Integrated crop–pasture rotational systems can store larger soil organic carbon (SOC) stocks in the topsoil (0–20 cm) than continuous grain cropping. The aim of this study was to identify if the main determinant for this difference may be the avoidance of old C losses in integrated systems or the higher rate of new C incorporation associated with higher C input rates. We analyzed the temporal changes of 0–20 cm SOC stocks in two agricultural treatments of different intensity (continuous annual grain cropping and crop–pasture rotational system) in a 60-year experiment in Colonia, Uruguay. We incorporated this information into a process of building and parameterizing SOC compartmental dynamical models, including data from SOC physical fractionation (particulate organic matter, POM > 53 µm > mineral-associated organic matter, MAOM), radiocarbon in bulk soil, and CO₂ incubation efflux. This modeling process provided information about C outflow rates from pools of different stability, C stabilization dynamics, and the age distribution and transit times of C. The differences between the two agricultural systems were mainly determined by the dynamics of the slow-cycling pool (∼MAOM). The outflow rate from this compartment was between 3.68 and 5.19 times higher in continuous cropping than in the integrated system, varying according to the historical period of the experiment considered. The avoidance of old C losses in the integrated crop–pasture rotational system resulted in a mean age of the slow-cycling pool (∼MAOM) of over 600 years, with only 8.8 % of the C in this compartment incorporated during the experiment period (after 1963) and more than 85 % older than 100 years old in this agricultural system. Moreover, half of the C inputs to both agricultural systems leave the soil in approximately 1 year due to high decomposition rates of the fast-cycling pool (∼POM). Our results show that the high capacity to preserve old C of integrated crop–pasture systems is the key for SOC preservation of this sustainable intensification strategy, while their high capacity to incorporate new C into the soil may play a second role. Maintaining high rates of C inputs and relatively high stocks of labile C appear to be a prerequisite for maintaining low outflow rates of the MAOM pool.

The current guidelines and recommendations for P fertilization in Uruguay can be improved by adjusting the sampling depth and analytical methods of testing soil P in pastures with different fertilization history. A set of field trials was conducted between 2008 and 2012 on 14 sites of Uruguay for the purpose of comparing two sampling depths and three methods for assessing P availability by their correlation with annual dry matter yield response. The trials had a randomized complete block design and were sown with Trifolium repens or Lotus corniculatus. Soil P availability was determined by sampling 0-7.5 and 0-15 cm depth using three analytical methods: Bray I, cationic resins, and citric acid. Rock phosphate and triple superphosphate were applied at five P rates. (0-240 kg kg P2O5 ha-1). Annual forage yield was recorded. Relative yield was calculated as measured yield/maximum yield observed within a block. The correlation between relative yield and soil P availability was studied using the modified arcsine-logarithm calibration curve (ALCC) and analyzing the resulting correlation coefficient, root-mean-square error (RMSE) of the soil P test, and RMSE of the relative yield. The 0-7.5 cm soil sampling depth did not show a better fit than the deeper sampling (0-15 cm), with the latter having less variation in soil P test values. When rock phosphate was used, the correlation coefficients were 0.50 for cationic resins, 0.53 for citric acid, and 0.38 for Bray I. When triple superphosphate was used, the correlation coefficients were 0.37 for cationic resins, 0.44 for citric acid and 0.43 for Bray I. For both P sources, the citric acid method with the sampling of 0-15 cm soil depth is the preferred soil P test method for management of P in leguminous pastures for the soils studied.

In this article, we make comments on some methodological issues and on the general approach of the paper “Back to the future? Conservative grassland management can preserve soil health in the changing landscapes of Uruguay” (Säumel et al., 2023). We have identified several design and methodological problems in the aforementioned article that may induce potential misinterpretations. First, our concerns are related to aspects of the study design and methodology that, in our opinion, introduce biases and critical errors. Second, we are concerned about the possible interpretations of the study with respect to the design of policies and the development of non-tariff barriers for South American countries.

Integrated crop-pasture rotational systems can store larger amounts of soil organic carbon (SOC) than continuous grain cropping. The aim of this study was to identify if the main determinant for this difference may be the avoidance of old C losses in integrated systems, or the higher rate of new C incorporation associated with higher C input rates. We analyzed the evolution of SOC in two agricultural treatments of different intensity (continuous cropping and crop-pasture rotational system) in a 60-year experiment in Colonia, Uruguay. We incorporated this information into a process of building and parameterizing SOC compartmental dynamical models, including data from SOC physical fractionation (POM > 53 µm > MAOM), radiocarbon in bulk soil and CO₂ incubation efflux. This modeling process provided information about C outflow rates from pools of different stability, C stabilization dynamics, as well as the age distribution and transit times of C. The differences between the two agricultural systems were mainly determined by the dynamics of the stable pool (MAOM). The outflow rate from this compartment was between 3.62 and 5.10 times higher in continuous cropping than in the integrated system, varying according to the historical period of the experiment considered. The avoidance of old C losses in the integrated crop-pasture rotational system determined that only 8.8 % of the MAOM C was incorporated during the experiment period (after 1963) and that more than 85 % was older than 100 years old. Moreover, half of the C inputs to both agricultural systems leave the soil in approximately one year due to high decomposition rates of the POM pool. Our results show that the high capacity to preserve old C of integrated crop-pasture systems is the key for SOC preservation of this sustainable intensification strategy, while their high capacity to incorporate new C into the soil may play a second role.

Agricultural systems are under growing pressure, as soil degradation threatens food security and sustainable land use. Early detection through soil monitoring and precision agriculture is vital to prevent irreversible damage and enable timely conservation. This study evaluates a combined procedure based on electrical resistivity tomography and frequency-domain electromagnetic induction measurements, together with discrete soil sampling, to electrically characterize the soil, identify layers, and map the A horizon depth in a non-disturbing way. This work includes the design and implementation of a mounting electrode system, which reduces the installation time of electrical resistivity tomography surveys by 60% while maintaining data quality. The data were acquired in the oldest long-term agronomic experiment in South America, comprising seven rotation systems with three replicates each, totaling 21 rainfed plots, and representing contrasting management scenarios. Soil A horizon thickness maps of the entire experiment were obtained through two procedures. A comparison between mapping inputs, including all plots and only bare-soil plots, revealed minimal differences in unvegetated areas but notable discrepancies under plant cover, where vegetation increased fluctuations and noise. The present study provides a methodology for accurately assessing the spatial variability of the A horizon thickness by means of proximal sensing techniques. This contributes to the challenge of gathering fundamental soil information in a fast and cost-effective manner, critical for precision agricultura.