Flooded savannas are valuable and extensive ecosystems in South America, but not widely studied. In this study, we quantify the spatial distribution of soil organic carbon (SOC) content and stocks in the Casanare flooded savannas. We sampled 80 sites at two soil-depth intervals (0-10 and 10-30 cm), where SOC values ranged from 0.41% in the surface and 0.23% in the sub-surface of drier soils to over 14.50% and 7.51%, in soils that experienced seasonal flooding. Spatial predictions of SOC were done through two digital soil mapping (DSM) approaches: Expert-Knowledge (EK) and Random-Forest (RF). Although both approaches performed well, EK was slightly superior at predicting SOC. Covariates derived from vegetation cover, topography, and soil properties were identified as key drivers in controlling its distribution. Total SOC stocks were 55.07 Mt with a mean density of 83.1±24.3 t·ha^-1 in the first 30 cm of soil, with 12.3% of this located in areas that experience long periods of flooding (semi-seasonal savannas) , which represented only 7.9% of the study area (664,752 ha). Although the study area represents only 15% of the total area of the Casanare department, the intensive pressure of human development could result in the reduction of its SOC stocks and the release of important amounts of greenhouse gases into the atmosphere. At regional level, the impact of a large-scale land use conversions of the flooded Llanos del Orinoco ecosystem area (15 Mha) could transform this area in a future source of important global emissions if correct decisions are not taken regarding the land management of the region.

Autonomous selective spraying could be a way for agriculture to reduce production costs, save resources, protect the environment and help to fulfill specific pesticide regulations. The objective of this paper was to investigate the use of a low-cost sonar sensor for autonomous selective spraying of single plants. For this, a belt driven autonomous robot was used with an attached 3-axes frame with three degrees of freedom. In the tool center point (TCP) of the 3-axes frame, a sonar sensor and a spray valve were attached to create a point cloud representation of the surface, detect plants in the area and perform selective spraying. The autonomous robot was tested on replicates of artificial crop plants. The location of each plant was identified out of the acquired point cloud with the help of Euclidian clustering. The gained plant positions were spatially transformed from the coordinates of the sonar sensor to the valve location to determine the exact irrigation points. The results showed that the robot was able to automatically detect the position of each plant with an accuracy of 2.7 cm and could spray on these selected points. This selective spraying reduced the used liquid by 72%, when comparing it to a conventional spraying method in the same conditions.

Tropical grasslands can sequester substantial soil organic carbon (SOC), yet the temporal dynamics of SOC across soil layers—particularly in deep horizons—remain poorly understood at landscape scale. This study presents the first large-scale, stratified assessment of SOC stocks under Urochloa humidicola pastures in the Colombian Llanos. We evaluated SOC stocks and related soil properties (soil texture and bulk density) across pasture age classes (Uh 1, Uh 2, Uh 3, and Uh > 3 years), and compared them to conventionally managed, regularly burned savanna areas (CBS). Soil samples were collected from 111 georeferenced field sites at four depths (0–10 cm, 10–30 cm, 30–50 cm, and 50–100 cm), and SOC stocks were calculated using the equivalent soil mass (ESM) approach. Results revealed a consistent increment in both SOC concentration and SOC stocks with increasing pasture age. Total SOC stocks (0–100 cm) were up to 35% higher in older pastures (Uh > 3 years) compared to CBS, corresponding to an average gain of ~27 Mg C ha⁻¹. These gains were observed in both soil layers, with ~8.5 Mg C ha⁻¹ (19.5%) in the topsoil (0–30 cm) and ~14.8 Mg C ha⁻¹ (39%) in the subsoil (30–100 cm). Accumulated SOC tends to be more stable in these deeper soil layers. SOC concentration patterns align with these trends, supporting its use as an early indicator of soil improvement. Soil texture and hydrological (drainage) conditions influenced SOC concentration and stock changes, with clay-rich and water-retentive soils accumulated significantly more SOC than sandy-texture soils. These results highlight the climate mitigation potential of improved tropical pastures and the importance of stratified, depth-resolved monitoring of SOC stocks. U. humidicola pastures show progressive, spatially heterogeneous SOC gains, supporting the strategy of sustainable intensification of tropical grazing systems and their integration into carbon crediting mechanisms.

In this study, the spectral responses obtained from a Typic Red Hapludox (oxisol) were analyzed under different uses and occupations: Ficus elastica cultivation, Citrus + Arachis association cultivation, transitional crops, forest, Mangifera indica, Anacardium occidentale, Elaeis guineensis (18 years), Brachiaria decumbens, Brachiaria brizantha, and Musa × paradisiaca + Zea mays at the La Libertad Research Center in the department of Meta in Colombia (4°04′ North latitude, 73°30′ West longitude, 330 MAMSL). Sampling was performed with four random replicates of the horizon A and B to determine the contents of organic carbon (CO), pH, exchangeable acidity (Ac. I), cation exchange capacity (Cc), P, Ca, Mg, K, Na, sand, lime, and clay and spectral responses were obtained in the visible band (VIS), near infrared (NIR), and infrared (MIR) for each sample under laboratory conditions. A comparison was made between the obtained spectra, determining the main changes in soil properties due to their use and coverage. Variation of soil characteristics such as color, organic carbon content, presence of ferrous compounds, sand, silt, and clay content and mineralogy allow the identification of the main spectral changes of soils, demonstrating the importance of the use of reflectance spectroscopy as a tool of comparison and estimation between physical-chemical properties of the soils.

The extent and distribution of tropical peatlands, and their importance as a vulnerable carbon (C) store, remain poorly quantified. Although large peatland complexes in Peru, the Congo basin, and Southeast Asia have been mapped in detail, information on many other tropical areas is uncertain. In the Eastern Colombian lowlands, peatland area estimates range from 700 km² to nearly 60,000 km², leading to highly uncertain C stocks. Using new field data, high‐resolution Earth observation (EO), and a random forest approach, we mapped peatlands across Colombian territory East of the Andes below 400 m elevation. We estimated peatland extent using two approaches: a conservative method focused on medium‐to‐high peat probability areas and a more inclusive one accounting for large low‐probability areas. Multiplying these extents by below‐ground carbon density yields a conservative estimate of 0.95 (0.6–1.39 Pg C, 95% confidence interval) over 9,391 km² (7,369–11,549 km²) and up to 2.86 Pg C (1.76–4.22 Pg C) across 29,069 km² (22,429–36,238 km²). Among four potentially peat‐forming ecosystems identified, palm swamps and floodplain forests contributed most to the peat extent and C stock. We found that most peatland patches were relatively small, covering less than 100 ha. We compared our map to previously published global and pan‐tropical peat maps and found low spatial overlap among them, suggesting that peat maps uninformed by local field information may not precisely specify which landscape areas within a peatland‐rich region are actually peatlands. We further assessed the suitability of different EO and climate variables, highlighting the need for high‐resolution data to capture local heterogeneities in the landscape.

Flooded savannas are extensive in South America and this study was conducted to assess two digital soil mapping (DSM) approaches to predict the spatial distribution of soil organic carbon (SOC) content and stocks in the Orinoco flooded savannas of Casanare department, located in the eastern plains of Colombia. SOC was estimated using a total of 80 sites sampled at two soil depth intervals (0-10 cm and 10-30 cm). SOC ranged from 0.41% at 0-10 cm and 0.23% at 10-30 cm in drier soils found in continental dunes with sandy textures and low vegetation cover (steppe) to over 14.50% and 7.51% in soils that experienced seasonal flooding located in depressions with loamy textures and flooded savanna vegetation. Predictions of the spatial distribution of SOC were done through Expert Knowledge (EK) and Random Forest (RF) approaches across the study area at 0-10 cm and 10-30 cm soil depth. Both DSM approaches were assessed through root mean square errors, mean absolute errors, and coefficients of determination. Although both DSM approaches performed very well, EK was considered slightly superior to predict SOC in the Casanare flooded savannas. Covariates derived from vegetation coverage, topography, and soil texture properties were identified as key drivers in controlling its distribution at the study area. We found total SOC stocks of 55.07 Mt with a mean density of 83.13 ± 24.32 t ha-1 stored in the first 30 cm soil depth, with 12.3% of this being located in the flooded parts of the savanna landscape, which represented only 7.9% of the study area (664,752 ha). This study provides the first effort to systematically quantify SOC stocks in the Casanare flooded savannas and shows the importance of conserving this ecosystem with the aim of avoiding SOC losses and consequent increased CO2 emissions to the atmosphere. We estimate that the department of Casanare would release an average of 2,42 Mton of CO2 emissions per year over 30 years if there were large scale conversion of the flooded savannas to intensive agriculture, which corresponds to 62% of the current emissions of the department. At regional level, the impact of a large-scale land use conversion of the flooded Llanos del Orinoco ecosystem area (15 Mha) would represent 1/3 of the current net Colombian CO2 emission (AFOLU), which makes this region a potentially important source of emissions if correct decisions are not taken regarding the land management.