a b s t r a c tThe ability of biogeochemical ecosystem models to represent agro-ecosystems depends on their correct integration with field observations. We report simultaneous calibration of 67 DayCent model parameters using multiple observation types through inverse modeling using the PEST parameter estimation software. Parameter estimation reduced the total sum of weighted squared residuals by 56% and improved model fit to crop productivity, soil carbon, volumetric soil water content, soil temperature, N 2 O, and soil NO 3 À compared to the default simulation. Inverse modeling substantially reduced predictive model error relative to the default model for all model predictions, except for soil NO 3 À and NH 4 þ . Post-processing analyses provided insights into parametereobservation relationships based on parameter correlations, sensitivity and identifiability. Inverse modeling tools are shown to be a powerful way to systematize and accelerate the process of biogeochemical model interrogation, improving our understanding of model function and the underlying ecosystem biogeochemical processes that they represent.

A B S T R A C TReduction of soil tillage is of paramount importance for agricultural soil preservation. However, it is often accompanied by yield reduction and weed management problems. In this perspective, cover crops could play an important role to alleviate weed infestation and sustain yield. In this study, the results from a three-year experiment of cover crop cultivation in different soil tillage treatments is presented, together with results from DayCent simulations on the long term evolution of soil organic carbon and total nitrogen. Eight cover crop treatments were set up as subtreatments in a long term experiment in Switzerland. Cover crops were cultivated for a short two-month period between two winter wheats. Substantial differences in cover crop growth were observed depending on cover crop species. In all tillage treatments, high cover crop biomass production allowed to supress weed biomass compared to the no cover crop control. Wheat grain yield was higher in the minimum tillage than in the plough treatment. In the no till treatment, wheat yield was notably low, except in the field pea treatments, where wheat yield reached values similar to that observed in the plough and minimum tillage treatments. In addition, these differences in biomass production translated into important differences in nutrient inputs, and even in soil nutrient concentration in some cases. Long term simulations showed that cover crop cultivation could increase drastically soil organic carbon and total nitrogen, especially in reduced tillage treatments. Altogether, these results demonstrated that the presence of a well-developed cover crop, even for only two months, allows to sustain wheat yield in a no till treatment. It impacts also soil fertility and nutrient cycling. This study shows that an accurate use and management of cover crops, in interaction with tillage reduction, could maintain yield and improve soil fertility in the long term.

Abstract. Further progress in understanding and mitigating N 2 O emissions from soil lies within transdisciplinary research that reaches across spatial scales and takes an ambitious look into the future.

Variability in soil organic carbon (SOC) results from natural and human processes interacting across time and space, and leads to large variation in the minimum difference in SOC that can be detected with a particular experimental design. Here we report a unique comparison of minimum detectable differences (MDDs) in SOC, and the estimated times required to observe those MDDs across the north central United States, calculated for the two most common SOC experiments: (1) a comparison between two treatments, e.g., moldboard plow (MP) and no-tillage (NT), using a randomized complete block design experiment; and (2) a comparison of changes in SOC over time for a particular treatment, e.g., NT, using a randomized complete block design experiment with time as an additional factor. We estimated the duration of the two experiment types required to achieve MDD through simulation of SOC dynamics. Data for the study came from 13 experimental sites located in Iowa, Illinois, Ohio, Michigan, Wisconsin, Missouri, and Minnesota. Soil organic carbon, bulk density, and texture were measured at four soil depths. Minimum detectable differences were calculated with probability of Type I error of 0.05 and probability of Type II error of 0.15.The MDDs in SOC were highly variable across the region and increased with soil depth. At 0 to 10 cm (0 to 3.9 in) soil depth, MDDs with five replications ranged from 1.04 g C kg -1 (0.017 oz C lb ; 3%) to 3.12 g C kg -1 (0.050 oz C lb -1 ; 13%) for SOC change over time. Large differences were also predicted in the experiment duration required to detect a difference in SOC between MP and NT (from 8 to >100 years with five replications), or a change in SOC over time under NT management (from 11 to 71 years with five replications). At most locations, the time required to detect a change in SOC under NT was shorter than the time required to detect a difference between MP and NT. Minimum detectable difference and experiment duration decreased with the number of replications and were correlated with SOC variability and soil texture of the experimental sites, i.e., they tended to be lower in fine textured soils. Experiment duration was also reduced by increased crop productivity and the amount of residue left on the soil. The relationships and methods described here enable the design of experiments with high power of detecting differences and changes in SOC and enhance our understanding of how management practices influence SOC storage.

The frequency and intensity of extreme weather years, characterized by abnormal precipitation and temperature, are increasing. In isolation, these years have disproportionately large effects on environmental N losses. However, the sequence of extreme weather years (e.g., wet-dry vs. dry-wet) may affect cumulative N losses.We calibrated and validated the DAYCENT ecosystem process model with a comprehensive set of biogeophysical measurements from a corn-soybean rotation managed at three N fertilizer inputs with and without a winter cover crop in Iowa, USA.Our objectives were to determine: (i) how 2-year sequences of extreme weather affect 2-year cumulative N losses across the crop rotation, and (ii) if N fertilizer management and the inclusion of a winter cover crop between corn and soybean mitigate the effect of extreme weather on N losses. Using historical weather (1951-2013), we created nine 2-year scenarios with all possible combinations of the driest ("dry"), wettest ("wet"), and average ("normal") weather years. We analyzed the effects of these scenarios following several consecutive years of relatively normal weather. Compared with the normal-normal 2-year weather scenario, 2-year extreme weather scenarios affected 2-year cumulative NO 3 À leaching (range: À93 to +290%) more than N 2 O emissions (range: À49 to +18%). The 2-year weather scenarios had nonadditive effects on N losses: compared with the normal-normal scenario, the dry-wet sequence decreased 2-year cumulative N 2 O emissions while the wet-dry sequence increased 2-year cumulative N 2 O emissions. Although dry weather decreased NO 3 À leaching and N 2 O emissions in isolation, 2-year cumulative N losses from the wet-dry scenario were greater than the dry-wet scenario. Cover crops reduced the effects of extreme weather on NO 3 À leaching but had a lesser effect on N 2 O emissions. As the frequency of extreme weather is expected to increase, these data suggest that the sequence of interannual weather patterns can be used to develop short-term mitigation strategies that manipulate N fertilizer and crop rotation to maximize crop N uptake while reducing environmental N losses. K E Y W O R D Sclimate change, crop phase, crop system, extreme precipitation, nitrate, nitrous oxide