Gabriela Posse - Academia.edu (original) (raw)

Papers by Gabriela Posse

Enteric Methane Emission from Cattle Grazing Systems with Cover Crops and Legume–Grass Pasture, 2025

This study aims to quantify enteric methane (CH4) emission and dry matter intake (DMI) in beef st... more This study aims to quantify enteric methane (CH4) emission and dry matter intake (DMI) in beef steers under two rotational grazing systems: (i) a mixture of cover crops (vetch + ryegrass + forage radish) (CC) and (ii) alfalfa and fescue pasture (AFP). Eighteen Hereford steers were divided
into two groups (nine steers per group), assigned to either the CC or AFP. Methane emissions were measured using the SF6 tracer technique. The results showed that steers grazing CC produced 29% less CH4 in g/d compared to those on the AFP (119.1 vs. 167.1 g/d for CC and AFP, p < 0.05) and 36% less CH4 yield (4.3 vs. 6.7% of gross energy intake). However, average daily gain (ADG), DMI, and CH4 intensity (gCH4/kg ADG) did not significantly differ between treatments. The integration of
CC in a cattle grazing system has the potential to reduce CH4 emissions by improving forage quality.

Spatial variability of nitrous oxide emissions from croplands and unmanaged natural ecosystems across a large environmental gradient, 2024

Atmospheric nitrous oxide (N2O) is a potent greenhouse gas, with long atmospheric residence time ... more Atmospheric nitrous oxide (N2O) is a potent greenhouse gas, with long atmospheric residence time and a global warming potential 273 times higher than CO2. N2Oemissions are mainly produced from soils and are influenced by biotic and abiotic factors that can be substantially altered by anthropogenic activities, such as land uses, especially when unmanaged natural ecosystems are replaced by croplands or other uses. In this study, we evaluated the spatial variability of N2O emissions from croplands
(maize, soybean, wheat, and sugar cane crops), paired with the natural grasslands or forests that they replaced across a wide environmental gradient in Argentina, and identified the key drivers governing the spatial variability of N2O emissions using structural equation modeling. We conducted on-farm field measurements over 2 years at nine different sites, including a wide environmental gradient (mean rainfall
from 679 to 1090 mm year−1 and mean temperatures from 13.8°C to 21.3°C), with diverse plant species life forms, and ecosystems, from the Semiarid Chaco forests in the Northwest of Argentina to the Pampas grasslands in the Southeast. On average, agricultural systems emitted more than twice N2O (+120%), had higher soil water content (+9%), higher soil temperatures (+3%), higher soil nitrate content (+19%) but lower ammonium (−33%) than natural ecosystems. We found that land use was
the main driver of N2O emissions by directly affecting soil NO3 − contents in both natural ecosystems and croplands. Urgent management practices aimed at reducing N2O emissions from croplands are needed to mitigate their contributions to global climate change.

Social Science Research Network, 2023

Precipitation in semi-arid countries such as Iran is one of the most important elements for all a... more Precipitation in semi-arid countries such as Iran is one of the most important elements for all aspects of human life. In areas with sparse ground-based precipitation observation networks, the reliable high spatial and temporal resolution of satellite-based precipitation estimation might be the best source for meteorological and hydrological studies. In the present study, four different satellite rainfall estimates (CMORPH, PERSIANN, adjusted PERSIANN, and TRMM-3B42 V6) are evaluated using a relatively dense Islamic Republic of Iran's Meteorological Organization (IRIMO) rain-gauge network as reference. These evaluations were done at daily and monthly time scales with a spatial resolution of 0.25 Â 0.25 latitude/longitude. The topography of Iran is complicated and includes different, very diverse climates. For example, there is an extremely wet (low-elevation) Caspian Sea coastal region in the north, an arid desert in the center, and high mountainous areas in the west and north. Different rainfall regimes vary between these extremes. In order to conduct an objective intercomparison of the various satellite products, the study was designed to minimize the level of uncertainties in the evaluation process. To reduce gauge uncertainties, only the 32 pixels, which include at least five rain gauges, are considered. Evaluation results vary by different areas. The satellite products had a Probability of Detection (POD) greater than 40% in the southern part of the country and the regions of the Zagros Mountains. However, all satellite products exhibited poor performance over the Caspian Sea coastal region, where they underestimated precipitation in this relatively wet and moderate climate region. Seasonal analysis shows that spring precipitations are detected more accurately than winter precipitation, especially for the mountainous areas all over the country. Comparisons of different satellite products show that adj-PERSIANN and TRMM-3B42 V6 have better performance, and CMORPH has poor estimation, especially over the Zagros Mountains. The comparison between PER-SIANN and adj-PERSIANN shows that the bias adjustment improved the POD, which is a daily scale statistic.

Journal of Environmental Management, Nov 1, 2022

HAL (Le Centre pour la Communication Scientifique Directe), Nov 6, 2013

Daily actual evapotranspiration (AET) and seasonal AET values are of great practical importance i... more Daily actual evapotranspiration (AET) and seasonal AET values are of great practical importance in the management of regional water resources and hydrological modeling. Remotely sensed AET models and Landsat satellite images have been used widely in producing AET estimates at the field scale. However, the lack of validation at a high spatial frequency under different soil water conditions and vegetation coverages limits their operational applications. To assess the accuracies of remote sensing-based AET in an oasis-desert region, a total of 59 local-scale daily AET time series, simulated using HYDRUS-1D calibrated with soil moisture profiles, were used as ground truth values. Of 59 sampling sites, 31 sites were located in the oasis sub-area and 28 sites were located in the desert sub-area. Additionally, the locally validated METRIC (Mapping Evapotranspiration at High Resolution with Internalized Calibration) surface energy balance model was employed to estimate instantaneous AET values in the area containing all 59 of the sampling sites using seven Landsat sub-images acquired from June 5 th to August 24 th in 2011. Daily AET was obtained using extrapolation and interpolation methods with the instantaneous AET maps. Compared against HYDRUS-1D, the remote sensing-based method produced reasonably similar daily AET values for the oasis sites, while no correlation was observed for daily AET estimated using these two methods for the desert sites. Nevertheless, a reasonable monthly AET could be estimated. The correlation analysis between HYDRUS-1D-simulated and remote sensing-estimated monthly AET values showed relative root-mean-square error (RRMSE) values of 15.1%, 12.1% and 12.3% for June, July and August, respectively. The RRMSE of the summer AET was 10.0%. Overall, remotely sensed models can provide This article is protected by copyright. All rights reserved. reasonable monthly and seasonal AET estimates based on periodic snapshots from Landsat images in this arid oasis-desert region.

Soil Use and Management, Nov 6, 2018

The increase in atmospheric GHGs can be mitigated by capturing CO 2 from the atmosphere and/or by... more The increase in atmospheric GHGs can be mitigated by capturing CO 2 from the atmosphere and/or by reducing their emissions. Replacing winter intercrop fallow by cover crops (CCs) can sequester carbon and improve nitrogen use efficiency under proper management. We monitored two cycles of a cash crop namely soybean (soy1) and double cropping soybean (soy2) and their respective post-harvest periods. During the first period, a winter crop (wheat) was used as an alternative to CCs and in the second period a chemical fallow treatment (bare soil) was applied. CO 2 and N 2 O exchange rates were estimated with turbulent flux measurements, and N 2 O fluxes with complementary static chambers. During the soy1 / wheat sequence, the soil gained 2800 kg C eq ha-1 , while during the soy2 / bare fallow sequence the soil lost 5083 kg C eq ha-1. Excluding the carbon exported by harvest, both sequences lost carbon, but the soy2 / bare fallow cycle was five-fold higher. The replacement of bare fallow by a winter cover crop like wheat decreases N 2 O emissions considerably and converts carbon losses (by respiration) into gains (by fixation in photosynthesis). The replacement of traditional non-harvested cover crops by winter wheat may provide not only similar advantages in terms of soil improvement, preservation and reduction in nitrogen loss, but also an additional harvest. It will be necessary to adjust the fertilization of this cover crop to prevent excess nitrogen from accumulating in soils.

Soil & Tillage Research, Jun 1, 2017

The estimation of the GHG balance of agroecosystems is essential to evaluate the impact of agricu... more The estimation of the GHG balance of agroecosystems is essential to evaluate the impact of agriculture on the composition of the atmosphere. Cultivated soils may act as a sink or a source of CO 2 and usually emit N 2 O. The aim of the present study was to assess the CO 2 and N 2 O balances, and to analyze the relationships between N 2 O fluxes and environmental variables for two soybean growing seasons and the fallow period between them, in an agricultural field in the Pampas region of Argentina. The fluxes of CO 2 and N 2 O were measured by the eddy covariance and the static-chamber methods, respectively. The net ecosystem exchange from sowing to harvest was À2543 and À2307 kg CO 2-C ha À1 , for the first and second growing seasons, respectively. The N 2 O net balance over the same periods was 1.45 and 0.96 kg N 2 ON ha À1. A multivariate analysis showed that during the growing season the most important variable influencing N 2 O emission was % water filled pore space (% WFPS), followed by nitrate content and soil temperature. During fallow, soil temperature was the main control factor, followed by % WPFS. The total balance (including CO 2 and N 2 O) showed that the soil gained 753.5 kg Ceq ha À1 on average during cultivarion cycle. Taking into account the fallow period, the global balance resulted in a carbon loss of 1328.5 kg Ceq ha À1 over about one year. Our results clearly indicate the need to incorporate winter cover crops for improving the production system, as they can provide carbon to the soil and use the available stubble nitrogen from the previous crop.

OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information), 2022

Communications in Soil Science and Plant Analysis, Feb 1, 1995

We studied the response curves of Dactylis glomerata to addition of nitrogen (N), potassium (K), ... more We studied the response curves of Dactylis glomerata to addition of nitrogen (N), potassium (K), and lime in presence of a range of added phosphorus (P) on an acid xeric heath soil (pH 4.3) of Tierra del Fuego (Argentina). The heath community developed on the soil has dominated by a 50% of cover of an evergreen dwarf shrub (Empetrum rubrum)

International Journal of Environment and Pollution, 2015

Turbulence data measured with fast response instruments at two sites with distinct conditions wer... more Turbulence data measured with fast response instruments at two sites with distinct conditions were available. The ability of a mesoscale model in the simulation of turbulent fluxes and boundary layer height was assessed in case studies covering periods in the Southern Hemisphere summer and winter. The energy apportionment at both locations was properly reproduced. In summer, at the site with native forest, the sensible heat flux was well estimated and the latent heat flux was underestimated. At the other site (commercial plantation) the sensible heat flux was properly represented and the latent heat flux was slightly overestimated. In winter, the best results were obtained at the implanted forest site. The performance of the model at the native forest site was very satisfactory when homogeneous initial soil moisture was considered. A model intercomparison between the boundary layer height obtained with an analytical model and the mesoscale model showed the influence of data and methodologies used in the two approaches.

Applied Vegetation Science, 2005

How do meteorological variations at seasonal, interannual scales differentially affect the canopy... more How do meteorological variations at seasonal, interannual scales differentially affect the canopy dynamics of four contrasting landscape units within a region? Location: Flooding Pampa, Buenos Aires, Argentina. 5000 km 2. Central point: 35°15' S, 57°45' W. Methods: We used a 19-year series of the normalized difference vegetation index (NDVI) derived from NOAA-AVHRR PAL (Pathfinder AVHRR Land) images and meteorological data provided by a nearby weather station. The NDVI was used as surrogate of canopy photosynthetic status. The relationship between annually integrated NDVI and meteorological conditions was explored by stepwise multiple regressions for each defined unit. PCA was performed to compare units and growing seasons on a multivariate basis. Results: Mean seasonal NDVI curve was similarly shaped among landscapes. However, the absolute values differed widely. There was high interannual variation so that the mean seasonal pattern was seldom observed in any particular year. Annually integrated NDVI of all landscapes was negatively associated with summer temperature and positively with previous year precipitation. It was also directly related with current year winter precipitation in two landscapes and with summer precipitation in the others. NDVI response to September and March precipitation accounted for some of the differences in interannual variation among landscapes. Conclusions: Our results revealed a strong intra-regional variation of canopy dynamics, closely linked to landscape (vegetation-soil) and water availability (mainly in summer and during the previous year). These links may be used to predict forage production rates for livestock.

Applied Vegetation Science, 2004

Question: How well does the use of NDVI predict secondary productivity at landscape scales? What ... more Question: How well does the use of NDVI predict secondary productivity at landscape scales? What is the influence of vegetation quality and phenology over secondary productivity? Location: Magellanic steppe in Tierra del Fuego, Argentina. (52°45' to 54° S, 68°15' to 67°30' W). Methods: Monthly and yearly integrated NDVI (NDVI-I) were calculated from AVHRR/NOAA 14, as estimators of phenology and aerial net primary productivity respectively. From a vegetation map we obtained the proportional cover of different physiognomic types and calculated the palatable fraction (forage) productivity that were used as estimators of vegetation quality. Data were analysed through correlations and regressions. Results: NDVI-I was not related with secondary productivity indices, while December and annual maximum NDVI, proportion of lawns and tussock grasslands and forage productivity were positively related with secondary productivity. A negative relationship was found between the proportion of heathlands and secondary productivity, but a positive relationship between heathland's proportion and NDVI-I was found. Conclusions: NDVI-I is not a good predictor of secondary productivity at the scale of our study. These results could be due to: (1) NDVI-I is not related to primary productivity and (2) primary productivity is not related to secondary productivity.

Applied Vegetation Science, Dec 1, 2000

We analysed vegetation dynamics in Tierra del Fuego steppes using Normalized Difference Vegetatio... more We analysed vegetation dynamics in Tierra del Fuego steppes using Normalized Difference Vegetation Index (NDVI) data provided by advanced very high-resolution radiometer (AVHRR) on board the National Oceanic and Atmospheric Administration (NOAA) polar satellite. Our objective, at a regional scale, was to analyse the spatial variability of NDVI dynamics in relation to parent material and geographic location, representing the fertility and climate gradients respectively; at a local scale, it was to analyse the inter-annual variability associated with climate and its relation with sheep production indices. The general pattern of NDVI dynamics was analysed with Principal Component Analysis. We found that the geographic location was more important than landscape type in explaining NDVI dynamics despite the fact that the variation in landscape type reflects a fertility gradient strongly associated with floristic composition and secondary productivity. Discriminant Analysis was performed to identify the variables that better distinguish geographic units. The Northern region (with the lowest precipitation and the highest temperatures) had lower NDVI values over the year. In the Central region, NDVI reached the highest value of the season, surpassing both other regions. The Southern region (the coldest and moistest) had its growth pattern displaced towards the summer. For the Central region we analysed 10 years of monthly NDVI data with PCA. We found that precipitation from August to December and winter temperature are the most important determinants of overall NDVI values. Lamb production was correlated with spring and early summer NDVI values. Sheep mortality is affected by low NDVI values in late summer and high annual amplitude. Satellite information allowed us to characterize the vegetation dynamics of three ecological areas across the Fuegian steppe.

Science of The Total Environment, Jun 1, 2017

Nitrous oxide (N 2 O) is the main greenhouse gas emitted from farming systems and is associated w... more Nitrous oxide (N 2 O) is the main greenhouse gas emitted from farming systems and is associated with nitrogen (N) fertilizer application as well as decomposition of organic matter present in the environment. The objective of this study was to determine the effect of post-harvest straw burning and synthetic N fertilization on the dynamics of N 2 O emissions in the sugarcane-soil system in Tucuman, Argentina, compared with a native forest. Close-vented chambers were used to capture N 2 O during three consecutive growing seasons. The highest N 2 O emissions from the sugarcane-soil system coincided with the period of high soil and air temperatures, rainfall and soil N content. The effect of synthetic N fertilization on annual cumulative N 2 O emission was 7.4-61.5% higher in straw burned than in unburned treatments, especially during a wet growing season. There was a significant effect of treatments on N 2 O emission factors among growing seasons: 0.58-1.67% and 0.94-3.34% in the unburnt and burnt treatments, respectively. The emission factors for sugarcane are highly dependent on rainfall, temperature and crop management practices; regarding the latter, avoiding straw burning and reducing N soil availability, assessing alternative N fertilizers or new application modes such as split rates, seem to be the key for mitigating N 2 O emissions from the sugarcane-soil system in Tucumán, Argentina.

According to the Paris Agreement 2015, increased carbon sequestration by soils is a vital option ... more According to the Paris Agreement 2015, increased carbon sequestration by soils is a vital option for climate change mitigation and, simultaneously, improves soil health and food security. Agricultural soils are globally depleted in soil organic carbon and, therefore, exhibit a high potential for carbon sequestration. Various agroecological practices aim to increase or maintain soil organic carbon through increasing carbon inputs in the soil (e.g., amendments, plant residues, cover crops) and/or through reducing carbon losses (e.g., reduced or no tillage, adapted grazing). However, these practices have the potential to increase greenhouse gas emissions, which limits their effectiveness in terms of climate change mitigation. The EJP-SOIL project TRUESOIL (2022-2025) studies trade-offs between agricultural management practices aiming at increasing carbon sequestration and reducing greenhouse gas emissions from agroecosystems across crops, soil properties and climates. TRUESOIL investig...

Frontiers in Soil Science

Estimations of Net Ecosystem Exchange (NEE) are crucial to assess the carbon sequestration/carbon... more Estimations of Net Ecosystem Exchange (NEE) are crucial to assess the carbon sequestration/carbon source capacity of agricultural systems. Although several global models have been built to describe carbon flux patterns based on flux tower data, South American ecosystems (and croplands in particular) are underrepresented in the databases used to calibrate these models, leading to large uncertainties in regional and global NEE estimation. Despite the fact that almost half of the land surface is used worldwide for agricultural activities, these models still do not include variables related to cropland management. Using enhanced vegetation index (EVI) derived from MODIS imagery (250 m) and monthly CO2 exchange from a 9-year record of an eddy covariance (EC) flux tower in a crop field in the Inland Pampas region, we developed regression models to predict monthly NEE. We tested whether including a term for crop identity/land cover as a categorical variable (maize, soybean, wheat, and fall...

Water Resources Research, 2021

Many remote sensing‐based evapotranspiration (RSBET) algorithms have been proposed in the past de... more Many remote sensing‐based evapotranspiration (RSBET) algorithms have been proposed in the past decades and evaluated using flux tower data, mainly over North America and Europe. Model evaluation across South America has been done locally or using only a single algorithm at a time. Here, we provide the first evaluation of multiple RSBET models, at a daily scale, across a wide variety of biomes, climate zones, and land uses in South America. We used meteorological data from 25 flux towers to force four RSBET models: Priestley–Taylor Jet Propulsion Laboratory (PT‐JPL), Global Land Evaporation Amsterdam Model (GLEAM), Penman–Monteith Mu model (PM‐MOD), and Penman–Monteith Nagler model (PM‐VI). was predicted satisfactorily by all four models, with correlations consistently higher () for GLEAM and PT‐JPL, and PM‐MOD and PM‐VI presenting overall better responses in terms of percent bias (%). As for PM‐VI, this outcome is expected, given that the model requires calibration with local data. ...