Winter legume-rice rotations can reduce nitrogen pollution and carbon footprint while maintaining net ecosystem economic benefits

Accepted Manuscript Winter legume-rice rotations can reduce nitrogen pollution and carbon footprint while maintaining net ecosystem economic benefits Siyuan Cai, Cameron M. Pittelkow, Xu Zhao, Shenqiang Wang PII:

S0959-6526(18)31451-3

DOI:

10.1016/j.jclepro.2018.05.115

Reference:

JCLP 12972

To appear in:

Journal of Cleaner Production

Received Date: 27 March 2018 Revised Date:

14 May 2018

Accepted Date: 15 May 2018

Please cite this article as: Cai S, Pittelkow CM, Zhao X, Wang S, Winter legume-rice rotations can reduce nitrogen pollution and carbon footprint while maintaining net ecosystem economic benefits, Journal of Cleaner Production (2018), doi: 10.1016/j.jclepro.2018.05.115. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT Target Journal: Journal of Cleaner Production

Winter legume-rice rotations can reduce nitrogen pollution and carbon footprint

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while maintaining net ecosystem economic benefits

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Authors: Siyuan Cai1, 2, Cameron M. Pittelkow3, Xu Zhao1, Shenqiang Wang1

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Affiliations: 1State Key Laboratory of Soil and Sustainable Agriculture, Changshu National Agro-Ecosystem Observation and Research Station, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China

University of Chinese Academy of Sciences, Beijing 100049, China

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Department of Crop Sciences, University of Illinois, Urbana, IL 61801, US

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Corresponding author: X. Zhao(
). E-mail: [email protected]. Phone: 86–25–

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86881534, Fax: 86–25– 86881028

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Graphical abstract

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Abstract Achieving reductions in nitrogen (N) losses and carbon (C) emissions without

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enduring a yield penalty is an environmental and economic challenge in sustainable

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rice production. The use of legumes as a winter crop in rice rotations may provide

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environmental benefits by reducing synthetic N inputs, yet few studies have integrated

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long-term field measurements of cropping system N and C dynamics with life cycle

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assessment (LCA) and net ecosystem economic benefits (NEEB) to determine

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whether legumes can improve environmental performance while minimizing tradeoffs

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related to yields and economic returns. We evaluated four contrasting rice cropping

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rotations (Rice-wheat (R-W); rice-rape (R-Ra); rice-fava bean (R-F); and, rice-milk

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vetch (R-M)) over six years to determine N input and output balances, methane (CH4)

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emissions, and soil C changes. These field observations were then incorporated into

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LCA and NEEB to estimate C footprint, economic and environmental benefits.

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Results showed that R-F and R-M maintained rice yield but reduced annual synthetic

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N inputs by 50-63% compared with the conventional R-W and R-Ra rotations,

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leading to consistent reductions in reactive N losses (ammonia (NH3) volatilization:

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39-48%; N runoff: 66-82%; N leaching: 14-34%; and nitrous oxide (N2O) emissions:

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40-64%). The estimated C footprint was 37-50% lower in R-F and R-M than R-W and

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R-Ra, largely owing to reduced fertilizer use which decreased direct soil N2O

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emissions as well as indirect emissions relating to reactive N losses. In contrast to N

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losses, there were no significant differences in CH4 emissions or soil C changes

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among rotations. When changes in N pollution and C footprint were accounted for in

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ACCEPTED MANUSCRIPT the economic assessment, R-F resulted in NEEB values similar to R-W, while

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substituting milk vetch as a winter crop reduced NEEB by 6-37%. In the first two

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study years before grain legume yields declined, NEEB for R-F was 38% greater than

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R-W, highlighting the potential for simultaneous environmental and economic

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benefits. This study demonstrated the potential of mixed winter grain/forage

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legumes-rice crop rotations to consistently reduce N pollution and C footprint while

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maintaining NEEB based on economic and environmental benefits.

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Key words: rice-legume rotation; N pollution; N2O emissions; C footprint; net

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environmental economic benefits; life cycle analysis

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Introduction Farmland is a major contributor to global climate change, accounting for 52% and 84% of global anthropogenic emissions of methane (CH4), and nitrous oxide

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(N2O), respectively, with losses in reactive N via waterborne and airborne nitrogen (N)

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flows that amount to 32-45 and 26-60 Tg N yr-1, respectively (Smil, 1999; Smith et al.,

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2008). Rice is a staple food in many regions providing 50% of dietary caloric intake

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and representing 22% of global cereal harvested area (FAO, 2015). To meet the food

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demands of an expanding world population, rice yields have increased over the last

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three decades, due in part to the intensive use of synthetic fertilizers (Hossain and

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Singh, 2000). The overuse of N fertilizer in rice paddy fields has led to GHG

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emissions and non-point source pollution (Choudhury and Kennedy, 2005; Linquist et

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al., 2012). Minimizing GHG emissions in rice is difficult due to a trade-off between

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CH4 and N2O emissions (Hou et al., 2000), where emissions of one GHG tend to

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increase with the implementation of management practices designed to reduce

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emissions of the other.

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In Asia, conventional rice-wheat cropping systems dominate agricultural land,

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occupying 24 million ha in South Asia and China (Ladha et al., 2003) and providing

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food security for more than 400 million people. Under this cropping system, rice is

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generally grown in the rainy season of the summer months, followed by wheat

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cultivation in the winter months. However, wheat yields are significantly lower in

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many rice-based cropping regions than in wheat-based systems (Ladha et al., 2000).

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For example, wheat yields in the Taihu Lake Plain, a typical rice-wheat cropping

ACCEPTED MANUSCRIPT region in China, are usually below 5.0 t ha-1, far lower than that in the main wheat

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producing area of the North China Plain (commonly above 6.0 t ha-1) (Zhu and Zhang,

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2010). Lower yields are possibly due to soil compaction caused by land preparation;

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flooding of the preceding rice crop and waterlogging resulting from disproportional

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winter rainfall in the subtropical monsoon climate (Dickin and Wright, 2008; Sharma

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et al., 2003). The efficiency and environmental sustainability of wheat production in

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the rice-wheat system is further compromised by the impact of intensive inputs of

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chemical N fertilizer during wheat cultivation, where losses of NH3, denitrification,

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and N runoff and leaching of total N input have been estimated at 20%, 10% and 20%,

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respectively (Zhao et al., 2012).

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Efforts to reduce the environmental impacts of rice-based cropping systems include improved tillage practices, development of crop genotypes with higher

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nutrient use efficiency, more effective water management, and diversified crop

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rotations (Smith et al., 2008). Farming systems that reduce reliance on external inputs

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like synthetic fertilizers have been suggested by IPCC (2007) to mitigate GHG

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emissions. Historically, leguminous crops were an integral component of arable

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systems, including rice rotations, but their use during the 20th century declined with

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the adoption of synthetic N fertilizers (Crews and Peoples, 2004) despite their value in

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biological N-fixation (Vance et al., 2000). A lack of improvement in legume yields

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compared with cereals has also limited legume cultivation (Graham and Vance, 2003).

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However, current challenges of agricultural practices are not only to fulfill food

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supply but also to increase the sustainability of agriculture (Tilman et al., 2002), thus

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highlighting the potential environmental benefits of integrating legumes into cereal

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crop rotations.

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Previous work indicates the use of leguminous crops with associated reductions in N fertilizer use within rice crop rotations could lower reactive N losses and GHG

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emissions. Xia et al. (2016) found that legumes substituted for winter wheat reduced

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greenhouse gas intensity by 11-41%, while Zhao et al. (2015a) showed that

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legume-rice rotations decreased reactive N losses by roughly half compared with a

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rice-wheat rotation. However a better understanding of the effects of legumes in a rice

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rotation on the mitigation of C emissions and N losses is needed to develop strategies

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for minimizing potential tradeoffs between environmental and economic outcomes.

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Indeed, despite the potential environmental benefits, encouraging farmers to increase

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the cultivation of legumes also requires economic evidence. Economic assessments

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that are based not only on grain yield revenues and costs of production, but assign an

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economic value to the environmental and social benefits of agricultural practices are

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increasingly valuable tools (Ness et al., 2007). However, few economic assessments

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on legume-rice rotations have taken into consideration environmental benefits

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(Mucheru-Muna et al., 2010; Pimentel et al., 2005), for instance, the potential for

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reductions in reactive N losses and C footprint.

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The sustainability of a production system and field management activities may

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be assessed using LCA where GHG emissions are quantified as CO2 equivalents

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(CO2-eq) to determine a total C footprint (IPCC, 2006). At the same time, the

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estimation of NEEB allows calculating the balance of economic benefits of grain

ACCEPTED MANUSCRIPT yield revenue with input costs and carbon and environmental costs related to C

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emissions and N losses, respectively (Li et al., 2015). Here, we combined the

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approaches of 1) long-term field measurements of cropping systems N and C

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dynamics with LCA to quantify the C footprint and 2) NEEB to quantify the holistic

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economic benefits of rice-legume rotations in comparison to conventional rice-wheat

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or rice-rape rotations in the Taihu Lake Region in southeastern China. Our objectives

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were to 1) investigate the long-term effects of growing winter legumes on crop yields,

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GHG emissions, NH3 volatilization, and N leaching and runoff; 2) evaluate C

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footprint using LCA and reactive N losses by long-term field measurements; and 3)

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assess the environmental economic benefits of rice-legume rotations using NEEB.

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The data from this study provide important insights into the economic feasibility of

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replacing conventional rotations with rice-legume rotations while also considering

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potential environmental benefits.

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2 Materials and methods

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2.1 Site description

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The study was conducted between 2011 and 2016 at the Yixing Base for

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Non-point Source Pollution Control, Changshu National Agro-Ecosystem Observation

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and Research Station, Chinese Academy of Sciences (Fig. 1a). The climate is humid

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subtropical monsoon with an average temperature of 15.7 °C and annual rainfall of

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1226 mm, with 886 mm of rainfall occurring during the summer rice growth period.

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The predominant soil type is a Gleyi-Stagnic Anthrosols derived from lacustrine

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experiment were 7% sand, 76% silt, and 17% clay; 15.4 g kg-1 organic C; 1.79 g kg-1

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total N; 11.8 cmol kg-1 cation exchange capacity; and 5.6 pH (H2O). Further details on

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the experimental site are reported by Zhao et al. (2015a).

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2.2 Experimental design

Four rice crop rotations were assigned to adjoining fields. Rotations included rice

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(Oryza sativa L.) -wheat (Triticum aestivum L.) (R-W), rice-rape (Brassica napus)

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(R-Ra), rice-milk vetch (Astragalus sinicus L.) (R-M), and rice-fava bean (Vicia faba

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L.) (R-F) (Fig. 1b-c). The crops were cultivated and monitored for 6 consecutive

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years.

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The rice season ran from mid-June until mid-October each year. Irrigation

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management practices for rice included midseason aeration lasting for about 10 days

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after 1 month of continuous flooding. The water depth at flooding stage was

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maintained at 3-5 cm and drainage ditches were opened during winter crop cultivation

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to reduce waterlogging. For nutrient management, fertilizer was applied to rice as urea

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according to local practices at a rate of 240 kg N ha-1 for R-W and R-Ra. For rice that

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followed milk vetch or fava bean, urea-N rate was adjusted each season based on the

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amount of organic N inputs supplied to the field in the form of chopped biomass of

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the preceding winter legume crop that was incorporated into soil to reach total N

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application rate of 240 kg N ha-1 (Fig. S1). Winter wheat and rape were fertilized with

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urea at a rate of 200 kg N ha-1, whereas milk vetch and fava bean received no N

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ACCEPTED MANUSCRIPT fertilizer. Urea was applied in three doses to rice, wheat, and rape as basal fertilizer

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(30%), top-dressing at tillering (40%), and top-dressing at panicle or bud formation

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(30%). Fertilizer P and K were applied once each season to each rotation as a base

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fertilizer at 60 kg P2O5 ha-1 and 45 kg K2O ha-1. Rice was transplanted to the fields in

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mid-June at a rate of 105 kg ha-1. At the end of October, fava bean seeds were placed

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in 20-cm deep planting holes at a rate of 263 kg ha-1, while milk vetch, rape and

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wheat were directly drilled at 75, 65, and 150 kg ha-1.

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2.3 Monitoring and analysis

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Reactive N losses were measured over 12 growing seasons following the methods described in detail in Appendix A, Supplementary Information. In brief, three

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observation sites within each cropping system were treated as pseudo-replicates for

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monitoring N losses (Fig. 1b). Monitoring of soil GHG emissions included CH4 (only

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from 2012-2016) and N2O emissions. Monitoring of reactive N loss pathways

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included NH3 volatilization, N leaching and N runoff. The closed-chamber method

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was used to measured N2O and CH4 emissions (Terry et al., 1981; Appendix A).

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Cumulative seasonal emissions of CH4 or N2O during the whole growing seasons

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were computed as:

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CE = ∑ (Fi + Fi+1) / 2 × t × 24

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where CE is the cumulative emissions (mg C m-2 for CH4 or µg N m-2 for N2O), then

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the unit for GHG emissions were converted to kg C or N ha-1 by multiply 10-2 for CH4

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or 10-5 for N2O; Fi and Fi+1 are the measured fluxes of two consecutive sampling days

(1)

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(mg C m-2 h-1 for CH4 and µg N m-2 h-1 for N2O); and t is the number of days between

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two consecutive sampling days (d).

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NH3 volatilization rate was measured using a continuous air flow enclosure method as described in Zhao et al. (2015a; Appendix A). Daily cumulative NH3

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volatilization fluxes were calculated by multiplying the cumulative NH3 volatilization

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fluxes in morning and afternoon by six. Total NH3 volatilization fluxes were

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calculated as:

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NV = ∑ Vi × ρ × 14 × 6 / (0.0314 × 100)

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where NV is the cumulative NH3 volatilization rate (kg N ha-1); Vi is the titrating acid

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volume (ml); ρ is the concentration of standard sulfuric acid (mol L-1); 0.0314 is the

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area of the chamber (m2); 14 is the N molecular weight (g mol-1); and, 100 is

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conversion coefficient of mg m-2 to kg ha-1.

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N leaching estimation followed the method described by Zhao et al. (2015a; Appendix A). Cumulative N leaching was calculated as:

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NL = ∑ Ci × Vi / (A × 100)

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where NL is the cumulative N leaching loss (kg N ha-1); Ci is the time interval weight

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N concentration (mg L-1), calculated as individual N concentration (mg N L−1) ×

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intervals between two adjacent samplings (d) / total growth time (d); Vi is the total

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leaching volume (L; based on methods in appendix A); A is the area of the field (m2);

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and, 100 is conversion coefficient of mg m-2 to kg ha-1.

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Water volume of individual irrigation and runoff events in each field was

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measured using two electromagnetic flow meters (LDBP-150L-M2X2-200, Yixing

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ACCEPTED MANUSCRIPT Xiangming Instrument Co.) installed in the irrigation inlet and drainage outlet

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(Fig.1b). Water samples were collected in 250 ml clean plastic bottles and

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immediately taken to the laboratory for analysis. Runoff N loss or irrigation N input

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was calculated as:

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NR = ∑ Ci ×Vi / (A × 100)

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where NR is the cumulative N runoff loss or irrigation N input (kg N ha-1); Ci is the N

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concentration (mg L-1); Vi is the individual runoff or irrigation volume (L); A is the

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area of the field (m2); and, 100 is conversion coefficient of mg m-2 to kg ha-1.

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Atmospheric N deposition was collected by method described in Appendix A.

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Crop plants from each field were manually harvest and divided into grain and

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straw fractions for yield analysis. Plant samples from three 0.5-m2 subplots in each

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field were evenly taken to laboratory and oven dried at temperature of 80 °C to a

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constant weight. Total N concentration was determined using the Kjeldahl method and

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total N uptake was calculated as the sum yield per unit area multiplied by the

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corresponding N concentration. Following harvest, composite soil samples at 0-15 cm

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depth were randomly collected from each field using a 5 cm diameter stainless steel

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auger. Samples were air-dried and subsamples were ground and passed through a 0.15

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mm sieve. Analysis of soil organic carbon (SOC) was performed following the

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Walkley-Black procedure (Schumacher, 2002) and soil total N using the Kjeldahl

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method. Soil bulk density (BD) was determined using a 100 cm-3 copper cylinder. The

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concentration of SOC (g kg -1) was converted to mass to determine the soil organic

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carbon pool (SCP) (kg C ha -1) using the equal depth method (Zhang et al., 2016):

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SCP = SOC × BD × 0.15 × 10,000

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where 0.15 is the thickness of the soil sampling layer (m) and 10,000 is the conversion coefficient from kg m-2 to kg ha-1.

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2.4 Estimate of C footprint and N input/output budget

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The LCA approach described by Hillier et al. (2009) was used to estimate the C footprint of the different rotations (Fig. 2). The following emission categories were

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included: direct soil N2O and CH4 emissions and indirect GHG emissions via NH3

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volatilization, N leaching and runoff; emissions resulting from farm management

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activities (plowing, seedling transplantation, fertilizer and pesticide application,

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irrigation, and harvest); the production, storage, and transportation of agricultural

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inputs; straw burning (Table S1); and SOC storage. Indirect emissions of N2O from

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leaching, runoff and NH3 volatilization were estimated as:

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N2Oindirect = EFleaching × (TNleaching + TNrunoff) + EFNH3 × NH3-N

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where EFleaching is the N2O emission factor for total N from leaching and runoff

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(EFleaching = 0.0075 kg N2O-N kg-1 N); TNleaching and TNrunoff are measured values of

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total N leaching and runoff as described above; and EFNH3 is the N2O emission factor

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for NH3-N (EFNH3 = 0.01kg N2O-N kg-1 N) (Table S1).

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The difference between final and initial SCP indicates the potential storage or

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emissions of CO2 due to changes in soil C stock in the topsoil. Changes in SCP were

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converted to atmospheric CO2 as:

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∆SCP = (SCP2016 – SCP2011) / 6 × 44 / 12

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where ∆SCP is the annual change in SCP in the topsoil from 2011 to 2016 (kg CO2-eq

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ha-1 yr-1); SCP2016 and SCP2011 are the SOC storage of the topsoil in 2011 and 2016

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(kg C ha-1); 6 is the study period (years); 44/12 is the conversion coefficient of C into

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CO2-eq.

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Both the product carbon footprint (PCF) and the farm carbon footprint (FCF)

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were calculated using the equations described by Xu and Lan (2017):

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FCF = ∑Ai × EFi - ∆SCP

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PCF = ∑(Ai × EFi - ∆SCP) / Y

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where FCF is the C footprint per unit area (kg CO2-eq ha-1 yr-1) and PCF is the C

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footprint per unit yield (kg CO2-eq kg-1 yr-1); Ai is the agricultural inputs shown in

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Table S1; EFi is the emission factor shown in Table S1; Y is the annual grain yield of

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summer rice (kg ha-1 yr-1); and, ∆SCP is the annual change in SCP (kg CO2-eq ha-1

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yr-1).

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To calculate field N inputs/outputs, we used the soil system budget approach

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described by Oenema et al. (2003). Inputs included anthropogenic and natural reactive

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N inputs (i.e., chemical N fertilizer, biological N fixation, atmospheric N deposition,

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N in irrigation water, and seed N). Outputs included crop N uptake, NH3 volatilization,

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runoff, leaching, and N2O emissions. Previous data of shoot N derived from

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atmosphere (%Ndfa) were averaged to estimate N inputs via biological N fixation

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(Table S2). As there is no proper method for monitoring in-situ soil denitrification rate,

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reactive N losses due to denitrification were not included in our study.

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2.5 Net ecosystem economic benefits

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Calculation of NEEB was used to evaluate the net social benefits of the different rotations (Fig. 2). We widened the application of this concept by also including CO2

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emissions and reactive N losses separately as additional ecosystem services and social

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costs. Hereafter, environmental costs refer to reactive N losses while carbon costs

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refer to C footprint. NEEB was calculated as:

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NEEB = grain yield revenue – agricultural costs – carbon costs – environmental costs

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(10)

where grain yield revenue was calculated from current grain prices for rice, wheat,

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rape, and fava bean of 3.1, 1.9, 2, and 10 CNY kg-1, respectively

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(http://www.grain.gov.cn). Agricultural costs included mechanical tillage (2400 CNY

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ha-1 yr-1), pesticides and herbicides (2250 CNY ha-1 yr-1), mechanical harvesting

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(2400 CNY ha-1 yr-1), fertilizer (2.5 CNY kg-1), and crop seeds (rice: 1680 CNY ha-1

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yr-1; wheat: 960 CNY ha-1 yr-1; rape: 1040 CNY ha-1 yr-1; fava bean: 866.25 CNY ha-1

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yr-1; and, milk vetch: 1500 CNY ha-1 yr-1) (Zhang et al., 2015). Carbon costs were

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calculated as C footprint × the carbon trade price [35 € (272.8 CNY) t-1 CO2-eq]

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(Melaku Canu et al., 2015). Environmental costs relating to reactive N losses included

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the estimated costs of acidification (84% × 1.88 × NH3 (kg N ha-1) × 5.0 (CNY kg-1)

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×17/14) plus eutrophication ((42% ×(NO3-Nrunoff + NO3-Nleaching (kg N ha-1)) × 62/14

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+ 33% × NH3-NNH3 + NH3-Nrunoff + NH3-Nleaching (kg N ha-1)) × 17/14) × 4.26 (CNY

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kg-1); Xia and Yan, 2012).

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2.6 Statistical analysis

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Data were present as means of the sub-samples triplicates or six yearly replicates. To evaluate the effects of rotation on cumulative N leaching and runoff loss,

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cumulative N2O and CH4 emissions, NH3 volatilization, grain yield, soil properties, N

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balances, C footprint, and NEEB, we performed one-way ANOVAs. Treatment means

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were separated according to the least significant difference test (LSD) at P < 0.05.

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Analyses were computed in SPSS 17.0 (Chicago, IL, USA). Figures were prepared by

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Origin (Version 9.0, USA).

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Results

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3.1 Crops yields and chemical N input

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Rice crop yields did not vary among the four rotations (Fig. 3a). Yields ranged from 6.23-8.50 Mg ha-1 in R-W, 6.30-8.92 Mg ha-1 in R-Ra, 6.42-9.83 Mg ha-1 in R-F

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and 6.70-9.83 Mg ha-1 in R-M, averaging 7.59-7.88 Mg ha-1 among rotations. Yields

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of the winter crops varied among the rotations, where yields were 3.03-6.27 Mg ha-1

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for wheat, 0.87 -1.69 Mg ha-1 for rape, <1.00-1.84 Mg ha-1 for fava bean, and 1.09 to

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4.63 Mg ha-1 dry matter of milk vetch as green manure (Fig. 3b). Grain yields of

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wheat, rape and fava bean under R-W, R-Ra and R-F averaged 4.74, 1.21 and 0.53 Mg

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ha-1, respectively (Fig. 3b).

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In R-W and R-Ra, 240 kg N ha-1 and 200 kg N ha-1 of N fertilizer were applied

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for each rice and winter crop season, respectively. In R-F, N contained in fava bean

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residues was 22.1-56.4 kg N ha-1 in the first three seasons and decreased to 4.48-14.8

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kg N ha-1 in the following three seasons (Fig. S1). Milk vetch as a green manure

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contributed 33.6-120 kg N ha-1. Combining inorganic and organic N sources, average

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annual chemical N input was significantly decreased to 218 and 164 kg N ha-1 for R-F

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and R-M, compared to 440 kg N ha-1 of total N input in R-W and R-Ra (Fig. S1).

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3.2 Direct N2O and CH4 emissions

Soil N2O emissions varied among rotations and years (Fig. S2), where rice

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seasons average N2O fluxes were 6.16-101 µg N m-2 h-1 and 2.84-85.2 µg N m-2 h-1 in

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R-W and R-Ra, respectively, and 3.02-88.7 µg N m-2 h-1 and 2.03-96.1 µg N m-2 h-1 in

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R-F and R-M, respectively (Table S3). In winter crops seasons average N2O fluxes

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were 14.6-125 µg N m-2 h-1 for R-W, 8.90-48.6 µg N m-2 h-1 for R-Ra, 4.19-8.89 µg N

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m-2 h-1 for R-F and 6.31-16.7 µg N m-2 h-1 for R-M, respectively (Table S3). Fluxes of

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N2O were much lower in the legume winter crops in contrast to conventional rotations

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including wheat and rape (Table S3). Winter cumulative N2O emissions were

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1.12-2.11 kg N ha-1 for R-W and R-Ra, while 0.36-0.51 kg N ha-1 for R-F and R-M,

312

respectively (Fig. 4a). There were no differences in cumulative N2O emissions among

313

cropping systems during rice, where emissions averaged 0.68-1.18 kg N ha-1 among

314

rotations (Fig. 4a).

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Soil CH4 emissions peaked at the beginning and middle of summer when fields

316

were flooded, after which they declined to almost zero during the winter (Fig. S2).

317

Fluxes of CH4 in the rice phase of conventional rotations were comparable among

318

rotations, Ranging from 1.13-25.3 mg C m-2 h-1 (Table S3). Fluxes of CH4 were

319

negligible in winter crops, with fluxes remaining lower than 0.5 mg C m-2 h-1 across

ACCEPTED MANUSCRIPT 320

rotations. Both during rice and the winter crops, cumulative CH4 emissions were

321

similar among rotations, averaging 104 to 186 kg C ha-1 in rice seasons and 3.00-3.81

322

kg C ha-1 in winter crops seasons, respectively (Fig. 4b).

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3.3 Reactive N losses

Over the twelve cropping seasons, NH3 volatilized from R-W and R-Ra varied

between the seasons, ranging from 23.3 to 77.2 and 25.5 to 73.4 kg N ha-1 in rice, and

327

2.87-3.97 and 3.61-6.09 kg N ha-1 in the winter crops, respectively (Fig. 4c). In

328

comparison, NH3 volatilization from rice in the R-F and R-M rotations was 18.8-44.6

329

and 16.2-41.1 kg N ha-1, respectively, decreasing to 0.93-1.98 and 0.76-2.25 kg N ha-1

330

from the fava bean and milk vetch in the winter. Average annual NH3 volatilization

331

from R-W and R-Ra were 39-40% higher (54.7 and 54.2 kg N ha-1, respectively) than

332

R-F and R-M rotations (33.3 and 28.6 kg N ha-1, respectively; Fig. 4c).

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The amount of runoff water varied between 281 and 1072 m3 ha-1 during the

334

winter crops, and was between 587 and 1709 m3 ha-1 during the rice seasons (Fig. S3).

335

While average TN concentrations in runoff water did not vary greatly in the rice

336

seasons among rotations (0.44-26.70 mg N L-1; Fig. S3), it differed among the winter

337

crops (wheat and rape: 0.14-69.3 mg N L-1; fava beans and milk vetch: 0.14-13.6 mg

338

N L-1; Fig. S3). The average annual N runoff varied among the rotations, where it was

339

reduced by 66-82% in the rice-legume rotations (R-F: 7.07 kg N ha-1; R-M: 5.98 kg N

340

ha-1) compared to the conventional rotations (R-W: 32.6 kg N ha-1; R-Ra: 20.5 kg N

341

ha-1, Figs 5a and b).

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The largest differences in N leaching occurred on a seasonal basis than in the four rotations (Fig. S4). While seasonal TN concentrations were generally higher in

344

wheat and rape than in fava bean and milk vetch, they did not vary significantly

345

among rotations (ranged 0.21-42.6 mg N L-1 in rice seasons and 1.00-72.3 mg N L-1 in

346

winter crops seasons; Fig. S4). In comparison to the winter crops, rice seasons

347

consistently had lower TN leaching concentrations and less variability, with seasonal

348

average values of 1.38-12.0 mg N L-1 in rice seasons and 1.61-19.3 mg N L-1 in winter

349

crops seasons(Table S4). Average N leaching across the rotations in the winter and

350

summer was 2.98-7.47 and 8.01-9.16 kg N ha-1, respectively (Figs 5c and d). With the

351

exception of leached NO3-, which was significantly lower from the winter legume

352

crops than wheat, there were no differences in N leaching among the four rotations

353

(Figs 5c and d).

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Based on the IPCC default emission factors of 0.0075 kg N2O-N kg-1 N for leaching and runoff and 0.01 kg N2O-N kg-1 N for volatilized NH3, average annual

356

indirect N2O emissions resulting from reactive N loss via volatilization, leaching and

357

runoff in R-W, R-Ra, R-F, and R-M were estimated to be 1.44, 1.25, 0.74, and 0.65 kg

358

N2O ha-1, respectively. Collectively, indirect emissions represented up to 22-26% of

359

total N2O emissions (Fig. 6).

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3.4 N input/output balance For N input/output balances, conventional rotations (R-W and R-Ra) were characterized by high N inputs and reactive N losses, whereas legume-based rotations

ACCEPTED MANUSCRIPT had lower N inputs and reactive N losses (Fig. S5). Synthetic and fixed N contributed

365

up to 78-87% of total N inputs in the rotations. Annual atmospheric TN inputs

366

averaged 64.7 kg N ha-1, representing 11-17% of total N inputs among rotations,

367

respectively (Appendix A and Fig. S5). Across all four rotations, irrigation N was

368

consistently less than 2% of total N inputs, averaging 6.73 kg N ha-1 yr-1. Removal of

369

N by harvesting was 21-44% lower in the legume-rice (149-170 kg N ha-1) than the

370

conventional (214-266 kg N ha-1) rotations (Fig. S5). NH3 volatilization was the

371

dominant reactive N loss pathway (represented 51-62% of total reactive N losses),

372

while sum of N leaching and runoff losses represented 38-46% and 35-36% of total

373

reactive N losses in the conventional and legume-based rotations, respectively. When

374

outputs were subtracted from inputs, surplus soil N balances occurred in all rotation

375

systems in the rank of R-Ra, R-W, R-M, and R-F (271, 202, 197, and 163 kg N ha-1

376

yr-1, respectively) without consideration of denitrification losses.

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The estimated FCF and PCF were comparable between R-W and R-Ra

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(11.2-13.1 Mg CO2-eq ha-1 yr-1 and 1.45-1.74 Mg CO2-eq Mg-1 yr-1, respectively).

381

However, FCF and PCF for R-W were significantly higher than R-F (98% and 93%

382

higher, respectively) and R-M (87% and 88% higher, respectively) (Fig. 6a). The

383

dominant source of FCF was CH4 emissions, accounting for 47-59% of FCF among

384

rotations, whereas N2O and fertilizer production contributed 8-12% and 26-31% of

385

CO2-eq, respectively. GHG emissions from electricity use in irrigation accounted for

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ACCEPTED MANUSCRIPT 6-11% of FCF among four fields. Indirect N2O emissions accounted for almost the

387

same proportion of FCF between rotations (3%), while it reduced by 41-55% in

388

rice-legume rotations contrasting to conventional rotations. By avoiding wheat straw

389

burning, the incorporation of legume residues reduced CO2-eq by 7% for R-F and

390

R-M, compared with R-W. The largest SCP occurred in R-F (1.62 Mg CO2-eq ha-1

391

yr-1), which was 54 %, 15 %, and 18% higher than in R-W, R-Ra, and R-M,

392

respectively, while no significant differences were found (Fig. 6b). The soil carbon

393

sink offset 7%, 10%, 11%, and 9% of total C emissions in R-W, R-Ra, R-F, and R-M

394

rotations, respectively.

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3.6 NEEB

The NEEB were comparable among rotations except for R-M (Fig. 7a). The

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highest grain yield revenue (32.8 × 103 CNY ha-1 yr-1) was for R-W, which was 22%

399

and 39% higher than R-Ra and R-M, respectively, and similar to R-F (28.9 × 103

400

CNY ha-1 yr-1) (Fig. 7b). Fertilizer costs in the legume rotations were 50-63% lower

401

than in the conventional cropping systems (Fig. 7b). Both the highest carbon costs and

402

environmental costs occurred in R-W (3.59 × 103 and 0.91 × 103 CNY ha-1 yr-1,

403

respectively), which were 87-98% and 98-126% higher than rice-legume rotations,

404

and similar to R-Ra (3.05 × 103 and 0.80 × 103 CNY ha-1 yr-1, respectively; Fig. 7b).

405

By combining carbon and environmental costs, rice-legume rotation offset grain yield

406

revenue penalty (comparing with R-W) by 24-56%.

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4.

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4.1 Effects of legumes on N losses and C footprint

410

Discussion

Rice-wheat cropping systems are characterized by high rates of reactive N losses and CO2 emissions due to the “high input-high loss-high pollution” management

412

approach (Zhao et al., 2012). Comprehensive comparisons of the environmental

413

performance of alternative rotations which also account for impacts on yield and

414

economic outcomes are needed to guide the development of sustainable rice

415

production systems in southeastern China. Our results provide strong evidence that

416

introducing legumes instead of winter wheat or rape is highly effective strategy for

417

reducing environmental risks but maintaining rice production based on 6 years of field

418

observations for reactive N losses, CH4 emissions and soil C pool changes, as well as

419

associated CO2-eq from fertilizer production, field management practices and indirect

420

N2O emission related to N losses. To our knowledge, multi-criteria assessments

421

combining comprehensive field measurements, LCA, and NEEB have not been

422

previously conducted for this study system.

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As documented in previous field research (Ju et al., 2009), high levels of N

424

inputs in R-W contributed to high levels of N leaching, runoff and NH3 volatilization,

425

negatively impacting water quality, in addition to elevated direct and indirect N2O

426

emissions and increased CO2-eq associated with fertilizer production and transport,

427

negatively impacting air quality. In terms of relative magnitude, NH3 volatilization is

428

well-documented as a prominent N loss pathway in flooded rice systems under strong

429

sunlight and high temperature conditions (Zhao et al., 2012). This was reflected in our

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ACCEPTED MANUSCRIPT results, where 7-10% of total N inputs were lost through NH3 volatilization among

431

rotations. Moreover, we found high reactive N loss through runoff and leaching in

432

wheat (Fig. 5), likely due to moderately heavy rainfall in winter crop growing season

433

under the subtropical monsoon climate, the acceleration of water flow by opened

434

drainage ditches, the slow fertilizer N assimilation by wheat and NO3- accumulation

435

in the cultivated layer (Zhao et al., 2012). High annual GHG emissions from the

436

rice-wheat rotation have also been reported by Wassmann et al. (2004), with values

437

ranging from 200-900 kg CH4 ha-1 and 0.017-4.72 kg N2O-N ha-1 under mineral

438

fertilization in Central China, equal to 5-23 Mg CO2-eq ha-1. Our direct measurements

439

of annual soil GHG emissions (186 kg CH4 ha-1 and 3.29 kg N2O ha-1) fall within this

440

range of high emissions, indicating the need for mitigation efforts. Overall, the

441

benefits of high crop productivity in the R-W rotation were offset by its negative

442

environmental performance, both in terms high rates of environmental N pollution

443

and enhanced global warming potential.

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The environmental N losses and C footprint of R-Ra showed a similar “high

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pollution” pattern with R-W (Figs S5 and 6a) due to the same high synthetic N

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fertilizer input as R-W. However, there was a penalty in rapeseed yield compared with

447

R-W, potentially making it less favorable for both farmers and decision makers (Fig.

448

3). Yet, as a second largest source of edible oil in China, oilseed rape is always in

449

demand. It has been suggested that one approach for compensating increased carbon

450

and environmental costs is to explore the potential value of rapeseed, for examples,

451

the use of rapeseed as an edible oil, vegetable, energy, forage, green manure and

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honey crop, as well as uses in extraction of glucosinolate compounds, as a sightseeing

453

attraction and for remediation of heavy metal pollution (Fu et al., 2016).

454

To transition away from intensive rice crop production systems in China which are associated with large carbon and environmental costs, alternative winter crops

456

such as legumes have been proposed as a solution. We found that relative to the

457

conventional rotation, the surface N balance of the rice-legume rotations was effective

458

in mitigating C emissions and reactive N losses via aquatic and atmospheric pathways

459

while also significantly reducing total N surplus. Importantly, these improvements in

460

sustainability were achieved without a rice yield penalty or negative impacts on soil

461

fertility in terms of soil N balances. Reductions in N inputs and outputs in rice-legume

462

rotations allowed this system to be characterized as a “lower input- lower loss”

463

alternative. By achieving a lower N surplus, legume rotations were able to mitigate a

464

range of potential environmental risks including eutrophication, soil acidification, and

465

GHG emissions (Fig. S5). These positive outcomes were largely associated with a

466

partial replacement of chemical N inputs with N derived from biological N fixation.

467

Incorporating legume residues has been suggested as an efficient soil amendment that

468

reduces NH3 volatilization and decreases soil NH4+-N concentration owing to the slow

469

decomposition rate compared with rate of urea hydrolysis (Justes et al., 2009). We

470

also found that waterborne reactive N losses were lower in the rice-legume rotations

471

than in the conventional rotations, which may have been due to the lower synthetic N

472

inputs. Runoff was the main source of reactive N loss in the conventional rotations,

473

comprising 23-30% of total reactive N loss, but only 13% in the rice-legume rotations,

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ACCEPTED MANUSCRIPT which may be most correlated with soil mineral N contents that could strongly

475

influenced by N fertilization (Vagstad et al., 1997). Decreased N runoff losses have

476

previously been reported in low N-fertilized cropping systems, where leguminous

477

manure systems reduced N runoff by up to 86% as a consequence of a reduction in N

478

fertilizer application rate (Zhao et al., 2015a). Although application of organic

479

amendments may increase SOC and therefore N2O production (Baggs et al., 2000),

480

this tradeoff may be compensated through reduced synthetic N application rates and

481

thus lower overall N2O emissions.

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This study revealed that an additional environmental benefit of rice-legume

483

rotations is that legume crops reduced C footprint by controlling both on-farm GHG

484

emissions and GHG emissions associated with the fertilizer production processes.

485

Likewise, in a farm-scale survey study results, Hillier et al. (2009) found the C

486

footprint in legume crops is only a quarter of which in winter wheat due to the

487

reduction in N applied. Barton et al. (2014) also showed the inclusion of lupin in a

488

wheat-based rotation decreased both FCF and PCF by about 50% through the

489

decreased CO2 emissions from fertilizer production and urea hydrolysis, and without

490

additional soil N2O emissions. Moreover, the indirect N2O emission that always been

491

neglected by previous researchers did showed a promising effect in reducing annual C

492

footprint by converting R-W or R-Ra to R-F or R-M, highlighting a necessary to

493

carefully tackle indirect N2O emission in the future C footprint researches. Our results

494

also support those reported by Xia et al. (2016) who found on-farm GHG emissions

495

decreased in a rice-legume rotation compared with a rice-wheat rotation even with an

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ACCEPTED MANUSCRIPT inclusion of extra GHGs emission during the fermentation process of leguminous

497

straws in rice-legume rotation. This study highlights the mitigating effect in total C

498

footprint when substituting winter legume for wheat with only low-cost direct straw

499

incorporation method were applied.

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Soil CH4 emissions from rice play a key role in determining the FCF of a

501

farming system, accounting for about half of annual CO2-eq in this study (Fig. 6b).

502

However, no clear increases in emissions from R-F or R-M compared with R-W and

503

R-Ra was found. The fact that CH4 emissions were not enhanced in rice-legume

504

rotations is a noteworthy finding since legume residue incorporation in soil before the

505

rice season should in theory increase C inputs compared to burning wheat or rape

506

straw, and thus increase CH4 emission (Liu et al., 2014) that penalize environmental

507

benefits in terms of reduced C emissions. Our results may in part be explained by the

508

rapid aerobic decomposition of legume biomass during the pre-rice growing phase, as

509

reported by Acharya (1935) who noted that highly aerobic plant decomposition

510

creates small amounts of CH4. It may also be possible that residual winter crop

511

stubbles incorporated into soil prior to flooding in R-W and R-Ra led to an increase in

512

labile soil C concentration that stimulated methanogenesis under anaerobic conditions

513

(Dalal et al., 2008), with higher rates of urea N fertilizer application potentially also

514

stimulating CH4 emissions through the inhibition of methanotrophic bacteria activity

515

(Xu et al., 2004), together resulting in similar CH4 emissions for the conventional and

516

legume-based rice rotations. To better understand these mechanisms, further study on

517

the relationship between the alternation of dry-wet soil conditions, fertilization, and

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other environmental factors and the long-term degradation rates of leguminous straws

519

in soil is needed.

520

4.2 Integrating environmental and economic costs

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The NEEB of cropping systems evaluated in the current study were most

523

responsive to gross grain yield revenues and associated carbon and environmental

524

costs discussed above, as other costs associated with rice production practices were

525

fixed once the experiment was designed. Our results highlight the possibility of

526

tradeoffs in crop productivity when designing agricultural systems to reduce

527

environmental pollution and enhance ecosystem services. For example, the sacrifice

528

of winter wheat yields in the rice-legume rotations, especially in rice-milk vetch

529

rotation where no revenue was produced during the legume winter crop (Fig. 7a) may

530

not appeal to farmers heavily focused on increasing economic outcomes. However,

531

the 40-49% reduction in estimated carbon and environmental costs by decreasing N

532

losses and C footprint in rice-legume rotations compensated the economic penalty

533

associated with a lower yielding fava bean winter crop (Fig. 7b), resulting in a

534

comparable NEEB between R-W and R-F. A major strength of our study is that

535

multiple years of field measurements for reactive N losses and soil GHG emissions

536

served as the basis for LCA and NEEB calculations, whereas many studies rely on

537

less dynamic conversion factors that may not represent the biophysical characteristics

538

of the study system.

539

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Considering the relatively low and unstable grain yields of fava bean in this

ACCEPTED MANUSCRIPT study, winter net return of R-F was unpredictable despite its high market price (Fig.

541

3b). Similarly, results reported by Xia et al. (2016) showed approximately a 12%

542

reduction in NEEB for R-F compared with R-W, considering revenue of rice yield but

543

lacking winter yield revenue and the various reactive N loss measurements performed

544

here. Another net economic benefit study by Zhao et al. (2015a) showed a 28%

545

increase in NEEB for R-F compared to R-W, without including the carbon costs.

546

Similar to the current study, Zhao et al. (2015a) found that fava bean crops suffered

547

from variable yields, and thus suggested a mixed cropping system with intercropping

548

strategy. Slinkhard et al. (1994) noted that legume crops may be susceptible to

549

increased pest and disease damage as a result of continuous cultivation, which could

550

be stabilized by proper rotation and intercropping strategy, as intercropping or rotation

551

with Chinese chive can decrease the occurrence of bacterial wilt (Huang et al., 2013).

552

Hence, to increase the potential for improved economic outcomes, farmers might

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consider either growing fava bean for one or two consecutive winter seasons before

554

switching to another winter crop in the rotation or intercropping fava bean with cash

555

crops (Kwabiah, 2004). One calculation based on the first two years of fava bean

556

yield in this study (which could be considered as optimized yield if integrated into a

557

more diversified long-term rotation), showed that NEEB of R-F increased by 41%,

558

leading to 38% higher NEEB compared to R-W. Moreover, this increase can enough

559

compensate for the NEEB decrease of the rice-legume manure rotation R-M caused

560

by the yield loss at the sacrifice of winter wheat. Aside from yield results, the negative

561

costs of aquatic and atmospheric N losses were likely underestimated in our approach,

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ACCEPTED MANUSCRIPT since we did not consider costs to human health (Ying et al., 2017). Likewise, the

563

potential revenue benefits of organic crops were not considered, for which prices may

564

be 20-140% higher than conventional crops (Pimentel et al., 2005). From this

565

standpoint, if governments wanted to develop policies promoting more sustainable

566

agricultural practices regarding N losses and C footprint, the motivation of farmers to

567

adopt rice-legume rotations could be further strengthened by relatively small financial

568

subsidies. For instance, the Chinese government issued a pilot land retirement

569

program intended to “explore a pilot scheme for the implementation of a crop land

570

rotation and fallow system” beginning in 2017, of which the annual subsidy for

571

farmers adopting environmental friendly rotation or fallow system in pilot sites like

572

Suzhou Municipal, Jiangsu Province, a city located near the TLR, was 4500 CNY ha-1

573

(China, 2017). By taking into account this subsidy when calculating NEEB for our

574

experiment, we found that NEEB of R-F could be 65% higher than that of R-W.

575

Perhaps the most promising aspect is that promoting rice-legume rotations is a rather

576

simple and practical means of achieving large improvements in environmental

577

performance with little risk to rice yields and potentially positive impacts on NEEB if

578

legume yields were further optimized as discussed above.

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Although the NEEB considered here intended to capture the entire life cycle of

580

crop production and a range of carbon and environmental costs, limitations existed

581

due to either a lack of information or methodology. For instance, N losses of the

582

cropping systems were likely underestimated due to the omission of denitrification. A

583

laboratory simulation that takes into consideration the magnitude of denitrification in

ACCEPTED MANUSCRIPT relation to other N loss pathways would deepen our understanding of how differences

585

in N losses contribute to overall N surplus estimates of legume-rice rotations. Nitric

586

oxide (NO), as an important intermediate of nitrification and denitrification processes,

587

contributes to ground level ozone and thus threatens human health. The omission of

588

NO in our study may underestimate the N losses as well as the total costs of NEEB

589

for the different systems. Similar with N2O emissions, emission of NO are higher in

590

upland crop than rice, which could mostly be attributed to aerobic soil conditions and

591

N fertilizer rate (Zhao et al., 2015b). While not measured in our study, based on the

592

reduced N fertilizer input for winter crops in the two rice-legume rotations, it could be

593

assumed that rice-legume rotations might reduce NO emission compared to

594

conventional rotations. Similarly, for economic calculations there is uncertainty in

595

crop prices and input costs due to fluctuating market prices which correlate with

596

market demand, but we were unable to precisely quantify this uncertainty. However,

597

as mentioned above this study features a compromise between accuracy and

598

feasibility in LCA studies, which are often constrained by a lack of empirical field

599

data. For example, consideration of local conditions and proper methods are needed to

600

account for soil C, thus Lovarelli et al. (2017) suggested the inclusion of primary

601

(measured) data into environmental assessment where possible, and Clavreul et al.

602

(2017) highlighted the importance of long-term investigation on the accuracy of C

603

footprint. This study provided an accurate assessment of on-farm GHG emissions

604

based on long-term data collection that could further contribute to the development of

605

LCA methodologies for different cropping systems.

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Conclusion

608

Our study showed rice-legume rotations offer great potential to mitigate C footprint

609

and reactive N losses compared with conventional rice rotations including wheat or

610

rape as a winter crop. We found FCF and reactive N losses were 46-50% and 50-57%

611

lower, respectively, when legumes were substituted for wheat. A key reason for these

612

mitigation effects is the > 63% reduction in annual application of synthetic N fertilizer,

613

with no N fertilizer applied to legumes and a reduced rate applied to rice. Reduced

614

GHG emissions related to fertilizer input, direct and indirect N2O emissions were the

615

greatest contributors to the decreased C footprint, whilst a reduction in NH3

616

volatilization and runoff was the major reduction pathways for reactive N losses. A

617

key finding is that while most of the N flow pathways showed reductions in the

618

rice-legume rotations, our estimate of economic efficiency which accounted for yield

619

benefits as well as carbon and environmental costs was similar for the conventional

620

rice-wheat rotation and when fava beans were substituted as a winter legume crop.

621

From an economic standpoint, this study also highlighted that NEEB can be

622

significantly higher for rice-legume rotations in years when grain legumes yields were

623

high, suggesting that future research is needed to identify long-term rotations or

624

intercropping systems which are capable of maintaining high legume yields. By

625

merging long-term field datasets with LCA approaches to account for multiple

626

environmental and economic outcomes, this work underscores the environmental

627

benefits of mixed winter grain/forage legume crops to support more sustainable and

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ACCEPTED MANUSCRIPT 628

productive rice cultivation, while potentially increasing NEEB when legume yields

629

are relatively high and stable.

630

Acknowledgements

632

The authors gratefully acknowledge the participating technicians and farmers at

633

Yixing Base of Changshu National Agro-Ecosystem Observation and Research

634

Station, Chinese Academy of Sciences (CAS) for their help with the field trial

635

management. We thank Mrs. Yang Li, Mrs. Chunyan Wang and Mr. Qingqian Wang

636

for their assistance with data collection and analysis. We also thank anonymous

637

reviewers and editors for their valuable comments. This work was supported by the

638

National Key R&D Program of China [grant number 2017YFD0200104].

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References Acharya, C.N., 1935. Studies on the anaerobic decomposition of plant materials: Comparison of the course of decomposition of rice straw under anaerobic, aerobic and

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partially aerobic conditions. Biochem. J. 29(5), 1116-1120.

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RI PT

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Baggs, E.M., Rees, R.M., Smith, K.A., Vinten, A.J.A., 2000. Nitrous oxide

emission from soils after incorporating crop residues. Soil Use and Manag. 16(2),

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82-87.

SC

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Barton, L., Thamo, T., Engelbrecht, D., Biswas, W.K., 2014. Does growing grain

648

legumes or applying lime cost effectively lower greenhouse gas emissions from wheat

649

production in a semi-arid climate? J. of Clean. Prod. 83, 194-203.

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Suzhou Municipal People's Government, 2017. Suggestions on the implementation of a crop land rotation and fallow system in suzhou city (trial).

652

http://www.zfxxgk.suzhou.gov.cn/sxqzf/szsrmzf/201709/t20170921_909029.html.

653

Accessed 19 September 2017

Choudhury, A.T.M.A., Kennedy, I.R., 2005. Nitrogen fertilizer losses from rice

EP

654

TE D

651

soils and control of environmental pollution problems. Commun. in Soil Sci. and

656

Plant Anal. 36(11-12), 1625-1639.

657

AC C

655

Clavreul, J., Butnar, I., Rubio, V., King, H., 2017. Intra- and inter-year variability

658

of agricultural carbon footprints – a case study on field-grown tomatoes. J. of Clean.

659

Prod. 158, 156-164.

660

Crews, T.E., Peoples, M.B., 2004. Legume versus fertilizer sources of nitrogen:

661

Ecological tradeoffs and human needs. Agric., Ecosyst. & Environ.102(3), 279-297.

ACCEPTED MANUSCRIPT 662

Dalal, R.C., Allen, D.E., Livesley, S.J., Richards, G., 2008. Magnitude and biophysical regulators of methane emission and consumption in the australian

664

agricultural, forest, and submerged landscapes: A review. Plant and Soil 309(1),

665

43-76.

666

RI PT

663

Dickin, E., Wright, D., 2008. The effects of winter waterlogging and summer drought on the growth and yield of winter wheat (triticum aestivum l.). Eur. J. of

668

Agron. 28(3), 234-244.

670 671

FAO, 2015. FAOSTAT online database. Food and Agri. Organ. of the UN,

M AN U

669

SC

667

http://www.fao.org/.

Fu, D.H., Jiang, L.Y., Mason, A.S., Xiao, M.L., Zhu, L.R., Li, L.Z., Zhou, Q.H., Shen, C.J., Huang, C.H., 2016. Research progress and strategies for multifunctional

673

rapeseed: A case study of china. J. of Integr. Agri. 15(8), 1673-1684.

676 677 678

use. Plant Physiol. 131(3), 872-877.

Hillier, J., Hawes, C., Squire, G., Hilton, A., Wale, S., Smith, P., 2009. The

EP

675

Graham, P.H., Vance, C.P., 2003. Legumes: Importance and constraints to greater

carbon footprints of food crop production. Int. J. of Agri. Sustain. 7(2), 107-118.

AC C

674

TE D

672

Hossain, M., Singh, V.P., 2000. Fertilizer use in asian agriculture: Implications

679

for sustaining food security and the environment. Nutr. Cycl. in Agroecol. 57(2),

680

155-169.

681

Hou, A.X., Chen, G.X., Wang, Z.P., Van Cleemput, O., Patrick, W.H., 2000.

682

Methane and nitrous oxide emissions from a rice field in relation to soil redox and

683

microbiological processes. Soil Sci. Soc. of Am. J. 64(6), 2180-2186.

ACCEPTED MANUSCRIPT 684

Huang, L., Song, L., Xia, X., Mao, W., Shi, K., Zhou, Y., Yu, J., 2013. Plant-soil

685

feedbacks and soil sickness: From mechanisms to application in agriculture. J. of

686

Chem. Ecol. 39(2), 232-242. IPCC, 2006. Guidelines for national greenhouse gas inventories, in: Eggleston,

RI PT

687 688

H., Buendia, L., Miwa, K., Ngara, T., Tanabe, K. (Eds.), Prepared by the National

689

Greenhouse Gas Inventories Programme. Inst. for Glob. Environ. Strateg. Japan.

IPCC, 2007. Climate change 2007: The physical science basis, Working Group I

SC

690

Contribution to the Fourth Assessment Report of the Intergovernmental Panel on

692

Climate Change. Cambridge University Press, Cambridge, United Kingdom and New

693

York, NY, USA.

M AN U

691

IPCC, 2014. Climate change 2013, The physical science basis: contribution of

695

Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on

696

Climate Change. Cambridge University Press, Cambridge, United Kingdom and New

697

York, NY, USA.

Ju, X.T., Xing, G.X., Chen, X.P., Zhang, S.L., Zhang, L.J., Liu, X.J., Cui, Z.L.,

EP

698

TE D

694

Yin, B., Christie, P., Zhu, Z.L., Zhang, F.S., 2009. Reducing environmental risk by

700

improving n management in intensive Chinese agricultural systems. Proc. of the Natl.

701

Acad. of Sci. of the U. S. A. 106(9), 3041-3046.

702

AC C

699

Justes, E., Mary, B., Nicolardot, B., 2009. Quantifying and modelling C and N

703

mineralization kinetics of catch crop residues in soil: Parameterization of the residue

704

decomposition module of STICS model for mature and non mature residues. Plant

705

and soil 325(1-2), 171-185.

ACCEPTED MANUSCRIPT 706 707 708

Kwabiah, A.B., 2004. Biological efficiency and economic benefits of pea-barley and pea-oat intercrops. J. of Sustain. Agri. 25(1), 117-128. Ladha, J., Fischer, K.S., Hossain, M., Hobbs, P., Hardy, B., 2000. Improving the productivity and sustainability of rice-wheat systems of the indo-gangetic plains: A

710

synthesis of NARS-IRRI partnership research. IRRI Discuss. Paper. Available at

711

http://www.irri.org/publications/discussion/pdfs/ricewheat.pdf (verified 22 July 2009). Ladha, J.K., Pathak, H., Tirol-Padre, A., Dawe, D., Gupta, R.K., 2003.

SC

712

RI PT

709

Productivity trends in intensive rice–wheat cropping systems in asia, in: Ladha, J.K.,

714

Hill, J.E., Duxbury, J.M., Gupta, R.K., Buresh, R.J. (Eds.), Improving the productivity

715

and sustainability of rice–wheat systems: Issues and impacts. Madison, WI, pp. 45-76.

M AN U

713

Li, B., Fan, C.H., Zhang, H., Chen, Z.Z., Sun, L.Y., Xiong, Z.Q., 2015.

717

Combined effects of nitrogen fertilization and biochar on the net global warming

718

potential, greenhouse gas intensity and net ecosystem economic budget in intensive

719

vegetable agriculture in southeastern china. Atmos. Environ. 100, 10-19. Linquist, B., Groenigen, K.J., Adviento-Borbe, M.A., Pittelkow, C., Kessel, C.,

EP

720

TE D

716

2012. An agronomic assessment of greenhouse gas emissions from major cereal crops.

722

Glob. Change Biol. 18(1), 194-209.

723

AC C

721

Liu, C., Lu, M., Cui, J., Li, B., Fang, C., 2014. Effects of straw carbon input on

724

carbon dynamics in agricultural soils: A meta-analysis. Glob. Change Biol. 20(5),

725

1366-1381.

726

Lovarelli, D., Bacenetti, J., Fiala, M., 2017. Effect of local conditions and

727

machinery characteristics on the environmental impacts of primary soil tillage. J. of

ACCEPTED MANUSCRIPT 728 729

Clean. Prod. 140(2), 479-491. Melaku Canu, D., Ghermandi, A., Nunes, P., Lazzari, P., Cossarini, G., Solidoro, C., 2015. Estimating the value of carbon sequestration ecosystem services in the

731

mediterranean sea: An ecological economics approach. Glob. Environ. Change 32,

732

87-95.

733

RI PT

730

Mucheru-Muna, M., Pypers, P., Mugendi, D., Kung’u, J., Mugwe, J., Merckx, R., Vanlauwe, B., 2010. A staggered maize–legume intercrop arrangement robustly

735

increases crop yields and economic returns in the highlands of central kenya. Field

736

Crops Res. 115(2), 132-139.

738

M AN U

737

SC

734

Ness, B., Urbel-Piirsalu, E., Anderberg, S., Olsson, L., 2007. Categorising tools for sustainability assessment. Ecol. Econ. 60(3), 498-508.

Oenema, O., Kros, H., de Vries, W., 2003. Approaches and uncertainties in

740

nutrient budgets: Implications for nutrient management and environmental policies.

741

Eur. J. of Agron. 20(1-2), 3-16.

Pimentel, D., Hepperly, P., Hanson, J., Douds, D., Seidel, R., 2005.

EP

742

TE D

739

Environmental, energetic, and economic comparisons of organic and conventional

744

farming systems. BioSci. 55(7), 573-582.

745

AC C

743

Schumacher, B.A., 2002. Methods for the determination of total organic carbon

746

(TOC) in soils and sediments. U. S. Environmental Protection Agency, Ecological

747

Risk Assesment Support Center.

748 749

Sharma, P.K., Ladha, J.K., Bhushan, L., 2003. Soil physical effects of puddling in rice–wheat cropping systems, in: Ladha, J.K., Hill, J.E., Duxbury, J.M., Gupta,

ACCEPTED MANUSCRIPT 750

R.K., Buresh, R.J. (Eds.), Improving the productivity and sustainability of rice–wheat

751

systems: Issues and impacts. American Society of Agronomy, Crop Science Society of

752

America, and Soil Science Society of America, Madison, pp. 97-113. Slinkhard, A., Bascur, G., Hernandez-Bravo, G., 1994. Biotic and abiotic stresses

RI PT

753

of cool season food legumes in the western hemisphere, Expanding the production

755

and use of cool season food legumes. Springer Netherlands, Dordrecht, pp. 195-203.

756

Smil, V., 1999. Nitrogen in crop production: An account of global flows. Glob.

758

Biogeochem. Cycles 13(2), 647-662.

M AN U

757

SC

754

Smith, P., Martino, D., Cai, Z.C., Gwary, D., Janzen, H., Kumar, P., McCarl, B., Ogle, S., O'Mara, F., Rice, C., Scholes, B., Sirotenko, O., Howden, M., McAllister, T.,

760

Pan, G.X., Romanenkov, V., Schneider, U., Towprayoon, S., Wattenbach, M., Smith,

761

J., 2008. Greenhouse gas mitigation in agriculture. Philos. Trans. of the R. Soc. (B):

762

Biol. Sci. 363(1492), 789-813.

764

Terry, R.E., Tate, R.L., Duxbury, J.M., 1981. The effect of flooding on nitrous oxide emissions from an organic soil. Soil Sci. 132(3), 228-232.

EP

763

TE D

759

Tilman, D., Cassman, K.G., Matson, P.A., Naylor, R., Polasky, S., 2002.

766

Agricultural sustainability and intensive production practices. Nat. 418, 671.

767

AC C

765

Vagstad, N., Eggestad, H.O., Høyås, T.R., 1997. Mineral nitrogen in agricultural

768

soils and nitrogen losses: Relation to soil properties, weather conditions, and farm

769

practices. Ambio 26(5), 266-272.

770 771

Vance, C.P., Graham, P.H., Allan, D.L., 2000. Biological nitrogen fixation: Phosphorus - a critical future need?, in: Pedrosa, F.O., Hungria, M., Yates, G., Newton,

ACCEPTED MANUSCRIPT 772

W.E. (Eds.), Nitrogen fixation: From molecules to crop productivity. Springer

773

Netherlands, Dordrecht, pp. 509-514.

774

Wassmann, R., Neue, H.U., Ladha, J.K., Aulakh, M.S., 2004. Mitigating greenhouse gas emissions from rice-wheat cropping systems in asia, in: Wassmann, R.,

776

Vlek, P.L.G. (Eds.), Tropical agriculture in transition — opportunities for mitigating

777

greenhouse gas emissions? Springer Netherlands, Dordrecht, pp. 65-90.

Xia, L.L., Xia, Y.Q., Li, B.L., Wang, J.Y., Wang, S.W., Zhou, W., Yan, X.Y., 2016.

SC

778

RI PT

775

Integrating agronomic practices to reduce greenhouse gas emissions while increasing

780

the economic return in a rice-based cropping system. Agric., Ecosyst. & Environ. 231,

781

24-33.

783 784 785

Xia, Y.Q., Yan, X.Y., 2012. Ecologically optimal nitrogen application rates for rice cropping in the Taihu Lake Region of China. Sustain. Sci. 7(1), 33-44.

TE D

782

M AN U

779

Xu, X.M., Lan, Y., 2017. Spatial and temporal patterns of carbon footprints of grain crops in china. J. of Clean. Prod. 146, 218-227. Xu, Z.J., Zheng, X.H., Wang, Y.S., Han, S.H., Huang, Y., Zhu, J.G.,

787

Butterbach-Bahl, K., 2004. Effects of elevated CO2 and N fertilization on CH4

788

emissions from paddy rice fields. Glob. Biogeochem. Cycles 18(3), 1-9.

790 791

AC C

789

EP

786

Ying, H., Ye, Y., Cui, Z., Chen, X., 2017. Managing nitrogen for sustainable

wheat production. J. of Clean. Prod. 162, 1308-1316. Zhang, X.Q., Pu, C., Zhao, X., Xue, J.F., Zhang, R., Nie, Z.J., Chen, F., Lal, R.,

792

Zhang, H.L., 2016. Tillage effects on carbon footprint and ecosystem services of

793

climate regulation in a winter wheat–summer maize cropping system of the North

ACCEPTED MANUSCRIPT 794 795

China Plain. Ecol. Indic. 67, 821-829. Zhang, Z.S., Guo, L.J., Liu, T.Q., Li, C.F., Cao, C.G., 2015. Effects of tillage practices and straw returning methods on greenhouse gas emissions and net

797

ecosystem economic budget in rice–wheat cropping systems in Central China. Atmos.

798

Environ. 122, 636-644.

799

RI PT

796

Zhao, X., Wang, S.Q., Xing, G.X., 2015a. Maintaining rice yield and reducing n pollution by substituting winter legume for wheat in a heavily-fertilized rice-based

801

cropping system of Southeast China. Agric., Ecosyst. & Environ. 202, 79-89.

M AN U

802

SC

800

Zhao, M., Tian, Y.H., Zhang, M., Yao, Y.L., Ao, Y.Q., Yin, B., Zhu, Z.L., 2015b. Nonlinear response of nitric oxide emissions to a nitrogen application gradient: A case

804

study during the wheat season in a Chinese rice-wheat rotation system. Atmos.

805

Environ. 102, 200-208.

806

TE D

803

Zhao, X., Zhou, Y., Wang, S.Q., Xing, G.X., Shi, W.M., Xu, R.K., Zhu, Z.L., 2012. Nitrogen balance in a highly fertilized rice–wheat double-cropping system in

808

southern china. Soil Sci. Soc. of Am. J. 76(3), 1068-1078. Zhu, Z.L., 1997. Nitrogen balance and cycling in agroecosystems of china, in:

AC C

809

EP

807

810

Zhu, Z.L., Wen, Q., Freney, J.R. (Eds.), Nitrogen in soils of china. Springer

811

Netherlands, Dordrecht, pp. 323-338.

812

Zhu, Z.L., Zhang, F.S., 2010. Basic study on nitrogen behavior and efficient

813

utilization of nitrogen fertilizer in two intensive agroecosystem of China. Science

814

Press Beijing(in Chinese).

815 816

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Fig. 1. Location of the study site in China (a); winter crops in the four experimental

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rotations under rice-wheat(R-W), rice-rape(R-Ra), rice-fava bean(R-F), and rice-milk

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vetch(R-M) annual (b); and, schematic view of the observed fields (c).

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Fig. 2. System boundary for calculating C footprint, N balance, and net ecosystem

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economic benefits of the four rotations. Green dotted boxes: CO2-eq sinks mainly

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indicating changes in soil organic C changes; red dotted boxes: CO2-eq sources

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including C emissions from fertilizers and farm operations, direct GHG emissions and

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indirect N2O emissions from reactive N losses to environment; green solid box: yield

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gains (1); red solid boxes: ecosystem economic costs of agricultural activities (2), C

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emissions (3) and reactive N exports (4).

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Fig. 3. Annual grain and straw yields from summer (a) and winter crops (b) in the

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four rotations over twelve cropping seasons.

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Fig. 4. Cumulative N2O (a), CH4 (b) emissions and NH3 volatilization (c), from rice

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and winter crops in the four rotations over twelve cropping seasons. R-W: rice-wheat;

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R-Ra: rice-rape; R-F: rice-fava bean; and, R-M: rice-milk vetch. * indicate individual

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values in each of six rice or winter crop seasons. The length of the lines: minimum

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and maximum values; box: upper and lower quartiles: horizontal line within box:

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median; red dot: mean. Different lowercase letters indicate significant differences in

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means at P < 0.05.

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Fig. 5. Cumulative N loads in summer (a) and winter (b) runoff, and summer (c) and

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winter (d) leaching from the four rotations over twelve cropping seasons. R-W:

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rice-wheat; R-Ra: rice-rape; R-F: rice-fava bean; and, R-M: rice-milk vetch. TN: total

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soluble N. * indicate seasonal TN, NO3- or NH4+ loads in runoff and leaching for a

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certain crop season of the four rice-based rotation systems. Lines: minimum and

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maximum values; box: upper and lower quartiles: horizontal line within box: median;

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red dot: mean. Different lowercase letters indicate significant differences in means at

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P < 0.05.

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Fig. 6. Farm and product carbon footprints (a) and distribution of total carbon

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emissions (b) of the four rotations over twelve cropping seasons. Data in panel (a) are

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total carbon emissions ha-1 and per unit of rice grain yield, * indicate individual

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values of six consecutive rotation cycles for a certain rice-based rotation system. Data

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in panel (b) are annual averages + SEM of carbon emissions and soil sequestrations,

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R-W: rice-wheat; R-Ra: rice-rape; R-F: rice-fava bean; and, R-M: rice-milk vetch.

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Lines: minimum and maximum values; box: upper and lower quartiles: horizontal line

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within box: median; red dot: mean. Different lowercase letters indicate significant

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differences in means at P < 0.05.

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Fig. 7. Net ecosystem economic benefits (NEEB) (a) and total costs and yield gains (b)

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of the four rotations over twelve cropping seasons. Data are annual averages ± SEM.

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R-W: rice-wheat; R-Ra: rice-rape; R-F: rice-fava bean; and, R-M: rice-milk vetch. In

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(b), * indicate individual NEEB values of six consecutive rotation cycles for a certain

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rice-based rotation system.

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Fig. 7.