Río de la Plata Grasslands, Southern Pampa
(Pilot site 1)

Team leaders: Prof. Dr. Martín Oesterheld, Dr. Mariano Oyarzabal

IFEVA, Laboratory of Regional Analysis and Remote Sensing, Faculty of Agronomy, University of Buenos Aires/CONICET.

 Project Overview

Our initiative is providing forage productivity data to the Argentinean livestock community to regularly monitor in real-time the condition of the rangelands and pasture lands at paddock, landscape and national levels (http://produccionforrajes.org.ar/).

Our specific objective in the Southern Pampa is to develop and upgrade a system that routinely estimates forage above-ground net primary production (ANPP) at the spatial and temporal resolution required by farmers, and to facilitate adoption of the system by end users as a managerial support tool (Grigera et al. 2007). Our approach is based on the radiation use efficiency (RUE) logic, which proposes that ANPP is determined by the amount of photosynthetically active radiation absorbed by the canopy (APAR), and the efficiency with which that energy is transformed in above-ground dry matter (radiation use efficiency, RUE). APAR is the product of incoming photosynthetically active radiation (PAR) and the fraction absorbed by the canopy (fPAR). We estimated fPAR as a non-linear function of MODIS normalized difference vegetation index (NDVI). RUE was empirically estimated for the two principal forage resources of the region, yielding the following relations: ANPP = 0.6 · APAR + 12, (R² = 0.86; p < 0.001; n = 18) for the upland sown pastures, and ANPP = 0.27 · APAR + 26, (R² = 0.74; p < 0.001; n = 18) for the lowland naturalized pastures, with ANPP in g/m²/60 days and APAR in MJ/m²/60 days (Grigera et al. 2007).

Collaboration & Stakeholder involvements

The project has a very strong collaborative environment within which to operate. It has been framed with long standing and regular consultation with national agencies:

• INTA, Spanish acronym for “Instituto Nacional de Tecnología Agropecuaria”;
• Minagri, for “Ministerio de Agroindustria de la Nación”;
• IPCVA for “Instituto de Promoción de la Carne Vacuna Argentina”);
• AACREA, for ‘‘Argentine Association of Regional Consortia of Agricultural Experimentation’’, a national consortium of farmers.

Main contact point

Mariano Oyarzabal (oyarzabal(at)agro.uba.ar)
LART – IFEVA, Facultad de Agronomía UBA,
Av. San Martín 4453,
C1417DSE  Buenos Aires
ARGENTINA

Site description

The project is focused on the extensive native grassland areas of the southernmost unit of the Río de la Plata Grasslands region, the Southern pampa. The unit includes the mountains of the Tandilia and Ventania Systems, as well as their pediments and the coastal plain with a moderate slope to the Atlantic ocean. The fluvial network is well defined and the area as a whole is exoreic. There are rock outcrops and deep soils in the alluvial fans; over a large part of this area silt deposits overlie a continuous limestone sheet, lying at a depth varying from 0.5 and 2 m (Soriano et al. 1991). Climate is temperate sub-humid. Mean annual precipitation ranges from 800 to 900 mm. Precipitation is more abundant in spring and summer (70%). Droughts are relatively common in winter, as a result of extremely low precipitation, but they may also take place in summer due to high evapotranspiration. Mean monthly temperature ranges from 7 to 9 ºC in July to 21–22 ºC in January. About 35 frost events occur between May and September, but both forage production and grazing occur year round. Mollisols are the dominant soils and they are often limited by a petrocalcic horizon, flooding, or alkalinity (Grigera et al. 2007).

Landscape-level heterogeneity consists of a mosaic of two topographical levels subjected to different water and salinity regimes, and concomitantly, to different land use. The upland position is typically under a 4 – 4 year pasture-crop rotation. Upland sown pastures are typically composed of Festuca arundinacea, Dactylis glomerata and Lolium multiflorum as grasses, and Medicago sativa, Trifolium pratense and Trifolium repens as legumes. During the cropping period of the rotation, winter crops are wheat and barley, and summer crops are sunflower, soybean and, to a lesser extent, corn (Pacin & Oesterheld 2014). The lowland position is frequently occupied by Tall wheatgrass (Agropyron elongatum = Elytrigia elongata) naturalized pastures or by natural grasslands co-dominated by C₃ and C₄ grasses of the genus Stipa, Piptochaetium, Briza, Paspalum, and Botriochloa (Grigera et al. 2007).

The farms under study are members of a national consortium of farmers (AACREA) whose objectives are to achieve profitable and sustainable agricultural enterprises by exchanging experiences and testing technologies, and to transfer that knowledge to contribute to the country’s development. This consortium is organized in groups with 10 members (farms) each. Members of a group share an advisor that makes monthly 1-day visits to each farm, and organizes monthly group meetings in a host farm that rotates every month. Meetings have a standard format that basically consists of evaluating each farm in relation to animal nutrition (state of forage resources), crop condition, and the principal productive activities they are developing. Particular attention is paid to the host farm, including a thorough tour and further criticism. This intense interaction generally results in farms having similar management: in relation to livestock production, they use rotational grazing all around the year with variable outdoor supplementation during winter, especially for fattening steers (Grigera et al. 2007).

In-situ Observations

 

Fig. 2: Calibration between ground estimations of ANPP and MODIS-derived APAR. Each data point is the average APAR and ANPP, in each date, of the four sites of Fig. 1 (Grigera etal. 207)

Month	ANPP (kg/ha)	n (paddocks)	Spatial variability (standard deviation between paddocks; kg/ha)	n (years)	Interannual variability (standard deviation between years; kg/ha)
1	627	1077	290	8	240
2	603	1077	234	8	207
3	622	1129	218	8	253
4	488	1129	152	8	185
5	316	1129	87	8	97
6	243	1122	73	8	67
7	251	1132	77	8	66
8	323	1132	109	8	115
9	522	1132	189	8	212
10	893	1128	270	8	319
11	945	1128	349	8	400
12	658	1126	250	8	262

Fig. 3: Average monthly estimates of ANPP for all paddocks with upland sown pastures of the Lamadrid AACREA group in the Southern Pampa region. Estimations were derived from the amount of photosynthetically active radiation absorbed by the canopy (APAR), and the efficiency with which that energy is transformed in above-ground dry matter (radiation use efficiency, RUE). Number of paddocks, spatial variability (standard deviation between paddocks), average number of years considered, and interannual variability (standard deviation between years) are also indicated. ANPP annual, as the sum of average monthly estimates, was 6491 kg/ha, and the coefficient of variation between months was 43 % (https://sites.google.com/a/agro.uba.ar/ipcva-fauba/home/resumen-de-datos-e-informacion/cortes/indice-general/27-pastura-poliftica)

 

Month	ANPP (kg/ha)	n  (paddocks)	Spatial variability (standard deviation between paddocks; kg/ha)	n  (years)	Interannual variability (standard deviation between years; kg/ha)
1	409	598	88	10	22
2	376	598	67	10	36
3	444	598	79	10	69
4	362	598	59	10	118
5	252	599	27	10	169
6	207	598	18	10	124
7	209	600	17	10	138
8	232	600	24	10	87
9	299	600	44	10	106
10	458	600	90	10	84
11	500	600	106	10	37
12	416	600	73	10	29

Fig. 4: Average monthly estimates of ANPP for all paddocks with lowland naturalized pastures of the Lamadrid AACREA group in the Southern Pampa region. Estimations were derived from the amount of photosynthetically active radiation absorbed by the canopy (APAR), and the efficiency with which that energy is transformed in above-ground dry matter (radiation use efficiency, RUE). Number of paddocks, spatial variability (standard deviation between paddocks), average number of years considered, and interannual variability (standard deviation between years) are also indicated. ANPP annual, as the sum of average monthly estimates, was 4164 kg/ha, and the coefficient of variation between months was 30 % (https://sites.google.com/a/agro.uba.ar/ipcva-fauba/pseudoestepa-de-mesofitas-y-estepa-arbustiva-27)

EO Data requirements

• MODIS
• EO-1 Hyperion
• Landsat 5–TM
• Landsat-7 +ETM
• Landsat-8
• VIIRS reflectance and products when available
• Sentinel

Location

 

Project – Source material

Grigera, G., M. Oesterheld, M. Durante, and F. Pacín. 2007. Evaluación y seguimiento de la productividad forrajera. Revista Argentina de Producción Animal 27:137-148.

Grigera, G., Oesterheld, M., Pacín, F., 2007. Monitoring forage production for farmers’decision making. Agric. Syst. 94, 637–648.

Oesterheld, M., G. Grigera, and F. Pacín. 2006. Capítulo 5. Nuevos métodos de evaluación de forrajes y de respuesta animal. Uso del Índice Verde para estimar la producción forrajera. in Revista de los CREA.

Oyarzabal, M., M. Oesterheld, and G. Grigera. 2011. ¿Cómo estimar la eficiencia en el uso de la radiación mediante sensores remotos y cosechas de biomasa? Pages 121-133 in A. Altesor and J. M. Paruelo, editors. Pastizales naturales: Bases ecológicas para su manejo. Marcos conceptuales e investigaciones sobre la estructura y el funcionamiento de los pastizales naturales y de su aprovechamiento en sistemas ganaderos extensivos. Instituto Nacional de Investigación Agropecuaria, Montevideo.

Oyarzabal, M., M. Oesterheld, J. M. Paruelo, and F. Pacín. 2012. Seguimiento satelital del forraje: bases y aplicaciones. . Pages 28 in F. O. M. y. P. Preliasco., editor. Buenas prácticas para una ganadería sustentable de pastizal: kit de extensión para las pampas y campos. Fundación Vida Silvestre Argentina; Aves Argentinas/AOP, Buenos Aires.

Pacín, F., Oesterheld, M., 2014. In farm diversity stabilizes return on capital. Agric. Syst. 124, 51–59.

Pacín, F., Oesterheld, M., 2015. Closing the technological gap of animal and crop production through technical assistance. Agric. Syst. 137:101–107

Paruelo, J. M., M. F. Garbulsky, J. P. Guershman, and M. Oesterheld. 1999. Caracterización regional de los recursos forrajeros de las zonas templadas de Argentina mediante imágenes satelitarias. Revista Argentina de Producción Animal 19:125-131.

Paruelo, J. M., M. Oesterheld, C. M. Di Bella, M. Arzadum, J. Lafontaine, M. Cahuepé, and C. M. Rebella. 2000. Estimation of primary production of subhumid rangelands from remote sensing data. Applied Vegetation Science 3:189-195.

Piñeiro, G., M. Oesterheld, and J. M. Paruelo. 2006. Seasonal variation in aboveground production and radiation use efficiency of temperate rangelands estimated through remote sensing. Ecosystems 9:357-373.