Bioenergy crop production and carbon sequestration potential under changing climate and land use: A case study in the upper River Taw catchment in southwest England.

Reductions in CO2 emissions are essential to support the UK in achieving its net zero policy objective by around mid-century. Both changing climate and land use change (LUC) offer an opportunity to deploy suitable bioenergy crops strategically to enhance energy production and C sequestration to help deliver net zero through capturing atmospheric CO2. Against this background, we applied process-based models to evaluate the extent of net primary productivity (NPP) losses/gains associated with perennial bioenergy crops and to assess their C sequestration potential under changing climate in the upper River Taw observatory catchment in southwest England. In so doing, we also determined whether LUC from permanent grassland to perennial bioenergy crops, considered in this study, can increase the production and C sequestration potential in the study area. The results show that a warming climate positively impacts the production of all crops considered (permanent grassland, Miscanthus and two cultivars of short rotation coppice (SRC) willow). Overall, Miscanthus provides higher aboveground biomass for energy compared to willow and grassland whereas the broadleaf willow cultivar 'Endurance' is best suited, among all crops considered, for C sequestration in this environment, and more so in the changing climate. In warmer lowlands, LUC from permanent grassland to Miscanthus and in cooler uplands from permanent grassland to 'Endurance', enhances NPP. Colder areas are predicted to benefit more from changing climate in terms of above and belowground biomass for both Miscanthus and willow. The study shows that the above LUC can help augment non-fossil energy production and increase C sequestration potential if C losses from land conversion do not exceed the benefits from LUC. In the wake of a changing climate, aboveground biomass for bioenergy and belowground biomass to enhance carbon sequestration can be managed by the careful selection of bioenergy crops and targeted deployment within certain climatic zones.

Exploring the effects of land management change on productivity, carbon and nutrient balance: Application of an Ensemble Modelling Approach to the upper River Taw observatory, UK.

Agriculture is challenged to produce healthy food and to contribute to cleaner energy whilst mitigating climate change and protecting ecosystems. To achieve this, policy-driven scenarios need to be evaluated with available data and models to explore trade-offs with robust accounting for the uncertainty in predictions. We developed a novel model ensemble using four complementary state-of-the-art agroecosystems models to explore the impacts of land management change. The ensemble was used to simulate key agricultural and environmental outputs under various scenarios for the upper River Taw observatory, UK. Scenarios assumed (i) reducing livestock production whilst simultaneously increasing the area of arable where it is feasible to cultivate (PG2A), (ii) reducing livestock production whilst simultaneously increasing bioenergy production in areas of the catchment that are amenable to growing bioenergy crops (PG2BE) and (iii) increasing both arable and bioenergy production (PG2A + BE). Our ensemble approach combined model uncertainty using the tower property of expectation and the law of total variance. Results show considerable uncertainty for predicted nutrient losses with different models partitioning the uncertainty into different pathways. Bioenergy crops were predicted to produce greatest yields from Miscanthus in lowland and from SRC-willow (cv. Endurance) in uplands. Each choice of management is associated with trade-offs; e.g. PG2A results in a significant increase of edible calories (6736 Mcal ha-1) but reduced soil C (-4.32 t C ha-1). Model ensembles in the agroecosystem context are difficult to implement due to challenges of model availability and input and output alignment. Despite these challenges, we show that ensemble modelling is a powerful approach for applications such as ours, offering benefits such as capturing structural as well as data uncertainty and allowing greater combinations of variables to be explored. Furthermore, the ensemble provides a robust means for combining uncertainty at different scales and enables us to identify weaknesses in system understanding.

Decadal analysis of impact of future climate on wheat production in dry Mediterranean environment: A case of Jordan.

Different aspects of climate change, such as increased temperature, changed rainfall and higher atmospheric CO2 concentration, all have different effects on crop yields. Process-based crop models are the most widely used tools for estimating future crop yield responses to climate change. We applied APSIM crop simulation model in a dry Mediterranean climate with Jordan as sentinel site to assess impact of climate change on wheat production at decadal level considering two climate change scenarios of representative concentration pathways (RCP) viz., RCP4.5 and RCP8.5. Impact of climatic variables alone was negative on grain yield but this adverse effect was negated when elevated atmospheric CO2 concentrations were also considered in the simulations. Crop cycle of wheat was reduced by a fortnight for RCP4.5 scenario and by a month for RCP8.5 scenario at the approach of end of the century. On an average, a grain yield increase of 5 to 11% in near future i.e., 2010s-2030s decades, 12 to 16% in mid future i.e., 2040s-2060s decades and 9 to 16% in end of century period can be expected for moderate climate change scenario (RCP4.5) and 6 to 15% in near future, 13 to 19% in mid future and 7 to 20% increase in end of century period for a drastic climate change scenario (RCP8.5) based on different soils. Positive impact of elevated CO2 is more pronounced in soils with lower water holding capacity with moderate increase in temperatures. Elevated CO2 had greater positive effect on transpiration use efficiency (TUE) than negative effect of elevated mean temperatures. The change in TUE was in near perfect direct relationship with elevated CO2 levels (R2>0.99) and every 100-ppm atmospheric CO2 increase resulted in TUE increase by 2kgha-1mm-1. Thereby, in this environment yield gains are expected in future and farmers can benefit from growing wheat.

Advancing the climate data driven crop-modeling studies in the dry areas of Northern Syria and Lebanon: an important first step for assessing impact of future climate.

Inter-annual and seasonal variability in climatic parameters, most importantly rainfall, have potential to cause climate-induced risk in long-term crop production. Short-term field studies do not capture the full nature of such risk and the extent to which modifications to crop, soil and water management recommendations may be made to mitigate the extent of such risk. Crop modeling studies driven by long-term daily weather data can predict the impact of climate-induced risk on crop growth and yield however, the availability of long-term daily weather data can present serious constraints to the use of crop models. To tackle this constraint, two weather generators namely, LARS-WG and MarkSim, were evaluated in order to assess their capabilities of reproducing frequency distributions, means, variances, dry spell and wet chains of observed daily precipitation, maximum and minimum temperature, and solar radiation for the eight locations across cropping areas of Northern Syria and Lebanon. Further, the application of generated long-term daily weather data, with both weather generators, in simulating barley growth and yield was also evaluated. We found that overall LARS-WG performed better than MarkSim in generating daily weather parameters and in 50 years continuous simulation of barley growth and yield. Our findings suggest that LARS-WG does not necessarily require long-term e.g., >30 years observed weather data for calibration as generated results proved to be satisfactory with >10 years of observed data except in area with higher altitude. Evaluating these weather generators and the ability of generated weather data to perform long-term simulation of crop growth and yield is an important first step to assess the impact of future climate on yields, and to identify promising technologies to make agricultural systems more resilient in the given region.