Understanding spatial and temporal variability of N leaching reduction by winter cover crops under climate change.

Winter cover crops are sown in between main spring crops (e.g. cash and forage crops) to provide a range of benefits, including the reduction of nitrogen (N) leaching losses to groundwater. However, the extent by which winter cover crops will remain effective under future climate change is unclear. We assess variability and uncertainty of climate change effects on the reduction of N leaching by winter oat cover crops. Field data were collected to quantify ranges of cover crop above-ground biomass (7 to 10 t DM/ha) and N uptake (70 to 180 kg N/ha) under contrasting initial soil conditions. The data were also used to evaluate the APSIM-NextGen model (R2 from 62 to 96% and RMSEr from 7 to 50%), which was then applied to simulate cover crop and fallow conditions across four key agricultural locations in New Zealand, under baseline and future climate scenarios. Cover crops reduced N leaching risks for all location/scenario combinations but with large variability in space and time (e.g. 21 to 47% of fallow) depending on the climate change scenario. For instance, end-of-century estimates for northern (warmer) locations mostly showed non-significant effects of climate change on cover crop effectiveness and N leaching. In contrast for southern (colder) locations, there was a systematic increase in N leaching risks with climate change intensity despite a concomitant, but less than proportional, increase in cover crop effectiveness (up to ~5% of baseline) due to higher winter yields and N uptake. This implies that climate change may not only modify the geography of N leaching hotspots, but also the extent by which cover crops can locally reduce pollution risks, in some cases requiring complementary adaptive measures. The patchy- and threshold-nature of leaching events indicates that fine spatio-temporal resolutions are better suited to evaluate cover crop effectiveness under climate change.

Simulation of management strategies to mitigate nitrogen losses from crop rotations in Southland, New Zealand.

BACKGROUND: Nitrogen (N) fertiliser used on crops is among the main sources of water pollution. Reliable measurement of N losses from land uses in catchments is key to designing effective management strategies that minimise those losses at the same time as keeping farms profitable. In the present study, we used a management simulation tool within the Agricultural Production Systems sIMulator (APSIM) to assess the effect of fertiliser management on N leaching from croplands in the Aparima catchment in Southland, New Zealand. The assessment was based on two N-fertiliser regimes: (i) Scheduled (conventional) where, N-fertiliser rates and timing of application followed a prescribed programme, and (ii) Soil-test where, N-fertiliser rates and timing depended on daily analysis of simulated soil N levels. Four rotations (continuous wheat, pasture-wheat-grain oats, wheat-fodder beet-peas and wheat-green oats-fodder beet-peas) were used in the evaluation. RESULTS: APSIM simulated crop productivity with reasonable accuracy. Yields were 2% greater, fertiliser N input was 11% lower and leaching was 20% lower under the Soil-test compared to the Scheduled fertiliser management. These results show the potential of a Soil-test based fertiliser application to increase fertiliser-N use efficiency and reduce the risk of N loss to the Southland catchment water systems. CONCLUSION: The present study demonstrates a dynamic farm systems model can be a viable tool to generate valuable data for assessing the productivity and environmental effects of cropping systems at a catchment scale. © 2021 Society of Chemical Industry.

Leaf Rubisco turnover in a perennial ryegrass (Lolium perenne L.) mapping population: genetic variation, identification of associated QTL, and correlation with plant morphology and yield.

This study tested the hypotheses that: (i) genetic variation in Rubisco turnover may exist in perennial ryegrass (Lolium perenne L.); (ii) such variation might affect nitrogen use efficiency and plant yield; and (iii) genetic control of Rubisco turnover might be amenable to identification by quantitative trait loci (QTL) mapping. A set of 135 full-sib F1 perennial ryegrass plants derived from a pair cross between genotypes from the cultivars 'Grasslands Impact' and 'Grasslands Samson' was studied to test these hypotheses. Leaf Rubisco concentration at different leaf ages was measured and modelled as a log-normal curve described by three mathematical parameters: D (peak Rubisco concentration), G (time of D), and F (curve standard deviation). Herbage dry matter (DM) yield and morphological traits (tiller weight (TW), tiller number (TN), leaf lamina length (LL), and an index of competitive ability (PI)) were also measured. The progeny exhibited continuous variation for all traits. Simple correlation and principal component analyses indicated that plant productivity was associated with peak Rubisco concentration and not Rubisco turnover. Lower DM was associated with higher leaf Rubisco concentration indicating that Rubisco turnover effects on plant productivity may relate to energy cost of Rubisco synthesis rather than photosynthetic capacity. QTL detection by a multiple QTL model identified seven significant QTL for Rubisco turnover and nine QTL for DM and morphological traits. An indication of the genetic interdependence of DM and the measures of Rubisco turnover was the support interval overlap involving QTL for D and QTL for TN on linkage group 5 in a cluster involving QTL for DM and PI. In this region, alleles associated with increased TN, DM, and PI were associated with decreased D, indicating that this region may regulate Rubisco concentration and plant productivity via increased tillering. A second cluster involving QTL for LL, TN, PI and DM was found on linkage group 2. The two clusters represent marker-trait associations that might be useful for marker-assisted plant breeding applications. In silico comparative analysis indicated conservation of the genetic loci controlling Rubisco concentration in perennial ryegrass and rice.