• Energy Research

Los pastizales compuestos por mezclas de gramíneas y leguminosas podrían convertirse en un sustituto del fertilizante nitrogenado a través de la fijación biológica de nitrógeno (BNF), que a su vez puede reducir las emisiones de óxido nitroso directamente de los suelos sin impactos negativos en la productividad. Los modelos pueden probar cómo se pueden usar las leguminosas para cumplir con los objetivos ambientales y de producción, pero muchos modelos utilizados para simular las emisiones de gases de efecto invernadero (GEI) de los pastizales tienen una representación deficiente de las mezclas de pasto y leguminosas y el BNF, o una validación deficiente de estas características. Nuestro objetivo es examinar cómo estos sistemas están representados actualmente en dos modelos biogeoquímicos basados en procesos, APSIM y DayCent, en comparación con un conjunto de datos experimentales con diferentes mezclas de gramíneas y leguminosas a tres tasas de fertilizantes de nitrógeno (N). Aquí, proponemos un enfoque novedoso para acoplar DayCent, un modelo de una sola especie a APSIM, un modelo multiespecie, para aumentar la capacidad de DayCent al representar una gama de fracciones de gramíneas y leguminosas. Si bien dependen de supuestos específicos, ambos modelos pueden capturar los aspectos clave del crecimiento de las leguminosas de pasto, incluida la producción de biomasa y BNF, y simular correctamente las interacciones entre las fracciones cambiantes de leguminosas y pasto, particularmente las mezclas con una fracción alta de trébol. Nuestro trabajo sugiere que los modelos de una sola especie no deben usarse para mezclas de gramíneas y leguminosas más allá de aproximadamente el 30% de contenido de leguminosas, a menos que se utilice un enfoque similar al adoptado aquí. Les prairies composées de mélanges herbe-légumine pourraient devenir un substitut à l'engrais azoté grâce à la fixation biologique de l'azote (BNF) qui, à son tour, peut réduire les émissions d'oxyde nitreux directement des sols sans impact négatif sur la productivité. Les modèles peuvent tester comment les légumineuses peuvent être utilisées pour atteindre les objectifs environnementaux et de production, mais de nombreux modèles utilisés pour simuler les émissions de gaz à effet de serre (GES) des prairies ont soit une mauvaise représentation des mélanges herbe-légumine et BNF, soit une mauvaise validation de ces caractéristiques. Notre objectif est d'examiner comment ces systèmes sont actuellement représentés dans deux modèles biogéochimiques basés sur les processus, APSIM et DayCent, par rapport à un ensemble de données expérimentales avec différents mélanges herbe-légumine à trois taux d'engrais azotés (N). Ici, nous proposons une nouvelle approche pour coupler DayCent, un modèle d'espèce unique à APSIM, un modèle multi-espèces, afin d'augmenter la capacité de DayCent lorsqu'il représente une gamme de fractions herbe-légumine. Bien qu'ils dépendent d'hypothèses spécifiques, les deux modèles peuvent capturer les aspects clés de la croissance des légumineuses à graminées, y compris la production de biomasse et le BNF, et simuler correctement les interactions entre les fractions changeantes des légumineuses et des graminées, en particulier les mélanges avec une fraction élevée de trèfle. Nos travaux suggèrent que les modèles à espèce unique ne devraient pas être utilisés pour les mélanges herbe-légumine au-delà d'environ 30% de teneur en légumineuses, à moins d'utiliser une approche similaire à celle adoptée ici. Grasslands comprised of grass-legume mixtures could become a substitute for nitrogen fertiliser through biological nitrogen fixation (BNF) which in turn can reduce nitrous oxide emissions directly from soils without negative impacts on productivity. Models can test how legumes can be used to meet environmental and production goals, but many models used to simulate greenhouse gas (GHG) emissions from grasslands have either a poor representation of grass-legume mixtures and BNF, or poor validation of these features. Our objective is to examine how such systems are currently represented in two process-based biogeochemical models, APSIM and DayCent, when compared against an experimental dataset with different grass-legume mixtures at three nitrogen (N) fertiliser rates. Here, we propose a novel approach for coupling DayCent, a single species model to APSIM, a multi-species model, to increase the capability of DayCent when representing a range of grass-legume fractions. While dependent on specific assumptions, both models can capture the key aspects of the grass-legume growth, including biomass production and BNF and to correctly simulate the interactions between changing legume and grass fractions, particularly mixtures with a high clover fraction. Our work suggests that single species models should not be used for grass-legume mixtures beyond about 30% legume content, unless using a similar approach to that adopted here. يمكن أن تصبح الأراضي العشبية المكونة من مخاليط البقوليات العشبية بديلاً عن الأسمدة النيتروجينية من خلال التثبيت البيولوجي للنيتروجين (BNF) والذي بدوره يمكن أن يقلل من انبعاثات أكسيد النيتروز مباشرة من التربة دون تأثيرات سلبية على الإنتاجية. يمكن للنماذج اختبار كيفية استخدام البقوليات لتحقيق الأهداف البيئية والإنتاجية، ولكن العديد من النماذج المستخدمة لمحاكاة انبعاثات غازات الدفيئة (GHG) من الأراضي العشبية إما لديها تمثيل ضعيف لخليط البقوليات العشبية و BNF، أو التحقق الضعيف من هذه الميزات. هدفنا هو دراسة كيفية تمثيل هذه الأنظمة حاليًا في نموذجين كيميائيين بيولوجيين قائمين على العمليات، APSIM و DayCent، عند مقارنتهما بمجموعة بيانات تجريبية بمخاليط مختلفة من البقوليات العشبية بثلاثة معدلات أسمدة نيتروجينية (N). هنا، نقترح نهجًا جديدًا لإقران DayCent، وهو نموذج نوع واحد بـ APSIM، وهو نموذج متعدد الأنواع، لزيادة قدرة DayCent عند تمثيل مجموعة من كسور البقوليات العشبية. مع الاعتماد على افتراضات محددة، يمكن لكلا النموذجين التقاط الجوانب الرئيسية لنمو البقوليات العشبية، بما في ذلك إنتاج الكتلة الحيوية و BNF ومحاكاة التفاعلات بين تغيير البقوليات وكسور العشب بشكل صحيح، وخاصة الخلائط ذات الكسر البرمجي العالي. يقترح عملنا أنه لا ينبغي استخدام نماذج الأنواع الفردية لمخاليط البقوليات العشبية التي تتجاوز حوالي 30 ٪ من محتوى البقوليات، ما لم تستخدم نهجًا مشابهًا للنهج المعتمد هنا.

Numerous climate futures are now available fromglobal climate models. Translation of climate data such as precipitation and temperatures into ecologicallymeaningful outputs formanagers and planners is the next frontier. We describe a model-based open platform to assess vulnerabilities of agricultural systems to climate change on pixel-wise data. The platformincludes a simulationmodeling engine and is suited towork with NetCDF format of input and output files. In a case study covering a region (Auvergne) in theMassif Central of France, the platformis configured to characterize climate (occurrence of arid conditions in historical and projected climate records), soils and human management, and is then used to assess the vulnerability to climate change of grassland productivity (downscaled to a fine scale). We demonstrate how using climate time series, and process-based simulations vulnerabilities can be defined at fine spatial scales relevant to farmers and land managers, and can be incorporated into management frameworks.

Over the last century, the management of pastoral systems has undergone major changes to meet the livelihood needs of alpine communities. Faced with the changes induced by recent global warming, the ecological status of many pastoral systems has seriously deteriorated in the western alpine region. We assessed changes in pasture dynamics by integrating information from remote-sensing products and two process-based models, i.e. the grassland-specific, biogeochemical growth model PaSim and the generic crop-growth model DayCent. Meteorological observations and satellite-derived Normalised Difference Vegetation Index (NDVI) trajectories of three pasture macro-types (high, medium and low productivity classes) in two study areas - Parc National des Écrins (PNE) in France and Parco Nazionale Gran Paradiso (PNGP) in Italy - were used as a basis for the model calibration work. The performance of the models was satisfactory in reproducing pasture production dynamics (R2 = 0.52 to 0.83). Projected changes in alpine pastures due to climate-change impacts and adaptation strategies indicate that: i) the length of the growing season is expected to increase between 15 and 40 days, resulting in changes in the timing and amount of biomass production, ii) summer water stress could limit pasture productivity; iii) earlier onset of grazing could enhance pasture productivity; iv) higher livestock densities could increase the rate of biomass regrowth, but major uncertainties in modelling processes need to be considered; and v) the carbon sequestration potential of pastures could decrease under limited water availability and warming.

Vulnerability assessment to climate change is an issue of concern.We develop Java-based software for vulnerability assessment to climate change.We illustrate the software in vulnerability assessments of European grasslands. Vuln-Indices Java-based software was developed on concepts of vulnerability to climate change of agro-ecological systems. It implements the calculation of vulnerability indices on series of state variables for assessments at both site and region levels. The tool is useful because synthetic indices help capturing complex processes and prove effective to identify the factors responsible for vulnerability and their relative importance. It is suggested that the tool may be plausible for use with stakeholders to disseminate information of climate change impacts.

AbstractA potential strategy for mitigating nitrous oxide (N2O) emissions from permanent grasslands is the partial substitution of fertilizer nitrogen (Nfert) with symbiotically fixed nitrogen (Nsymb) from legumes. The input of Nsymb reduces the energy costs of producing fertilizer and provides a supply of nitrogen (N) for plants that is more synchronous to plant demand than occasional fertilizer applications. Legumes have been promoted as a potential N2O mitigation strategy for grasslands, but evidence to support their efficacy is limited, partly due to the difficulty in conducting experiments across the large range of potential combinations of legume proportions and fertilizer N inputs. These experimental constraints can be overcome by biogeochemical models that can vary legume‐fertilizer combinations and subsequently aid the design of targeted experiments. Using two variants each of two biogeochemical models (APSIM and DayCent), we tested the N2O mitigation potential and productivity of full factorial combinations of legume proportions and fertilizer rates for five temperate grassland sites across the globe. Both models showed that replacing fertilizer with legumes reduced N2O emissions without reducing productivity across a broad range of legume‐fertilizer combinations. Although the models were consistent with the relative changes of N2O emissions compared to the baseline scenario (200 kg N ha−1 yr−1; no legumes), they predicted different levels of absolute N2O emissions and thus also of absolute N2O emission reductions; both were greater in DayCent than in APSIM. We recommend confirming these results with experimental studies assessing the effect of clover proportions in the range 30–50% and ≤150 kg N ha−1 yr−1 input as these were identified as best‐bet climate smart agricultural practices.