Acidity. Marcel Dekker, New York, pp. 27–52. Bolton, H., Elliott, L.F., Papendick, R.I., Bezdicek, D.F., 1985. Soil microbial biomass and selected soil enzyme activities: effect of fertilization and cropping practices. Soil Biol. Biochem. 17, 297–302. https://doi.org/10.1016/0038-0717(85)90064-1. Borrelli, K., Koenig, R.T., Gallagher, R.S., Pittman, D., Snyder, A.M., Burke, I.C., Hoagland, L., Fuerst, E.P., Pittmann, D., Snyder, A.M., Koenig, R.T., Fuerst, E.P., Burke, I.C., Hoagland, L., 2010. Alternative strategies for transitioning to organic production in direct-seeded grain systems in Eastern Washington I: crop agronomy. J. Sustain. Agric. 34, 461–477. https://doi.org/10.1080/10440046.2010.484680. Bowman, R.A., Halvorson, A.D., 1998. Soil chemical changes after nine years of differential N fertilization in a no-till dryland wheat-corn-fallow rotation. Soil Sci. 163, 241–247. Brown, B., Westcott, M., Christensen, N., Pan, B., Stark, J., 2005. Nitrogen Management for Hard Wheat Protein Enhancement. Pacific Northwest Ext. PNW 578. Brown, T.T., Huggins, D.R., 2012. Soil carbon sequestration in the dryland cropping region of the Pacific Northwest. J. Soil Water Conserv. 67, 406–415. https://doi.org/ 10.2489/jswc.67.5.406. Brown, T.T., Koenig, R.T., Huggins, D.R., Harsh, J.B., Rossi, R.E., 2008. Lime effects on soil acidity, crop yield, and aluminum chemistry in direct-seeded cropping systems. Soil Sci. Soc. America 72. https://doi.org/10.2136/sssaj2007.0061. Caldwell, B., Mohler, C.L., Ketterings, Q.M., DiTommaso, A., 2014. Yields and profitability during and after transition in organic grain cropping systems. Agron. J. 106, 871–880. https://doi.org/10.2134/agronj13.0286. Carpenter-Boggs, L., Stahl, P.P.D., Lindstrom, M.J., Schumacher, T.E., 2003. Soil microbial properties under permanent grass, conventional tillage, and no-till management in South Dakota. Soil Tillage Res. 71, 15–23. https://doi.org/10.1016/S01671987(02)00158-7. Chavarría, D.N., Verdenelli, R.A., Serri, D.L., Restovich, S.B., Andriulo, A.E., Meriles, J.M., Vargas-Gil, S., 2016. Effect of cover crops on microbial community structure and related enzyme activities and macronutrient availability. Eur. J. Soil Biol. 76, 74–82. https://doi.org/10.1016/j.ejsobi.2016.07.002. Chu, H., Lin, X., Fujii, T., Morimoto, S., Yagi, K., Hu, J., Zhang, J., 2007. Soil microbial biomass, dehydrogenase activity, bacterial community structure in response to longterm fertilizer management. Soil Biol. Biochem. 39, 2971–2976. https://doi.org/10. 1016/j.soilbio.2007.05.031. Conant, R.T., Paustian, K., 2002. Spatial variability of soil organic carbon in grasslands : implications for detecting change at different scales. Environ. Pollut. 116, 127–135. Curtin, D., Campbell, C.A., 2007. Mineralizable Nitrogen, in: Soil Sampling and Methods of Analysis, Canadian Society of Soil Science. CRC Press, Boca Raton, FL, pp. 599. Davies, S.L.A., Peoples, M.B.A., 2003. Identifying potential approaches to improve the reliability of terminating a lucerne pasture before cropping : a review. Aust. J. Exp. Agric. 43, 429–447. Davis, A.S., Hill, J.D., Chase, Ca, Johanns, A.M., Liebman, M., 2012. Increasing cropping system diversity balances productivity, profitability and environmental health. PLoS One 7, e47149. https://doi.org/10.1371/journal.pone.0047149. De Jong, E., Kachanoski, R.G., 1988. The importance of erosion in the carbon balance of prairie soils. Can. J. Soil Sci. 68, 111–119. De Ponti, T., Rijk, B., Van Ittersum, M.K., 2012. The crop yield gap between organic and conventional agriculture. Agric. Syst. 108, 1–9. https://doi.org/10.1016/j.agsy.2011. 12.004. Delate, K., Cambardella, C.A., 2004. Agroecosystem performance during transition to certified organic grain production. Agron. J. 96, 1288–1298. https://doi.org/10.

4. Conclusion This study was an examination of the performance of four contrasting farming systems in terms of their total productivity, economic performance, and impacts on soil biological properties and pH. ORGhay, ORGcrop, MIX, and CONV in this order produced a gradation of forage production relative to cereal production from greatest to least, and also a gradation of economic and soil sustainability metrics from greatest to least. The system with least crop diversity, ORGhay, provided the best outcomes in financial performance and, along with ORGcrop, the best soil health outcomes during this study period. The ability to extrapolate these findings is limited by the length of the study period and by the size of the study site relative to long-term and large-scale variability. This 5-yr period had overall high hay prices and overall average grain prices compared to long-term prices, favoring the economic performance of ORGhay and ORGcrop. The landscape position of this study site is of relatively poorer soil quality and is not representative of the full heterogeneity of soils that make up a typical farm field in this region (an area of native grassland soils of generally high quality). Integrating perennial crops, such as alfalfa and forage grasses, into organic farming systems can build soil quality, be profitable, and supply nitrogen to succeeding grain crops. These perennial crops were furthermore shown to be more resilient to heat and drought compared to annual legumes. Livestock are an important tool for utilizing forage resources, generating revenue, and managing nutrient cycling. There remains great untapped potential for perennial crops to improve soil quality, and for perennial hay in certified organic systems to increase revenues in the Palouse region of eastern Washington. Future research on these plots should examine the long-term economic stability of these farming systems and characterize the nature of change in SOC between stable and labile fractions of organic matter.

Declaration of Competing Interest None.

Acknowledgements The authors thank Eric Zakarison and Sheryl Hagen-Zakarison for their expertise and for providing the research site. This work was supported by the United States Department of Agriculture National Institute of Food and Agriculture (grant number < GN1 > 230470) and National Science Foundation Integrative Graduate Education and Research Traineeship (grant number < GN2 > 0903714) < / GN2 > < /GN1 > .

Appendix A. Supplementary data Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.agee.2019.106665. 10

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114, 201612311. https://doi.org/10.1073/pnas.1612311114. Lelièvre, F., Seddaiu, G., Ledda, L., Porqueddu, C., Volaire, F., 2011. Water use efficiency and drought survival in Mediterranean perennial forage grasses. Field Crops Res. 121, 333–342. https://doi.org/10.1016/j.fcr.2010.12.023. Littell, R.C., Milleken, G.A., Stroup, W.W., Wolfinger, R.D., Schabenberger, O., 2006. SAS for Mixed Models, 2nd ed. SAS Institute, Inc., Cary, NC. Long, R.F., Orloff, S.B., Klonsky, K.M., De Moura, R.L., 2013. Sample costs to establish and produce organic alfalfa hay. Univ. Calif. Coop. Ext. https://www.doi.org/AFSV-08. Mäder, P., Fließbach, A., Dubois, D., Gunst, L., Fried, P., Niggli, U., 2002. Soil fertility and biodiversity in organic farming. Science 296, 1694–1697. https://doi.org/10.1126/ science.1071148. Mahler, R.L., Guy, S.O., 2007. Northern Idaho Fertilizer Guide: Soft White Spring Wheat. University of Idaho Extension, No. CIS 1101. Martens, J.R.T., Entz, M.H., 2011. Integrating green manure and grazing systems: a review. Can. J. Plant Sci. 91, 811–824. https://doi.org/10.4141/CJPS10177. Maughan, M.W., Flores, J.P.C., Anghinoni, I., Bollero, G., Fernández, F.G., Tracy, B.F., 2009. Soil quality and corn yield under crop-livestock integration in Illinois. Agron. J. 101, 1503–1510. https://doi.org/10.2134/agronj2009.0068. McCool, D.K., Huggins, D.R., Saxton, K.E., Kennedy, A.C., 2001. Factors affecting agricultural sustainability in the pacific Northwest, USA: an overview. In: Stott, D.E., Mohtar, R.H., Steinhardt, G.C. (Eds.), Sustaining the Global Farm, pp. 255–260. McDaniel, M.D., Tiemann, L.K., Grandy, A.S., 2014. Does agricultural crop diversity enhance soil microbial biomass and organic matter dynamics? A meta-analysis. Ecol. Appl. 24, 560–570. https://doi.org/10.1890/13-0616.1. Miller, P.R., Lighthiser, E.J., Jones, C.A., Holmes, J.A., Rick, T.L., Wraith, J.M., 2011. Pea green manure management affects organic winter wheat yield and quality in semiarid Montana. Can. J. Plant Sci. 91, 497–508. https://doi.org/10.4141/CJPS10109. Morrow, J.G., Huggins, D.R., Carpenter-Boggs, L.A., Reganold, J.P., 2016. Evaluating measures to assess soil health in long-term agroecosystem trials. Soil Sci. Soc. Am. J. 80, 450–462. https://doi.org/10.2136/sssaj2015.08.0308. Painter, K., 2016. Enterprise Budgets for the Dryland Grain Annual Cropping Region of the Pacific Northwest Using Conservation Tillage. Univ. Idaho Agric. Econ. Ext. (accessed 4.1.17). https://www.reacchpna.org/farm-enterprise-budgets. Painter, K., 2015. 2015 Enterprise Budgets : District 1 Grass Hay.2015 Enterprise Budgets : District 1 Grass Hay. Painter, K., 2011. Costs of Owning and Operating Farm Machinery in the Pacific Northwest : 2011. Pacific Northwest Ext. Painter, K., 1991. Does sustainable farming pay: a case study. J. Sustain. Agric. 1, 37–48. Painter, K.M., Young, D.L., Granastein, D.M., Mulla, D.J., 1993. Prospects for alternative cropping systems in the Palouse. In: Center for Sustaining Agriculture and Natural Resources Conference. Washington State University. Patterson, P.E., Painter, K.M., 2014. Idaho Crop Input Price Summary for 2014. Univ. Idaho Agric. Econ. Ext. Series No. 14-04. Patterson, P.E., Painter, K.M., 2013. 2013 Crop Input Cost Summary. Univ. Idaho Agric. Econ. Ext. Series No. 13-03. Patterson, P.E., Painter, K.M., 2012. Idaho Crop Input Price Summary for 2012. Univ. Idaho Agric. Econ. Ext. Series No. 12-02. Patterson, P.E., Painter, K.M., Ruhoff, N., Eborn, B., 2015. Idaho Crop Input Price Summary for 2015. Univ. Idaho Agric. Econ. Ext. Series No. 15-05. Raiesi, F., Beheshti, A., 2014. Soil C turnover, microbial biomass and respiration, and enzymatic activities following rangeland conversion to wheat-alfalfa cropping in a semi-arid climate. Environ. Earth Sci. 72, 5073–5088. https://doi.org/10.1007/ s12665-014-3376-5. Reganold, J.P., 2013. Comparing organic and conventional farming systems: metrics and research approaches. Crop Manag. https://doi.org/10.1094/CM-2013-0429-01-RS. https://doi.org/10.1094/CM-2013-0429-01-RS.Abstract. Reganold, J.P., Jackson-Smith, D., Batie, S.S., Harwood, R.R., Kornegay, J.L., Bucks, D., Flora, C.B., Hanson, J.C., Jury, W.A., Meyer, D., Schumacher, J.A., Sehmsdorf, H., Shennan, C., Thrupp, L.A., WIllis, P., 2011. Transforming U.S. Agriculture. Science 332, 670–671. Reganold, J.P., Wachter, J.M., 2016. Organic agriculture in the twenty-first century. Nat. Plants 2, 15221. https://doi.org/10.1038/NPLANTS.2015.221. Römkens, P.F.A.M., van der Plicht, J., Hassink, J., 1999. Soil organic matter dynamics after the conversion of arable land to pasture. Biol. Fertil. Soils 28, 277–284. https:// doi.org/10.1007/s003740050494. Russelle, M.P., Entz, M.H., Franzluebbers, A.J., 2007. Reconsidering integrated crop-livestock systems in North America. Agron. J. 99, 325–334. https://doi.org/10.2134/ agronj2006.0139. Sanderson, M., Archer, D., Hendrickson, J., Kronberg, S., Liebig, M., Nichols, K., Schmer, M., Tanaka, D., Aguilar, J., 2013. Diversification and ecosystem services for conservation agriculture: outcomes from pastures and integrated crop-livestock systems. Renew. Agric. Food Syst. 28, 129–144. https://doi.org/10.1017/ S1742170512000312. Schillinger, W.F., Papendick, R.I., McCool, D.K., 2010. Soil and Water Challenges for Pacific Northwest Agriculture, in: Soil and Water Conservation Advances in the United States. pp. 47–80. Stark, C., Condron, L.M., Stewart, A., Di, H.J., O’Callaghan, M., 2006. Effects of past and current management practices on crop yield and nitrogen leaching—a comparison of organic and conventional cropping systems. New Zeal. J. Crop Hortic. Sci. 34, 207–215. Su, Y.Z., 2007. Soil carbon and nitrogen sequestration following the conversion of cropland to alfalfa forage land in northwest China. Soil Tillage Res. 92, 181–189. https://doi.org/10.1016/j.still.2006.03.001. Sulc, R.M., Tracy, B.F., 2007. Integrated crop-livestock systems in the U.S. Corn belt. Agron. J. 99, 335–345. https://doi.org/10.2134/agronj2006.0086.

2134/agronj2004.1288. Dodor, D.E., Tabatabai, M.A., 2003. Effect of cropping systems phosphatases in soils. J. Plant Nutr. Soil Sci. 166, 7–13. https://doi.org/10.1007/s003740050647. Drinkwater, L.E., Snapp, S.S., 2007. Nutrients in agroecosystems: rethinking the management paradigm. Adv. Agron. 92, 163–186. https://doi.org/10.1016/S00652113(04)92003-2. Duffin, A.P., 2007. Plowed Under: Agriculture and Environment in the Palouse. University of Washington Press, Seattle, WA. Ellert, B.H., Janzen, H.H., McConkey, B.G., 2001. Measuring and comparing soil carbon storage. In: Lal, R., Kimble, J.M., Follett, R.F., Stewart, B.A. (Eds.), Assessment Methods for Soil Carbon. CRC Press, Boca Raton, FL, pp. 131–146. Entz, M.H., Baron, V.S., Carr, P.M., Meyer, D.W., Smith, S.R., Mccaughey, W.P., 2002. Potential of forages to diversify cropping systems in the northern Great Plains. Agron. J. 94, 240–250. Fließbach, A., Oberholzer, H.-R., Gunst, L., Mader, P., 2007. Soil organic matter and biological soil quality indicators after 21 years of organic and conventional farming. Agric. Ecosyst. Environ. 118, 273–284. https://doi.org/10.1016/j.agee.2006.05.022. Foley, Ja., Ramankutty, N., Brauman, Ka., Cassidy, E.S., Gerber, J.S., Johnston, M., Mueller, N.D., Connell, C.O., Ray, D.K., West, P.C., Balzer, C., Bennett, E.M., Sheehan, J., Siebert, S., Carpenter, S.R., Hill, J., Monfreda, C., Polasky, S., Rockstro, J., Tilman, D., Zaks, D.P.M., O’Connell, C., Ray, D.K., West, P.C., Balzer, C., Bennett, E.M., Carpenter, S.R., Hill, J., Monfreda, C., Polasky, S., Rockström, J., Sheehan, J., Siebert, S., Tilman, D., Zaks, D.P.M., 2011. Solutions for a cultivated planet. Nature 478, 337–342. https://doi.org/10.1038/nature10452. Franzluebbers, A.J., 2007. Integrated crop-livestock systems in the southeastern USA. Agron. J. 99, 361–372. https://doi.org/10.2134/agronj2006.0076. Franzluebbers, A.J., Stuedemann, J.A., 2008. Early response of soil organic fractions to tillage and integrated crop-livestock production. Soil Sci. Soc. Am. J. 72, 613–625. https://doi.org/10.2136/sssaj2007.0121. Franzluebbers, A.J., Stuedemann, J.A., 2009. Soil-profile organic carbon and total nitrogen during 12 years of pasture management in the Southern Piedmont USA. Agric. Ecosyst. Environ. 129, 28–36. https://doi.org/10.1016/j.agee.2008.06.013. Fuerst, E.P., Koenig, R.T., Kugler, J., Painter, K., Stannard, M., Goldberger, J., 2009. Organic Alfalfa Management Guide. Washington State University Extension EB2039E, EB2039E. Gallagher, R.S., Pittmann, D., Snyder, A.M., Koenig, R.T., Fuerst, E.P., Burke, I.C., Hoagland, L., 2010. Alternative strategies for transitioning to organic production in direct-seeded grain systems in Eastern Washington I: crop agronomy. J. Sustain. Agric. 34, 483–503. https://doi.org/10.1080/10440046.2010.484680. Gattinger, A., Muller, A., Haeni, M., Skinner, C., Fliessbach, A., Buchmann, N., Mäder, P., Stolze, M., Smith, P., Scialabba, N.E.-H., Niggli, U., 2012. Enhanced top soil carbon stocks under organic farming. Proc. Natl. Acad. Sci. U. S. A. 109, 18226–18231. https://doi.org/10.1073/pnas.1209429109. Gentile, R.M., Martino, D.L., Entz, M.H., 2005. Influence of perennial forages on subsoil organic carbon in a long-term rotation study in Uruguay. Agric. Ecosyst. Environ. 105, 419–423. https://doi.org/10.1016/j.agee.2004.05.002. Gomiero, T., Pimentel, D., Paoletti, M.G., 2011. Environmental Impact of Different Agricultural Management Practices: Conventional vs. Organic Agriculture. Crit. Rev. Plant Sci. 30, 95–124. https://doi.org/10.1080/07352689.2011.554355. Guan, X.K., Turner, N.C., Song, L., Gu, Y.J., Wang, T.C., Li, F.M., 2016. Soil carbon sequestration by three perennial legume pastures is greater in deeper soil layers than in the surface soil. Biogeosciences 13, 527–534. https://doi.org/10.5194/bg-13-5272016. Hall, M., Young, D.L., Walker, D.J., 1999. Agriculture in the Palouse: a Portrait of Diversity. University of Idaho Extension, Moscow ID BUL 794. Hardesty, L.H., Tiedeman, J.A., 1996. Integrating crop and livestock production in Inland Northwest farming systems. Am. J. Altern. Agric. 11, 121–126. Hatfield, P.G., Blodgett, S.L., Spezzano, T.M., Goosey, H.B., Lenssen, A.W., Kott, R.W., Marlow, C.B., 2007a. Incorporating sheep into dryland grain production systems I: impact on over-wintering larva populations of wheat stem sawfly, Cephus cinctus Norton (Hymenoptera: cephidae). Small Rumin. Res. 67, 209–215. https://doi.org/ 10.1016/j.smallrumres.2005.10.002. Hatfield, P.G., Lenssen, A.W., Spezzano, T.M., Blodgett, S.L., Goosey, H.B., Kott, R.W., Marlow, C.B., 2007b. Incorporating sheep into dryland grain production systems II: impact on changes in biomass and weed density. Small Rumin. Res. 67, 216–221. https://doi.org/10.1016/j.smallrumres.2005.10.004. Helmers, G.A., Yamoah, C.F., Varvel, G.E., 2001. Separating the impacts of crop diversification and rotations on risk. Agron. J. 93, 1337–1340. Helyar, K.R., Porter, W.M., 1989. Soil acidification, its measurement, and the processes involved. In: Robson, A.D. (Ed.), Soil Acidity and Plant Growth. Academic Press, Australia, Marrickwillve, NSW, pp. 61–102. Jeranyama, P., Garcia, A.D., 2004. Understanding Relative Feed Value (RFV) and Relative Forage Quality (RFQ). South Dakota State Univ. Coop. Ext. Serv. ExEx8149. Joner, E.J., van Aarle, I.M., Vosatka, M., 2000. Phosphatase activity of extra-radical arbuscular mycorrhizal hyphae: a review. Plant Soil 226, 199–210. King, A.E., Blesh, J., 2017. Crop rotations for increased soil carbon: perenniality as a guiding principle. Ecol. Appl. 28, 249–261. https://doi.org/10.1002/eap.1648. Kirby, E., Granatstein, D., 2018. Certified Organic Acreage and Sales in Washington State: 2009–2017. Organic Trends Series, Center for Sustaining Agriculture and Natural Resources. Washington State University, Wenatchee, WA. Kirby, E., Pan, W., Huggins, D., Painter, K., Bista, P., 2017. Rotational Diversification and Intensification, in: Advances in Dryland Farming in the Inland Pacific Northwest. Koenig, R., 2005. Eastern Washington Nutrient Management Guide: Dryland Winter Wheat. Washington State University Extension No. EB1987. Kravchenko, A.N., Snapp, S.S., Robertson, G.P., 2017. Field-scale experiments reveal persistent yield gaps in low-input and organic cropping systems. Proc. Natl. Acad. Sci.

11

Agriculture, Ecosystems and Environment 286 (2019) 106665

J.M. Wachter, et al.

Vogel, K.P., Pedersen, J.F., Masterson, S.D., Toy, J.J., 1999. Evaluation of a filter bag system for NDF, ADF, and IVDMD forage analysis. Crop Sci. 39, 276–279. https://doi. org/10.2135/cropsci1999.0011183X003900010042x. Voroney, R.P., Brookes, P.C., Beyaert, R.P., 2008. Soil microbial biomass C, N, P, and S. In: Carter, M.R., Gregorich, E.G. (Eds.), Soil Sampling and Methods of Analysis. CRC Press, Boca Raton, FL, pp. 639–642. Wang, Z., Goonewardene, L.A., 2004. The use of MIXED models in the analysis of animal experiments with repeated measures data. Can. J. Anim. Sci. 84, 1–11. https://doi. org/10.4141/A03-123. Yost, M.A., Russelle, M.P., Coulter, J.A., 2014. Field-specific fertilizer nitrogen requirements for first-year corn following alfalfa. Agron. J. 106, 645–658. https://doi.org/ 10.2134/agronj2013.0416. Young, D.L., Kwon, T.J., Young, F.L., 2004. Downsizing an agricultural field experiment alters economic results: a case study. Rev. Agric. Econ. 26, 255–265. https://doi.org/ 10.1111/j.1467-9353.2004.00174.x.

Tabatabai, M.A., 1994. Soil Enzymes, in: Methods of Soil Analysis: Part 2—Microbiological and Biochemical Properties, SSSA Book Series SV - 5.2. Soil Science Society of America, Madison, WI, pp. 775–833. https://doi.org/10.2136/ sssabookser5.2.c37. Thiessen Martens, J., Entz, M., Wonneck, M., 2015. Redesigning Canadian prairie cropping systems for profitability, sustainability, and resilience: a review. Can. J. Plant Sci. 645–648. https://doi.org/10.4141/CJPS-2014-173. Thomas, G.W., 1996. Soil pH and Soil Acidity, in: Methods of Soil Analysis Part 3—Chemical Methods, SSSA Book Series SV - 5.3. Soil Science Society of America, American Society of Agronomy, Madison, WI, pp. 475–490. https://doi.org/10.2136/ sssabookser5.3.c16. Tilman, D., Cassman, K.G., Matson, P.A., Naylor, R., Polasky, S., 2002. Agricultural sustainability and intensive production practices. Nature 418, 671–677. https://doi.org/ 10.1038/nature01014. USDA National Agricultural Statistics Service, 2018. USDA Quick Stats. USDA-NASS, Washington, DC. Available at https://www.nass.usda.gov/ (Accessed 1 May 2019).

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