Universidad del Rosario

Wildfires play a key role in the Earth system by shaping ecosystem dynamics and influencing the carbon cycle and atmospheric composition. Data-driven models have recently emerged as powerful tools for reproducing observed fire activity, particularly burned area, across a range of spatial and temporal scales. The first version of BuRNN (Burned area and emissions modelling through Recurrent Neural Networks) focused solely on burned area and outperformed all process-based fire-coupled DGVMs from ISIMIP over a wide range of spatial, temporal and spatio-temporal skill metrics. Here we present the 2nd version of BuRNN, a data-driven model that now jointly represents burned area and fire-related emissions.

Abstract Life can be unstable. This is especially true for seedlings growing on erodible surfaces, such as newly exposed areas after glacier retreat. Here we used a space-for-time approach to study the role of biological soil crust (biocrust) as surface stabilizer and facilitator of ecological succession along a glacier forefield chronosequence at the retreating Conejeras glacier in the Tropical Andes. We used the point-intercept method to estimate surface cover of plants, biocrust, bare ground and rocks, as well as surface roughness; and a field soil aggregate kit to estimate soil stability. As hypothesized, following a bare-ground stage near the edge of the glacier, the successional trajectory involved the development of a biocrust belt, including bryophytes and lichens, followed by an increasing vascular plant cover in more advanced successional stages. The development of biocrust was accompanied by higher roughness and stability, which likely increased seed entrapment and seedling establishment. Our results suggest that the development of cyanobacterial-dominated biocrust at the forefield of the Conejeras glacier may favor the establishment of plants with large seeds, such as graminoids from the Festuca genus. Overall, our findings highlight the key role of biocrusts in the ecological dynamics that follow glacier melt in the Tropical Andes.

Purpose. To analyze the economic situation of print press in Colombia during 2016-2024. Method. Quantitative study based on the analysis of financial statements of three national newspapers, seven regional newspapers, and one weekly magazine, using data from the Integrated Financial Information System of the Superintendence of Companies. Seven financial indicators were examined: assets, revenues, net profits, gross margins, return on assets, return on equity, and return on sales, through the application of trend analysis techniques and temporal comparison. Results. The findings reveal widespread decapitalization of assets in most print mass media, structural contraction of revenues, and negative net profits with high volatility during the analyzed period. The year 2020 represented a critical inflection point due to the pandemic. A marked difference was identified between national media, which maintain greater survival capacity, and regional media, which face a much more severe crisis, with risk of closure or elimination of print versions. Conclusions. The print media sector is experiencing a profound economic crisis, characterized by advertising migration toward digital platforms and the inability to generate new revenue sources, particularly threatening the sustainability of regional media. Original contributions. First empirical documentation of the financial deterioration of the Colombian press sector based on official data, with quantitative identification of the asymmetry in the crisis's impact between national and regional media, evidencing the risk of media concentration and news deserts.

Giardia lamblia is a globally prevalent gastrointestinal parasite. Breastfeeding provides protective effects against infections, but the impact of early life stress, such as maternal separation, on G. lamblia infection remains unclear. This study examines how Maternal Separation During Breastfeeding (MSDB) affects G. lamblia infection in Wistar rats. In a Wistar rat model, MSDB led to a significant increase in G. lamblia cyst shedding, with early effects more evident in males and delayed effects in females. Additionally, infected MSDB rats showed elevated eosinophil infiltration in the intestinal mucosa-consistent with heightened immune response-along with altered villus/crypt ratios in non-infected separated animals, particularly in males. Our findings demonstrate that maternal separation during breastfeeding intensifies the severity of G. lamblia infection. This suggests that early-life maternal interactions may play a protective role in host resistance specifically against G. lamblia, highlighting the relevance of early-life conditions in shaping outcomes of giardiasis.

El artículo examina la definición de “víctima” contenida en la Ley 1448 de 2011 o Ley de Víctimas (art. 3), y ofrece una reflexión crítica sobre la necesidad de implementar el numeral 6.1.10 del Acuerdo Final de Paz que comprometió al Estado con la modificación de dicha definición para suprimir la exclusión que se impuso a los miembros de los grupos armados en Colombia. A diferencia del tratamiento que la ley de víctimas otorga a los miembros de las fuerzas armadas oficiales, y en contravía a lo señalado en el estándar internacional en la materia, la señalada exclusión impide a los miembros de grupos armados ser reconocidos como eventuales víctimas del conflicto armado en los casos en los que hubiesen sido objeto de graves infracciones al Derecho Internacional Humanitario. A efectos de mostrar la importancia de la referida modificación y el posible tamaño del subregistro que está generando la norma vigente, el artículo recupera los resultados del censo de excombatientes de FARC-EP residentes en Bogotá que, como resultado de interés, resaltó que el 76% de los encuestados se consideró como posible víctima de alguna infracción al DIH en el marco del conflicto armado colombiano

Abstract. Fires play an important role in the Earth system but remain complex phenomena that are challenging to model numerically. Here, we present the first version of BuRNN, a data-driven model simulating burned area on a global 0.5° × 0.5° grid with a monthly time resolution. We trained Long Short-Term Memory networks to predict satellite-based burned area (GFED5) from a range of climatic, vegetation and socio-economic parameters. We employed a region-based cross-validation strategy to account for the high spatial autocorrelation in our data. BuRNN outperforms the process-based fire models participating in ISIMIP3a on a global scale across a wide range of metrics. Regionally, BuRNN outperforms almost all models across a set of benchmarking metrics in all regions. Through explainable AI we unravel the difference in regional drivers of burned area in our models, showing that the presence/absence of bare ground and C4 grasses along with the fire weather index have the largest effects on our predictions of burned area. Lastly, we used BuRNN to reconstruct global burned area for 1901–2019 and compare the simulations against independent long-term historical fire observation databases in five countries and the EU. Our approach highlights the potential of machine learning to improve burned area simulations and our understanding of past fire behaviour.