Toward Sustainable Nitrogen and Carbon Cycling on Diversified Horticulture Farms Serving Community Food Systems

Toward Sustainable Nitrogen and Carbon Cycling on Diversified

Horticulture Farms Serving Community Food Systems

Krista L. Jacobsen, Debendra Shresta, Department of Horticulture, University of Kentucky

Ole Wendroth*, Department of Plant and Soil Sciences, University of Kentucky

John Schramski, College of Engineering, University of Georgia *presenting author 2013-67019-21403

Introduction

Project Background & Context Project overview Highlights from one of the field experiments Overview of modeling objectives and goals

Background and Context

Small- and medium-scale, diversified farms are important sources of agricultural products for the local and regional food movement

Local food purchases are increasingly valued by the public for perceptions of healthier products due to “freshness,” conservation of local farm lands, and/or supporting local farmers (Onozaka et al, 2010)

Horticultural crops are a large part of this market Fruits, vegetables and nuts were 70% of local food sales in

2007 (Low & Vogel, 2011). Diversification into horticultural crops serving local

markets is a global trend for small-holder farmers (Weinberger and Lumpkin, 2007), as horticultural crops are typically higher in value per unit area than cereals (USDA-NASS, 2009)

Background and Context However, much of what we know about C and N cycling in

agroecosystems comes from agronomic systems, less research in horticulture systems (e.g. West & Post, 2002; Ma & Shaffer, 2001)

Further, production practices are highly variable, with little standard rotation varying degree of intensity

Example: A lower input system, with no supplemental irrigation, “living mulch” between rows, and seasonal production

Example: Green bean production in a high tunnel system, with drip supplemental irrigation, intense-tillage, in a year-round production system

Project Objectives Broadly, to improve our understanding of how intensification on diversified

horticulture-based farms influences (1) nitrogen availability, efficiency, and retention and (2) soil carbon dynamics in labile carbon pools.

Project Objectives: Specifically…

(i) In addition to C and N dynamics, we are also seeking to better understand the net effects of intensification on whole system C balances using Energy Returned on Energy Invested (akin to life cycle analysis) approaches.

More on this next year…

Project Objectives Specifically…

(ii) to compare the nitrogen dynamics and key loss pathways in five farming systems, including four organic systems, representing a gradient of intensification (characterized by quantity of inputs, and the frequency of tillage and fallow periods)

Project Objectives: Specifically…

(iii) to identify the sensitivity of a model to measured parameters to describe the key plant growth and soil processes.

Soil input:Soil hydraulic propertiesStatus of soil moisture and different C- and N-fractions

Plant input:Growth status, root development

00.5

11.5

22.5

33.5

44.5

5

-30

-20

-10

0

10

20

30

40

Precipita-tion (Inch)

Prec

ipita

tion

(inch

)

Air T

emp

(°C)

0100200300400500600700800 CO2 FLUX

Extensive Organic system Conventional system Stationary Organic High Tunnel system

Tota

l flux

(mgC

O2

m-2

hr-

1

-100

-50

0

50

100

150

200

250

300

350

400

N2O FLUXExtensive Organic system Conventional system Stationary Organic High Tunnel system

N2O

flux

ug

m-2

hr-1

First results on GHG fluxes in different horticultural systems

New RZWQM GHG Submodel (Fang et al., 2015)N2O emission (N2O_nit) from DAYCENT, fixed proportion of nitrification (Rnit) modified by a soil water factor (FSW_Nit) (Gillette et al., 2017) with WFPS as the water-filled pore space

nitNitSWNitnit RFFr _ON_2 _ON2

04.104.14.0

_

WFPSWFPSF NitSW

denDenONden RFrON __2 2

New: diffusion factor for taking into account N2O diffusion across different soil depths.

09/01/2009 02/28/2010 08/27/2010 02/23/2011 08/22/20110

50

100

150

PREC

IPIT

ATIO

N (m

m)

-15

-5

5

15

25

35

Tavg

PRECIP.AIR-TEMP.

09/01/2009 02/28/2010 08/27/2010 02/23/2011 08/22/2011

0.00

0.04

0.08

0.12

0.16

0.20

N2O

-FLU

X (k

g N

/ha/

day)

N2O-MEASUREDN2O SIMULATED

CROP (WHEAT)n = 30

09/01/2009 02/28/2010 08/27/2010 02/23/2011 08/22/2011Date

0.0

0.1

0.2

0.3

0.4

0.5

SWC

(cm

3 cm

-3)

SWC 0-10 cm

6/1/2010 8/1/2010 10/1/2010 12/1/2010 1/31/2011 4/2/2011 6/2/20110

40

80

DA

ILY

PR

EC

IP.

(m

m)

-10

10

30

AIR

TE

MP

. (C

)

PREC.

AIR-TEMP.

6/1/2010 8/1/2010 10/1/2010 12/1/2010 1/31/2011 4/2/2011 6/2/20115

7

9

SW

S 0

-30

cm

(cm

)-10

10

30

SO

IL T

EM

P. (

C)

SWS SOIL TEMP.

6/1/2010 8/1/2010 10/1/2010 12/1/2010 1/31/2011 4/2/2011 6/2/20110

10

20

qC

O2

(mg

m-2

min

-1)

0.0

0.5

1.0

1.5

CV

q CO

2qCO2 CVqCO2

6/1/2010 8/1/2010 10/1/2010 12/1/2010 1/31/2011 4/2/2011 6/2/2011

0

5

10

15

NU

GG

ET

C0

(mg

m-2

min

-1)2

050100150200250

RA

NG

E a

(m)

NUGGET C0qCO2 RANGE aqCO2

6/1/2010 8/1/2010 10/1/2010 12/1/2010 1/31/2011 4/2/2011 6/2/2011DATE

0.0

0.5

1.0

C0/

(C+C

0)

0

10

20

STD

q CO

2NUGGET/SILL qCO2STD qCO2

RESULTS

• Temporal stability of CO2 flux • rank relationship to surface soil water storage• What are the main drivers of CO2 flux

6/1/2010 8/31/2010 11/30/2010 3/1/2011 5/31/2011DATE OF MEASUREMENT

-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

JUNE 08, 2010

6/1/2010 8/1/2010 10/1/2010 12/1/2010 1/31/2011 4/2/2011 6/2/20115

7

9

SW

S 0

-30

cm

(cm

)

-10

10

30

SO

IL T

EM

P. (

C)

SWS SOIL TEMP.

CO2 flux Pattern Development and Dependence on Soil Moisture during one year.


-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

JUNE 08, 2010

6/1/2010 8/1/2010 10/1/2010 12/1/2010 1/31/2011 4/2/2011 6/2/20115

7

9

SW

S 0

-30

cm

(cm

)-10

10

30

SO

IL T

EM

P. (

C)

SWS SOIL TEMP.


-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

JUNE 21, 2010


-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

JULY 06, 2010


-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

JULY 19, 2010


-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

AUG. 02, 2010


-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

AUG. 16, 2010


-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

SEP. 02, 2010


-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

SEP. 16, 2010


-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

SEP. 30, 2010


-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

OCT. 15, 2010


-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

OCT. 28, 2010


-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

NOV. 11, 2010


-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

NOV. 25, 2010


-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

DEC. 31, 2010


-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

JAN. 31, 2011


-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

FEB. 15, 2011


-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

MAR. 01, 2011


-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

MAR. 17, 2011


-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

MAR. 28, 2011


-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

APR. 13, 2011


-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

APR. 28, 2011


-1.0

-0.5

0.0

0.5

1.0

SP

EA

RM

AN

RA

NK

CO

RR

ELA

TIO

N r s

qCO2

qCO2 - WS0-30

JUNE 08, 2011

Conclusions GHG fluxes and relevant soil state variables

(moisture, nitrogen) measured over two seasons. GHG flux behavior locally driven (SWC and T

influence gas flux only on a relative not on an absolute basis).

First steps in modeling N2O fluxes with RZWQM Next steps:

• model sensitivity to measured soil parameters• dynamics at different time-scales

Thank you

to USDA-AFRI for supporting our research.

Environment

Toward Sustainable Nitrogen and Carbon Cycling on Diversified Horticulture Farms Serving Community Food Systems