A global, empirical, harmonised dataset of soil organic carbon changes under perennial crops.

A global, unified dataset on Soil Organic Carbon (SOC) changes under perennial crops has not existed till now. We present a global, harmonised database on SOC change resulting from perennial crop cultivation. It contains information about 1605 paired-comparison empirical values (some of which are aggregated data) from 180 different peer-reviewed studies, 709 sites, on 58 different perennial crop types, from 32 countries in temperate, tropical and boreal areas; including species used for food, bioenergy and bio-products. The database also contains information on climate, soil characteristics, management and topography. This is the first such global compilation and will act as a baseline for SOC changes in perennial crops. It will be key to supporting global modelling of land use and carbon cycle feedbacks, and supporting agricultural policy development.

Evaluation of four modelling approaches to estimate nitrous oxide emissions in China's cropland.

Process-based models are useful tools to integrate the effects of detailed agricultural practices, soil characteristics, mass balance, and climate change on soil N2O emissions from soil - plant ecosystems, whereas static, seasonal or annual models often exist to estimate cumulative N2O emissions under data-limited conditions. A study was carried out to compare the capability of four models to estimate seasonal cumulative N2O fluxes from 419 field measurements representing 65 studies across China's croplands. The models were 1) the DAYCENT model, 2) the DNDC model, 3) the linear regression model (YLRM) of Yue et al. (2018), and 4) IPCC Tier 1 emission factors. The DAYCENT and DNDC models estimated crop yields with R2 values of 0.60 and 0.66 respectively, but both models showed significant underestimation for all measurements. The estimated seasonal N2O emissions with R2 of 0.31, 0.30, 0.21 and 0.17 for DAYCENT, DNDC, YLRM, and IPCC, respectively. Based on RMSE, modelling efficiency and bias analysis, YLRM performed well on N2O emission prediction under no fertilization though bias still existed, while IPCC performed well for cotton and rapeseed and DNDC for soybean. The DAYCENT model accurately predicted the emissions with no bias across other crop and fertilization types whereas the DNDC model underestimated seasonal N2O emissions by 0.42 kg N2O-N ha-1 for all observed values. Model evaluation indicated that the DAYCENT and DNDC models simulated temporal patterns of daily N2O emissions effectively, but both models had difficulty in simulating the timing of the N2O fluxes following some events such as fertilization and water regime. According to this evaluation, algorithms for crop production and N2O emission should be improved to increase the accuracy in the prediction of unfertilized fields both for DAYCENT and DNDC. The effects of crop types and management modes such as fertilizations should also be further refined for YLRM.

Limits of agricultural greenhouse gas calculators to predict soil N2O and CH4 fluxes in tropical agriculture.

Demand for tools to rapidly assess greenhouse gas impacts from policy and technological change in the agricultural sector has catalyzed the development of 'GHG calculators'- simple accounting approaches that use a mix of emission factors and empirical models to calculate GHG emissions with minimal input data. GHG calculators, however, rely on models calibrated from measurements conducted overwhelmingly under temperate, developed country conditions. Here we show that GHG calculators may poorly estimate emissions in tropical developing countries by comparing calculator predictions against measurements from Africa, Asia, and Latin America. Estimates based on GHG calculators were greater than measurements in 70% of the cases, exceeding twice the measured flux nearly half the time. For 41% of the comparisons, calculators incorrectly predicted whether emissions would increase or decrease with a change in management. These results raise concerns about applying GHG calculators to tropical farming systems and emphasize the need to broaden the scope of the underlying data.

A 2 MV Van de Graaff accelerator as a tool for planetary and impact physics research.

Investigating the dynamical and physical properties of cosmic dust can reveal a great deal of information about both the dust and its many sources. Over recent years, several spacecraft (e.g., Cassini, Stardust, Galileo, and Ulysses) have successfully characterised interstellar, interplanetary, and circumplanetary dust using a variety of techniques, including in situ analyses and sample return. Charge, mass, and velocity measurements of the dust are performed either directly (induced charge signals) or indirectly (mass and velocity from impact ionisation signals or crater morphology) and constrain the dynamical parameters of the dust grains. Dust compositional information may be obtained via either time-of-flight mass spectrometry of the impact plasma or direct sample return. The accurate and reliable interpretation of collected spacecraft data requires a comprehensive programme of terrestrial instrument calibration. This process involves accelerating suitable solar system analogue dust particles to hypervelocity speeds in the laboratory, an activity performed at the Max Planck Institut für Kernphysik in Heidelberg, Germany. Here, a 2 MV Van de Graaff accelerator electrostatically accelerates charged micron and submicron-sized dust particles to speeds up to 80 km s(-1). Recent advances in dust production and processing have allowed solar system analogue dust particles (silicates and other minerals) to be coated with a thin conductive shell, enabling them to be charged and accelerated. Refinements and upgrades to the beam line instrumentation and electronics now allow for the reliable selection of particles at velocities of 1-80 km s(-1) and with diameters of between 0.05 µm and 5 µm. This ability to select particles for subsequent impact studies based on their charges, masses, or velocities is provided by a particle selection unit (PSU). The PSU contains a field programmable gate array, capable of monitoring in real time the particles' speeds and charges, and is controlled remotely by a custom, platform independent, software package. The new control instrumentation and electronics, together with the wide range of accelerable particle types, allow the controlled investigation of hypervelocity impact phenomena across a hitherto unobtainable range of impact parameters.

Onset of sheath extension and duration of lamina extension are major determinants of the response of maize lamina length to plant density.

BACKGROUND AND AIMS: Plants regulate their architecture strongly in response to density, and there is evidence that this involves changes in the duration of leaf extension. This questions the approximation, central in crop models, that development follows a fixed thermal time schedule. The aim of this research is to investigate, using maize as a model, how the kinetics of extension of grass leaves change with density, and to propose directions for inclusion of this regulation in plant models. METHODS: Periodic dissection of plants allowed the establishment of the kinetics of lamina and sheath extension for two contrasting sowing densities. The temperature of the growing zone was measured with thermocouples. Two-phase (exponential plus linear) models were fitted to the data, allowing analysis of the timing of the phase changes of extension, and the extension rate of sheaths and blades during both phases. KEY RESULTS: The duration of lamina extension dictated the variation in lamina length between treatments. The lower phytomers were longer at high density, with delayed onset of sheath extension allowing more time for the lamina to extend. In the upper phytomers--which were shorter at high density--the laminae had a lower relative extension rate (RER) in the exponential phase and delayed onset of linear extension, and less time available for extension since early sheath extension was not delayed. CONCLUSIONS: The relative timing of the onset of fast extension of the lamina with that of sheath development is the main determinant of the response of lamina length to density. Evidence is presented that the contrasting behaviour of lower and upper phytomers is related to differing regulation of sheath ontogeny before and after panicle initiation. A conceptual model is proposed to explain how the observed asynchrony between lamina and sheath development is regulated.

Maximum likelihood inference and bootstrap methods for plant organ growth via multi-phase kinetic models and their application to maize.

BACKGROUND AND AIMS: Fitting the parameters of models of plant organ growth is a means to investigate how environmental conditions affect plant architecture. The aim of this article is to evaluate some non-linear methods for fitting the parameters of multi-phase models of the kinetics of extension of plant organs such as laminae, sheaths and internodes. * METHODS: A set of computational procedures was developed allowing parameter-fitting of multi-phase models, using the maximum likelihood criterion, in which phases are identified with reference to ontogenic processes. Two bootstrap methods were compared to assess the precision of the estimates of fitted parameters, and of functions of these parameters such as the final leaf length, and the duration and rate of the rapid extension phase. Methods were applied to an experimental dataset, representing the kinetics of laminae, sheaths and internodes along the maize shoot, for two contrasting densities. * KEY RESULTS: A set of multi-phase models was proposed to describe the extension of laminae, sheaths and internodes along the shoot. The distinguishable phases differed between laminae, sheaths and internodes. For sheaths and laminae, but not for internodes, the same model could be fitted to all phytomers along the shoot. The variation of parameters along the shoot and between density treatments, as well as derived functions such as the durations of the phases of extension, are presented for laminae. It was the duration of the fast extension period, rather than its rate, which determined the difference in final length between treatments. * CONCLUSIONS: Such methods permit a large degree of objectivity and facilitate the analysis of such rather complicated but co-ordinated datasets. The work also illustrates some natural limitations of maximum likelihood methods, and viable ways of overcoming them by including a priori knowledge in the model fitting method are discussed.

Travelling waves of resistance in a bi-trophic pest adaptation model.

We consider a reaction-diffusion system for spatial spread of pest resistance to host plant resistance genes which is based on the Lotka-Volterra predator-prey equations, with logistic growth of the resource level and a diffusion term added to account for spatial spread of the pest. The model is phenotype specific, in which a pest subpopulation's fitness comes down to a balance between its resource assimilation rate and its respiration rate. We derive an expression for the rate of spatial spread of the resistant pest types from an initial point source, and discuss its relevance for adaptive pest resistance management strategies. Using results for an analogous single-species reaction-diffusion model in heterogeneous media, we consider the likely impact of pest-susceptible plant refugia on the speed of the travelling wave of resistant pests, and simultaneously the expected trade-off, in terms of crop yield decrease, when refugia are included. We also explore the possibility that resistance breaking by the pest population is not an inevitable phenomenon, particularly when refugia of the appropriate size are used.

Bi-trophic mathematical model for pest adaptation to a resistant crop.

A version of the Lotka-Volterra predator-prey model with logistic crop growth is modified to explore the rate of adaptation of a herbivore to a pest-resistant crop. This provides a phenotypic model for the evolution of resistance in a population comprising three different pest types each defined by differing parameter values for respiration rate and crop palatability. Expressions estimating the rates of increase of the fitter pest types are obtained as a function of the food qualities, and respiration and mortality rates. Potential strategies for delaying the rate of adaptation with regard to the expressions derived above, via the use of pest-susceptible refugia and natural enemies, are discussed. Although the model is formulated as one in which a single gene is the factor conferring resistance it can be interpreted and used independently of this.