This study assesses the ability of 21 crop models to capture the impact of elevated CO2 concentration ([CO2]) on maize yield and water use as measured in a 2-year Free Air Carbon dioxide Enrichment experiment conducted at the Thünen Institute in Braunschweig, Germany (Manderscheid et al., 2014). Data for ambient [CO2] and irrigated treatments were provided to the 21 models for calibrating plant traits, including weather, soil and management data as well as yield, grain number, above ground biomass, leaf area index, nitrogen concentration in biomass and grain, water use and soil water content. Models differed in their representation of carbon assimilation and evapotranspiration processes. The models reproduced the absence of yield response to elevated [CO2] under well-watered conditions, as well as the impact of water deficit at ambient [CO2], with 50% of models within a range of +/−1 Mg ha−1 around the mean. The bias of the median of the 21 models was less than 1 Mg ha−1. However under water deficit in one of the two years, the models captured only 30% of the exceptionally high [CO2] enhancement on yield observed. Furthermore the ensemble of models was unable to simulate the very low soil water content at anthesis and the increase of soil water and grain number brought about by the elevated [CO2] under dry conditions. Overall, we found models with explicit stomatal control on transpiration tended to perform better. Our results highlight the need for model improvement with respect to simulating transpirational water use and its impact on water status during the kernel-set phase
Las regiones metropolitanas son vulnerables al cambio climático desde distintas perspectivas. Los territorios rurales apoyan muchas funciones estratégicas esenciales para la calidad de vida de estas regiones, incluida su contribución a la seguridad alimentaria. La supervivencia de la agricultura metropolitana requiere no solo la protección de los recursos agrícolas, sino también que el valor de la funcionalidad de varios de estos territorios agrícolas sea apreciado por su contribución a la calidad de vida en estas regiones. Por último, los agricultores también deben desarrollar aún más su capacidad de adaptación a diferentes factores estresantes, tales como el cambio climático y la variabilidad, con el fin de sobrevivir, prosperar y seguir apoyando estas funciones estratégicas en la región metropolitana.
This paper introduces a five-step framework, namely the Robust Adaptation Planning (RAP) framework, to plan and respond to the 'grand challenge' of climate change. RAP combines, under a unified framework, elements from robust action, participatory planning and network theory to capture the different motives, perception, and roles of actors that are important for climate change adaptation. RAP leverages existing structures and networks and involves diverse actors to plan, sequence and time strategies across multiple levels (i.e. from local to national). Actors identify adaptation interventions and important actor relations to develop wide networks, highlighting potential pathways for connecting action from central policy to local implementation (and vice versa). Comparing these proposed participatory structures with existing structures reveals actors deemed important for delivering adaptation, as well as gaps and overlaps in their relations. The end result is a robust plan covering many perspectives and local realities for both relieving immediate and adapting to longer-term consequences of climate change. We applied the RAP framework in Ghana's agricultural climate change adaptation regime to demonstrate its usefulness as a means of planning adaptation interventions in a climate-vulnerable, multi-actor and multi-level setting. The application of the RAP framework in this paper highlights how it can: (1) visualise the adaptation space (and its different components), and reduce the complexity of implementing adaptation responses; (2) offer a shared space to actors from all administrative levels to think and create collective narratives for adaptation without demanding explicit consensus and; (3) identify key actors and actions through a collaborative planning process, and allocate responsibility for the smooth delivery of adaptation interventions.
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