Soil-Specific Inventories of Landscape Carbon and Nitrogen Stocks ...

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material, soil texture, and land use (Jenny, 1941; Stevenson and Cole, 1999). ...... Sá, J.C.M., C.C. Cerri, W.A. Dick, R. Lal, S.P. Venske, M.C. Piccolo, and B.E..
Soil & Water Management & Conservation

Soil-Specific Inventories of Landscape Carbon and Nitrogen Stocks under No-Till and Native Vegetation to Estimate Carbon Offset in a Subtropical Ecosystem João Carlos de Moraes Sá*

State Univ. of Ponta Grossa Dep. of Soil Science and Agricultural Engineering Av. Carlos Cavalcanti 4748 Campus de Uvaranas, 84030-900 Ponta Grossa-PR, Brazil

Josiane Bürkner dos Santos Inst. Agronômico do Paraná Polo Regional de Ponta Grossa Av. Presidente Kennedy, s/n Ponta Grossa-PR, Brazil

Rattan Lal

The Ohio State Univ. Carbon Management and Sequestration Center School of Environment and Natural Resources OARDC/FAES 2021 Coffey Rd. Columbus, OH 43210

Anibal de Moraes

Federal Univ. of Paraná Dep. of Crop Science Av. Dos Funcionários, s/n Juvevê, 80060-000 Curitiba-PR, Brazil

Florent Tivet

Centre de Coopération Internationale en Recherche Agronomique pour le Développement CIRAD, UR SIA Avenue Agropolis, 34398 Montpellier, France

Marcia Freire Machado Sá

State Univ. of Ponta Grossa Dep. of Soil Science and Agricultural Engineering Av. Carlos Cavalcanti 4748 Campus de Uvaranas, 84030-900 Ponta Grossa-PR, Brazil

Clever Briedis

Agronomy Graduate Program State Univ. of Ponta Grossa Av. Carlos Cavalcanti 4748 Campus de Uvaranas 84030-900 Ponta Grossa-PR, Brazil

Ademir de Oliveira Ferreira

Soil Science Graduate Program Federal Univ. of Santa Maria Santa Maria-RS Av. Roraima 1000 Camobi CEP 97105-900 Santa Maria-RS, Brazil

Guilherme Eurich Anderson Farias

Agronomy Undergraduate Program State Univ. of Ponta Grossa Av. Carlos Cavalcanti 4748 Campus de Uvaranas, 84030-900 Ponta Grossa-PR, Brazil

Theodor Friedrich

Food Agriculture Organization Plant Production and Protection Division (AGP) Room C-782 Viale delle Terme di Caracalla 00153 Rome, Italy



Inventories of C and N footprints on a landscape scale are essential tools for estimating C offsets from agricultural emissions. Therefore, the aims of this study conducted in the subtropical humid ecosystem in southern Brazil were to: (i) conduct a soil-specific inventory of landscape soil C and N stocks with reference to soil order, soil texture, and land use/management type; (ii) estimate accretion rates for soil organic C (SOC) and total N (TN) for areas managed under no-till (NT) practices management with reference to native vegetation (NV) based on this inventory; (iii) generate a map of C stocks for each land use system; and (iv) calculate estimated C offset for the region through the use of NT compared to conventional tillage (CT). Soil samples were collected at 324 points to a 1-m depth from the entire region. Soil texture and duration of NT had a strong influence on C and N stocks. The average soil C stock across all types of soils for depths of 0–40 and 40–100 cm was 57.0 and 43.0%, respectively. The extrapolation of C stored in the 0- to 40-cm depth based on the NT management for 11 and 20 yr for 1.52 million hectare (Mha) was 9.08 ± 0.62 Tg (1 Tg = 1012 g) representing 11.9% of the C stored in all soil orders. The long-term of C sink capacity by conversion of arable land from CT to NT in this region is 33.2 Tg of CO2, with the C offset of 22.5% of all anthropogenic emissions. Abbreviations: CRB, Carambeí; CT, conventional tillage; CTR, Castro; Eq. CE, equivalent C emission; GHG, greenhouse gas; GIS, geographic information systems; IPCC, Intergovernmental Panel on Climate Change; LULUCF, Land Use, Land-Use Change and Forestry; Mha, million hectares; NT, no-till; NT-11, NT practiced for 15 yr; NV, native vegetation; PG, Ponta Grossa; PLR, Palmeira; SCS, soil carbon stock; SOC, soil organic C; TBG, Tibagi; Tg, 1012 g º 1 trillion g; TN, total N; TNS, total N stock; TOC, total organic C.

S

oil organic C is a key parameter affecting the productivity and sustainability of agroecosystems (Bruce et al., 1999). The amount of C stored in world soils to a 1-m depth is approximately four times that existing in plant biomass and three times that in the atmosphere (Lal, 2004b, 2008). Thus, SOC stock, hereafter called soil C stock (SCS), is influenced by numerous factors in the ecosystems including climate, vegetation, soil order and biodiversity, topography, parent material, soil texture, and land use ( Jenny, 1941; Stevenson and Cole, 1999). Soil orders with deep profiles, high clay and fine silt contents, 2:1 type clay minerals and predominance of sesquioxides in the clay fraction, high water retention capacity, and high concentrations of N, P, and S are likely to have high C sink capacity ( Jenny, 1980; Stevenson and Cole, 1999). Based on these criteria, soil orders with high C sink capacity include Histosols and Inceptisols, medium capacity include Mollisols, low capacity include Oxisols and Ultisols, and very low capacity include Entisols (Bohn, 1976; Batjes, 1996, 2005). Attempts to quantify global SCS since the 1970s and develop maps of regional C distribution (Bolin, 1970; Bohn, 1976; Parton et al., 1987; Batjes, 1996) have Soil Sci. Soc. Am. J. 77:2094–2110 doi:10.2136/sssaj2013.01.0007 Received 7 Jan. 2013. *Corresponding author ([email protected]). © Soil Science Society of America, 5585 Guilford Rd., Madison WI 53711 USA All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.

Soil Science Society of America Journal

greatly advanced efforts to predict temporal changes in SCS for different land use and soil management systems (Lettens et al., 2004; Bradley et al., 2005). These studies have strengthened the understanding of C distribution in diverse ecosystems and also advanced the measurement and monitoring techniques (Lettens et al., 2004) along with the use of geographic information systems (GIS). Significant advances have been made since the 2000s in software for GIS (Schulp and Veldkamp, 2008; Hartemink, 2008; Soil Survey Staff, 2010; Lilburne et al., 2012) and the development of more accurate digital mapping of the spatial distribution of SCS, which in turn has generated decision support tools for terrestrial C management in different environments (Ogle et al., 2005; Dolan et al., 2006). The Intergovernmental Panel on Climate Change (IPCC) has sought to develop periodic inventories of greenhouse gas (GHG) emissions and C sinks to guide political action at a global scale (1998). The IPCC (2006) established a protocol for the quantification of SCS and total N stocks (TNS) and GHG fluxes for the field scale inventories on an areal basis for different agricultural soil management systems. Conversion of NV to agricultural ecosystems through deforestation, biomass burning, and the continued use of mechanical tillage depletes SOC stock with the attendant emission of CO2 into the atmosphere (Lal, 2008; Don et al., 2011). Land use and soil management influence the magnitude and rate of C accretion as SCS because they determine whether a soil is a source or a sink of GHGs (Bruce et al., 1999; Lal, 2004b). In general, soils managed in plow-based systems are a source of CO2 and other GHGs because mechanical disturbance increases the oxidation of soil organic matter (SOM) by microbiota (Elliott, 1986; Powlson et al., 1987) and increase risks of accelerated erosion in soils of the tropics (Lal, 1976). In contrast, the adoption of an NT system tends to create a sink for atmospheric CO2 in these soils because of a decrease in risks of soil erosion (Lal, 1976; Cogo et al., 1984; Meyer et al., 1999; Vandenbygaart et al., 2012) and SOC decomposition (Staley et al., 1988; Emmerling et al., 2001). The effectiveness of management strategies that increase C-input and decrease losses through erosion and decomposition can be maximized by using soil-specific management approaches. For example, increasing input of deficient nutrients (e.g., P, S) for Oxisols and Ultisols; neutralization of active acidity for Oxisols, Ultisols, and Inceptisols; and alleviation of toxicity (e.g., Al, Mn) for Oxisols, Ultisols, and Inceptisols (Fox, 1980) would enhance the net primary productivity (NPP) and increase input of biomass-C into the soil (Lugo and Brown, 1993). Since circa 2000, the estimation of SCS and its spatial distribution maps for Brazilian soils (Bernoux et al., 2002; Wang et al., 2003; Bernoux et al., 2005; Bayer et al., 2006; Cerri et al., 2007; Fidalgo et al., 2007; Tornquist et al., 2009) have contributed to the preparation of national GHG inventories. However, most SCS inventories and SCS maps in Brazil are based on a database from ground surveys conducted by the National Soil Survey and Classification Service (Serviço Nacional de Levantamento e Classificação do Solo—Embrapa Solos) during 1978–80 and www.soils.org/publications/sssaj

1981 and by the RADAMBRASIL project in 1986–87 (Embrapa, 1984). Furthermore, there are no reports of landscape scale inventories of SCS and TNS that are based on the IPCC land use, land use change and forestry, or Tier- 3 guidelines (2006), which can be used to develop a baseline for building C offset scenarios. Thus, there is a strong need for up to date in situ inventories of C and N stocks at the landscape-scale based on land use and management systems. Therefore, specific objectives of this study were to (i) prepare an inventory of C and N stocks according to soil order, textural class, and duration of NT farming; (ii) generate spatial distribution maps of SCS for each land use system as a function of soil order and texture; (iii) assess the historic contribution of NT to the changes in SCS relative to NV; and (iv) estimate the C offset from NT farming for a subtropical ecosystems encompassing an area of 1.52 Mha in the region of Campos Gerais do Paraná, Southern Brazil.

Material and Methods Rationale for the Inventory of Carbon and Nitrogen Footprint Assessment on Landscape-Scale Farm Sites The inventory of SCS and TNS presented in this study was based on the IPCC’s Good Practice Guidance for Land Use, Land-Use Change and Forestry (LULUCF), Chapter 3, Tier 3 (IPCC, 2003). The LULUCF methodology is based on two assumptions: (i) the efflux of CO2 to the atmosphere results from changes in plant biomass and SCS, and (ii) changes in SCS and TNS can be estimated by measuring temporal changes in land use and management practices.

Location and Description of the Study Area The study region designated as Campos Gerais do Paraná is located on the first and second plateaus of the south-central quadrant of the State of Paraná (Fig. 1). The entire region is comprised of 13 municipalities with a total area of 1.81 Mha (Embrapa, 2008). The altitude ranges from 810 to 1075 m above sea level and the region has a high-elevation subtropical, humid, mesothermal, Cfb-type climate (Köppen climate classification). The summer is cool, and frequent frosts occur during the winter but there is no well-defined dry season. The average temperature of the region is Inceptisols > Oxisols > Ultisols heavy-clay > Histosols sandy > Ultisols sandy-clay > Entisols. Total C stored to a 1-m depth for all soil orders in NT-11 (205 ± 2.21 Tg) was lower than in NT-20 (220 ± 2.13 Tg). Further, total C stored to a 1-m depth of all soil orders under NV was 16% higher than 2107

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Area/Soil Order † 0.274 0.060 0.032 0.011 0.234 0.041 0.086 0.011 0.114 0.010 0.034 0.91

Total

NT-11

NT-20

———————— Mha ———————— 0.233 0.082 0.152 0.051 0.018 0.033 0.027 0.009 0.017 0.009 0.003 0.006 0.199 0.070 0.129 0.035 0.012 0.022 0.073 0.026 0.048 0.009 0.003 0.006 0.097 0.034 0.063 0.009 0.003 0.006 0.029 0.010 0.019 0.77 0.27 0.50

Total cropland area ‡ NT-11

NT-20

———— Mg ha-1 ———— 122.8 111.8 119.2 111.0 83.3 98.6 59.0 49.2 57.2 135.7 127.6 106.8 93.2 88.8 89.9 96.2 68.8 93.2 119.8 109.0 116.3 180.7 146.4 166.4 33.4 27.0 30.7 111.0 83.3 98.6 96.2 68.8 93.2

NV

SCS by soil order ¶ Mg ha-1 0.98 0.98 0.60 0.55 0.55 0.55 0.44 0.80 0.40 0.98 0.80

C-Sequestration rate/soil order # NT

C added by NT ‡‡

—————— Tg —————— 28.66 27.21 3.85 5.69 4.78 0.85 1.58 1.46 0.27 1.22 1.03 0.08 18.55 17.82 1.84 3.32 2.92 0.32 8.79 8.34 0.55 1.66 1.46 0.12 3.25 2.86 0.66 0.95 0.80 0.14 2.82 2.48 0.40 76.48 71.17 9.08 2.04 7.47

NV

C storage by land use ††

† Area per soil order. ‡ Total cropland area per soil order = area per soil order * percent of cropland area of each soil order). § Area under NT: Total area = Total cropland area * 0.85 (85% of the cropland area is under NT), NT-11 area = cropland area under NT * 0.35 (35% of NT area in NT-11), NT-20 area = cropland area under NT * 0.65 (65% of NT area in NT-20). ¶ Soil C stock (SCS) by soil order for a 0- to 40-cm depth. # Carbon sequestration rate by each soil order obtained in the soil catena (Table 2). †† Carbon storage in NV and NT soils = (total cropland area * SCS stock NV or NT)/1000000) and for NT = ((NT-11 area * C Seq. rate by soil order * 11 yr * 0.35) + (NT-20 area * SCS stock NT-20 * C Seq. rate by soil order * 20 yr * 0.65))/1000000. ‡‡ Carbon added by NT = SUM of C added by each soil order. §§ Total C offset by NT = 9.08 * 0.225 (22.5%); Total CO2 offsetting by NT = 2.04 * 3.66.

% 85 85 85 55 55 55 45 45 45 45 45

Cropland area by Soil Order

Mha Oxisol, hc 0.323 Oxisol, c 0.071 Oxisol, sc 0.037 Inceptisol, hc 0.019 Inceptisol, c 0.426 Inceptisol, sc 0.074 Ultisol, sc 0.192 Histosol, sc 0.024 Entisol, s 0.234 Ultisol, hc 0.022 G-Histosol, sc 0.077 Total 1.52 Total C offset by NT (Tg of C) §§ Total CO2 offset by NT (Tg of CO2)

Soil Order

Area under NT §

Table 7. Estimation of C offset for a 0- to 40-cm depth by soils orders under NT (no-till) area in the Campos Gerais do Paraná, Southern Brazil. NT-11, NT practiced for 15 yr; NV, native vegetation.

those under NT-11 and 12% higher than those under NT-20. Soils under NT-20 contained 6% more C than those under NT11 indicating that longer period of NT is required for SCS to the level under NV. The long-term NT adoption such as NT-11 plus NT-20 can mitigate 33.2 Tg of CO2 or 22.5% of total CO2 emissions due to management. Thus, NT farming based on continuous crop residues input is a strong tool to restore SCS and offset CO2 emissions by farming operation.

Acknowlegements

We gratefully acknowledge the support of the ABC Foundation in providing the use of the database to develop this research project, as well as that of the Centre de Cooperation Internationale en Recherche Agronomique pour le Developpement–CIRAD and Food Agriculture Organization –FAO for financial support.

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