October 4, 2018
Scientists, stakeholders and decision makers face trade-offs between adopting simple or complex approaches when modeling ecosystem services (ES). Complex approaches may be time- and data-intensive, making them more challenging to implement and difficult to scale, but can produce more accurate and locally specific results. In contrast, simple approaches allow for faster assessments but may sacrifice accuracy and credibility. The ARtificial Intelligence for Ecosystem Services (ARIES) modeling platform has endeavored to provide a spectrum of simple to complex ES models that are readily accessible to a broad range of users
October 2, 2018
BC3 lidera el proyecto PROCESA, con el apoyo de la Fundación Biodiversidad, del Ministerio para la Transición Ecológica, enfocado en la evaluación del progreso y efectividad de las políticas de adaptación en las principales ciudades del Estado.
September 27, 2018
"Eñaut Izagirre, Guest Researcher de BC3, ha sido parte de la exploración científica a la Cordillera Pariacaca Cordillera Central (Perú). Izagirre, junto a sus compañeros, ha analizado la variabilidad climática y como ésta afecta a la evolución de los glaciares y los caudales que allí se generan."
September 26, 2018
Most land use (change) decisions are still based on incomplete information about the real welfare effects (costs and benefits) because many so-called externalities (positive and negative) associated with the change in land use and management are neglected. This leads to loss and degradation of ecosystems and their services affecting human well-being. Worldwide more than 25% of the land surface is now more or less degraded (UNCCD Global Land Outlook, 2017), costing between 4 and 20 trillion US$/year in terms of damage, repair or replacement costs (Costanza et al., 2014).
September 26, 2018
Achieving the long-term temperature goal of the Paris Agreement requires forest-based mitigation. Collective progress towards this goal will be assessed by the Paris Agreement’s Global stocktake. At present, there is a discrepancy of about 4 GtCO2 yr−1 in global anthropogenic net land-use emissions between global models (reflected in IPCC assessment reports) and aggregated national GHG inventories (under the UNFCCC). We show that a substantial part of this discrepancy (about 3.2 GtCO2 yr−1) can be explained by conceptual differences in anthropogenic forest sink estimation, related to the representation of environmental change impacts and the areas considered as managed.
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Diseminación
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