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Xylem sap flow measurement is a key method to quantify plant water use and assess the responses to environmental conditions and climatic change. However, available methods are generally invasive and of limited portability. This paper presents a non-invasive approach called TIMFLOW that combines microwave heat pulse and infrared thermography, while having a high portability and versatility potential. The methodology was tested in laboratory conditions for black poplar (Populus nigra) stems of various diameters (10–45 mm) and for the known sap flow velocity range (10–100 cm h−1). The heat pulse was generated by microwaves with a power amplifier supplying a bi-quad antenna at 2.45 GHz frequency located near the stem. The scene was filmed using a relatively low-cost light and compact InfraRed (IR) thermography camera. A stem temperature map was used to determine the heat pulse propagation velocity. The calculated heat velocity was highly correlated with the applied flow velocity with a unique relationship regardless of the diameter. The latter result confirms the equation of Marshall (1958) which links the sap velocity to the heat velocity with a vessel fraction of around 25 % within samples. The feasibility of outdoor measurements was also successfully tested. The assumed potentials and limitations of the proposed methodology are discussed. In summary, the study demonstrates the concept and validates, in woody stems, this new methodology for non-invasive portable sap flow velocity measurement. International audience

Antecedentes: Las huellas humanas globales han alterado fundamentalmente los regímenes de fuegos, creando serias consecuencias para la salud humana, la biodiversidad y el clima. Sin embargo, resulta difícil proyectar cómo las interacciones a largo plazo entre el uso de la tierra, la gestión, y el Cambio Climático van a afectar el comportamiento del fuego, lo que representa un vacío clave en el conocimiento para la gestión sostenible. Usamos las apreciaciones de expertos para combinar opiniones sobre regímenes de fuegos pasados y futuros de 99 investigadores en el tema de fuegos de vegetación. Preguntamos por determinaciones cualitativas y cuantitativas de la frecuencia, tipo, e implicaciones de los cambios en los regímenes de fuegos desde el inicio del Holoceno hasta el año 2300.Resultados Quienes respondieron indicaron alguna influencia humana directa en los fuegos de vegetación desde al menos ~ 12.000 años atrás, en los que la variabilidad climática perduró como la conductora dominante de los cambios en los regímenes de fuego hasta hace aproximadamente unos 5.000 años, para la mayoría de las regiones en estudio. Las respuestas sugirieron que hubo un incremento de 10 veces en la frecuencia de cambios en los regímenes de fuego durante los últimos 250 años comparado con el resto del Holoceno, correspondiendo en primer lugar con la intensificación y expansión del uso de la tierra y luego con el Cambio Climático antropogénico. Mirando al futuro, predicen que los cambios en los regímenes de fuego se intensificarán, con incrementos en la frecuencia, severidad, y tamaño en todos los biomas con excepción de los ecosistemas de pastizales. Los regímenes de fuego muestran diferente sensibilidad climática a través de los biomas, aunque la probabilidad de cambio en el régimen de fuego se incrementa con mayores escenarios de calentamiento en todos los biomas. Predicen asimismo que la biodiversidad, el almacenamiento de Carbono, y otros servicios ecosistémicos, van a decrecer para la mayoría de los biomas bajo escenarios de mayores emisiones. Presentamos recomendaciones para la adaptación y mitigación bajo regímenes de fuego emergentes, mientras que reconocemos que las opciones de manejo están condicionadas bajo escenarios de mayores emisiones.Conclusiones La influencia de los humanos en los regímenes de fuego se ha incrementado en las últimas dos centurias. Las perspectivas ganadas sobre incendios pasados deben ser consideradas en las estrategias de manejo de tierras y de fuego, aunque un nuevo comportamiento del fuego es probable, dado que la disrupción humana en las comunidades vegetales, en el clima, y en otros factores no tiene precedentes. Los regímenes de fuegos futuros probablemente degraden algunos servicios ecosistémicos clave, al menos que el Cambio Climático sea agresivamente mitigado. Las apreciaciones de los expertos complementan los datos empíricos y modelados, proveyendo una perspectiva más amplia de la ciencia del fuego para informar a los decisores y priorizar futuras investigaciones. Background The global human footprint has fundamentally altered wildfire regimes, creating serious consequences for human health, biodiversity, and climate. However, it remains difficult to project how long-term interactions among land use, management, and climate change will affect fire behavior, representing a key knowledge gap for sustainable management. We used expert assessment to combine opinions about past and future fire regimes from 99 wildfire researchers. We asked for quantitative and qualitative assessments of the frequency, type, and implications of fire regime change from the beginning of the Holocene through the year 2300.Results Respondents indicated some direct human influence on wildfire since at least ~ 12,000 years BP, though natural climate variability remained the dominant driver of fire regime change until around 5,000 years BP, for most study regions. Responses suggested a ten-fold increase in the frequency of fire regime change during the last 250 years compared with the rest of the Holocene, corresponding first with the intensification and extensification of land use and later with anthropogenic climate change. Looking to the future, fire regimes were predicted to intensify, with increases in frequency, severity, and size in all biomes except grassland ecosystems. Fire regimes showed different climate sensitivities across biomes, but the likelihood of fire regime change increased with higher warming scenarios for all biomes. Biodiversity, carbon storage, and other ecosystem services were predicted to decrease for most biomes under higher emission scenarios. We present recommendations for adaptation and mitigation under emerging fire regimes, while recognizing that management options are constrained under higher emission scenarios.Conclusion The influence of humans on wildfire regimes has increased over the last two centuries. The perspective gained from past fires should be considered in land and fire management strategies, but novel fire behavior is likely given the unprecedented human disruption of plant communities, climate, and other factors. Future fire regimes are likely to degrade key ecosystem services, unless climate change is aggressively mitigated. Expert assessment complements empirical data and modeling, providing a broader perspective of fire science to inform decision making and future research priorities. International audience

Wildfires are critical socio-ecological features in the Mediterranean basin. In a context of global changes (climate, land use), we questioned whether the wildfire regime was altered in the mountains of Corsica, France. Using tree- ring analysis of fire-scarred trees, we tested for changes in frequency, seasonality, and area. We hypothesized that the fire regime changed during the middle-20th century due to human activities, as observed elsewhere in the Mediterranean. We sampled fire-scarred trees, geolocated for mapping fire areas, in a forest of black pine (Pinus nigra laricio). The oldest fire was in 1684 but the fire chronology with adequate sample depth for analysis covered 202 years [1820–1921]. Between 1820–2012, 15 fires were recorded, 8 of which scarred at least 25% of the sampled trees. The mean fire interval was 14 years, corresponding to a high fire frequency with 4 major fires per century. Most fires occurred between 1931–1970. On average, about 50% of trees were scarred by fires before 1931, but this percentage decreased thereafter. The exception was the 2000 fire that impacted 100% of living trees. Mapping showed spatially heterogenous fire areas. These results match other Mediterranean studies showing longer fire intervals since the late-20th century, and wildfires generally occurred during the period of late-earlywood or latewood formation, i.e., summer or early autumn, which is the season of contemporary fires. Although fires were recurrent for more than 200 years with no change in the fire season, the regime changed twice in frequency. These changes likely result from a combination of land use and warmer summer conditions. While pines survived most past fires of low intensity through the last large fire in the 1970’s, the severe fire of 2000, following ca 30 years of fire suppression, killed large patches of mature trees. Such chronology provides rational arguments for black pine ecosystem management, notably to consider seeking to recover the sustainable fire regime of the 19th century, for instance by using prescribed fires to manage surface fuel. International audience

Highlights: • AI in weed management potentials for transforming agricultural ecosystems. • AI influence in economic, social, technological, and environmental dimensions. • AI's role in enhancing food safety by reducing pesticides residues. • Digital literacy as a crucial enabler empowering stakeholders to use AI effectively.Abstract: In the face of increasing agricultural demands and environmental concerns, the effective management of weeds presents a pressing challenge in modern agriculture. Weeds not only compete with crops for resources but also pose threats to food safety and agricultural sustainability through the indiscriminate use of herbicides, which can lead to environmental contamination and herbicide-resistant weed populations. Artificial Intelligence (AI) has ushered in a paradigm shift in agriculture, particularly in the domain of weed management. AI's utilization in this domain extends beyond mere innovation, offering precise and eco-friendly solutions for the identification and control of weeds, thereby addressing critical agricultural challenges. This article aims to examine the application of AI in weed management in the context of weed detection and the increasing impact of deep learning techniques in the agricultural sector. Through an assessment of research articles, this study identifies critical factors influencing the adoption and implementation of AI in weed management. These criteria encompass factors of AI adoption (food safety, increased effectiveness, and eco-friendliness through herbicides reduction), AI implementation factors (capture technology, training datasets, AI models, and outcomes and accuracy), ancillary technologies (IoT, UAV, field robots, and herbicides), and the related impact of AI methods adoption (economic, social, technological, and environmental). Of the 5821 documents found, 99 full-text articles were assessed, and 68 were included in this study. The review highlights AI's role in enhancing food safety by reducing herbicide residues, increasing effectiveness in weed control strategies, and promoting eco-friendliness through judicious herbicide use. It underscores the importance of capture technology, training datasets, AI models, and accuracy metrics in AI implementation, emphasizing their synergy in revolutionizing weed management practices. Ancillary technologies, such as IoT, UAVs, field robots, and AI-enhanced herbicides, complement AI's capabilities, offering holistic and data-driven approaches to weed control. Additionally, the adoption of AI methods influences economic, social, technological, and environmental dimensions of agriculture. Last but not least, digital literacy emerges as a crucial enabler, empowering stakeholders to navigate AI technologies effectively and contribute to the sustainable transformation of weed management practices in agriculture. International audience

Agriculture is an important contributor to greenhouse gas (GHG) emissions. While the development of agricultural GHG emissions on national and global scales is well studied for the last three to six decades, little is known about their trajectory and drivers over longer periods. In this article, we address this research gap by calculating and analyzing GHG emissions related to agriculture in Austria from 1830 to 2018. We calculate territorial emissions on an annual basis and include all GHG emissions from the processes directly involved in agricultural production. Based on this time series, we quantify the relative importance of major drivers of changes in GHG emissions across time and agricultural product categories, applying a structural decomposition analysis. We find that agricultural GHG emissions in Austria increased by 69 % over the total study period, from 4.6 Mt. CO

Woody encroachment (WE) and agricultural expansion are widespread in tropical savannas, where they threaten biodiversity and ecosystem function. In Africa's largest savanna, the miombo woodlands, cropland expansion is expected to cause extensive habitat loss over the next 30 years. Meanwhile, widespread WE is altering the remaining untransformed vegetation. Quantifying the extent of both processes in the Angolan miombo woodlands (~570,000 km2) has been challenging due to limited infrastructure, a history of conflict, and widespread landmines. Here, we analyze spectral satellite imagery to investigate the extent of WE and cropland expansion in the Angolan miombo woodlands since 1990. We asses WE using two complementary metrics: multi-decade canopy greenness trends and conversion from grassland to woodland. We also examine whether WE trends are driven by landscape fragmentation and decreasing fire frequency. We found that from 1990 to 2020, 34.1% of the Angolan miombo woodlands experienced significant WE or was converted to cropland, while open grassy vegetation declined by 62%. WE advanced rapidly even in areas experiencing extraordinarily high burn frequencies and was not adequately explained by changing temperature or precipitation. WE was concentrated far from the agricultural frontier, in remote areas with low population densities. These results challenge the hypothesis that human-altered fire regimes are the primary driver of WE in mesic savannas. The results will help decision-makers conserve the miombo woodlands' biodiversity and ecosystem services, by highlighting that strategies to slow habitat loss must address WE and cropland expansion together International audience

This article aims to estimate the water footprint (WF) of cereals—specifically, wheat and barley—in the Kairouan plain, located in central Tunisia. To achieve this objective, two components must be determined: actual evapotranspiration (ETa) and crop yield. The study covers three growing seasons from 2010 to 2013. The ETa estimation employed the S-SEBI (simplified surface energy balance index) model, utilizing Landsat 7 and 8 optical and thermal infrared spectral bands. For yield estimation, an empirical model based on the normalized difference vegetation index (NDVI) was applied. Results indicate the effectiveness of the S-SEBI model in estimating ETa, demonstrating an R2 of 0.82 and an RMSE of 0.45 mm/day. Concurrently, yields mapped over the area range between 6 and 77 qx/ha. Globally, cereals’ average WF varied from 1.08 m3/kg to 1.22 m3/kg over the three study years, with the majority below 1 m3/kg. Notably in dry years, the importance of the blue WF is emphasized compared to years with average rainfall (WFb-2013 = 1.04 m3/kg, WFb-2012 = 0.61 m3/kg, WFb-2011 = 0.41 m3/kg). Moreover, based on an in-depth agronomic analysis combining yields and WF, four classes were defined, ranging from the most water efficient to the least, revealing that over 30% of cultivated areas during the study years (approximately 40% in 2011 and 2012 and 29% in 2013) exhibited low water efficiency, characterized by low yields and high WF. A unique index, the WFI, is proposed to assess the spatial variability of green and blue water. Spatial analysis using the WFI highlighted that in 2012, 40% of cereal plots with low yields but high water consumption were irrigated (81% blue water compared to 6% in 2011). International audience

Abstract Satellite remote sensing enables the study of atmospheric aerosols at large spatial scales, with geostationary platforms making this possible at sub‐daily frequencies. High‐temporal‐resolution aerosol observations can be made from geostationary data by using robust numerical inversion methods such as the widely‐used optimal estimation (OE) theory. This is the case of the instantaneous Aerosol and surfacE Retrieval Using Satellites in GEOstationary orbit (iAERUS‐GEO) algorithm, which successfully retrieves aerosol optical depth (AOD) maps from the Meteosat Second Generation weather satellite based on a simple implementation of the OE approach combined with the Levenberg–Marquardt method. However, the exact gain in inversion performances that can be obtained from the multiple and more advanced possibilities offered by OE is not well documented in the current literature. Against this background, this article presents the quantitative assessment of OE for the future improvement of the iAERUS‐GEO algorithm. To this end, we use a series of comprehensive experiments based on AOD maps retrieved by iAERUS‐GEO using different OE implementations, and ground‐based observations used as reference data. First, we assess the varying importance in the inversion process of satellite observations and a priori information according to the content of satellite aerosol information. Second, we quantify the gain of AOD estimation in log space versus linear space in terms of accuracy, AOD distribution and number of successful retrievals. Finally, we evaluate the accuracy improvement of simultaneous AOD and surface reflectance retrieval as a function of the regions covered by the Meteosat Earth's disk. International audience