Floods in the Pampas : Insights from over a decade of satellite observations

Non peer reviewedPublisher PD

Análisis de la variabilidad de la lluvia, la evapotranspiración e índices de vegetación en áreas agrícolas de Entre Ríos

Sobre la base de los resultados del proyecto anterior ‘Integración de datos agrometeorológicos, de sensores remotos y de cultivos mediante técnicas de geoinformación y modelos en el Centro-Oeste de Entre Ríos (PICT 06-1221 PIDUNER 2128) y tomando en consideración el efecto de las anomalías en la producción de granos en la provincia de Entre Ríos se hace evidente la necesidad e importancia de llevar adelante estudios que posibiliten una mayor comprensión de la variabilidad de la lluvia, la evapotranspiración e índices de vegetación y las relaciones con la producción. Esta reseña del proyecto se refiere a dos aspectos del mismo: meteorología agrícola y teledetección aplicada. La primera dirigida a mejorar la información agrometeorológica, a conocer la variabilidad espacial y temporal e investigar asociaciones o efectos en los cultivos. La segunda para: estudiar el comportamiento de la reflectividad de los cultivos de maíz, soja y trigo mediante índices, poner a prueba técnicas avanzadas de procesamiento y manejo de datos de satélites de recursos naturales (Landsat, Modis y nuevos satélites).El proyecto pertenece a un área científica con escaso desarrollo en nuestro país y casi nula en la provincia, pero la importancia actual y el carácter prioritario para los años venideros -por el potencial impacto- señalan la necesidad de iniciar y afianzar estas líneas de investigación y formar recursos humanos capaces de conducirlas

Protecting climate with forests

Policies for climate mitigation on land rarely acknowledge biophysical factors, such as reflectivity, evaporation, and surface roughness. Yet such factors can alter temperatures much more than carbon sequestration does, and often in a conflicting way. We outline a framework for examining biophysical factors in mitigation policies and provide some best-practice recommendations based on that framework. Tropical projects-avoided deforestation, forest restoration, and afforestation-provide the greatest climate value, because carbon storage and biophysics align to cool the Earth. In contrast, the climate benefits of carbon storage are often counteracted in boreal and other snow-covered regions, where darker trees trap more heat than snow does. Managers can increase the climate benefit of some forest projects by using more reflective and deciduous species and through urban forestry projects that reduce energy use. Ignoring biophysical interactions could result in millions of dollars being invested in some mitigation projects that provide little climate benefit or, worse, are counter-productive

Contrasting CO2 and water vapour fluxes in dry forest and pasture sites of central Argentina

The dry forests of South America are a key player of the global carbon cycle and the regional water cycle, but they are being intensively deforested. We used eddy covariance measurements to compare the temporal patterns of CO2 and water vapour fluxes and their relationships with environmental variables in dry forest and pastures sites of central Argentina. Ecosystem fluxes showed clear contrasts in magnitude, timing and response to environmental controls between ecosystems. The dry forest displayed higher daily gross primary productivity (GPP, 10.6 vs. 7.8 g CO2 m−2 d−1) and ecosystem respiration (Reco, 9.1 vs. 7.0 g CO2 m−2 d−1) and lower net ecosystem exchange (NEE, −1.5 vs. −0.7 g CO2 m−2 d−1) than the pasture. These differences were explained by a lower tolerance of the pasture to cool temperatures and drought. The lowest NEE rates were observed between 26°C and 34°C in the pasture, but below this range, NEE increased sharply, switching to a carbon source with temperatures <20°C. By contrast, the dry forest remained as a strong carbon sink down to 18°C. The pasture also showed a stronger drop of GPP with drought compared with the dry forest, becoming a carbon source with soil wetness <25% of soil available water. Rainfall was strongly coupled with GPP in both ecosystems, but the dry forest responded to longer rainfall integration periods. This study helps to understand how ecosystems can respond to climate change, improve global scale modelling and increase the productivity and resilience of rangelands.Fil: Nosetto, Marcelo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi"; ArgentinaFil: Luna Toledo, Emanuel Santiago. Instituto Nacional de Tecnología Agropecuaria; Argentina. Universidad Nacional de Chilecito; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Magliano, Patricio Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi"; ArgentinaFil: Figuerola, Patricia Irene. Universidad Nacional de Chilecito; ArgentinaFil: Blanco, Lisandro Javier. Instituto Nacional de Tecnología Agropecuaria; ArgentinaFil: Jobbagy Gampel, Esteban Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi"; Argentin

Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2&nbsp;m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0\u20135 and 5\u201315&nbsp;cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10\ub0C (mean&nbsp;=&nbsp;3.0&nbsp;\ub1&nbsp;2.1\ub0C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6&nbsp;\ub1&nbsp;2.3\ub0C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler ( 120.7&nbsp;\ub1&nbsp;2.3\ub0C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data.

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible

Global maps of soil temperature.

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km &lt;sup&gt;2&lt;/sup&gt; resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km &lt;sup&gt;2&lt;/sup&gt; pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications