The use of lysimeter data for the test of two soil–water balance models: A case study

Two soil–water balance models were tested by a comparison of simulated with measured daily rates of actual evapotranspiration, soil water storage, groundwater recharge, and capillary rise. These rates were obtained from twelve weighable lysimeters with three different soils and two different lower boundary conditions for the time period from January 1, 1996 to December 31, 1998. In that period, grass vegetation was grown on all lysimeters. These lysimeters are located in Berlin‐Dahlem, Germany. One model calculated the soil water balance using the Richards equation. The other one used a capacitance approach. Both models used the same modified Penman formula for the estimation of potential evapotranspiration and the same simple empirical vegetation model for the calculation of transpiration, interception, and evaporation. The comparisons of simulated with measured model outputs were analyzed using the modeling‐efficiency index IA and the root mean squared error RMSE. At some lysimeters, the uncalibrated application of both models led to an underestimation of cumulative and annual rates of groundwater recharge and capillary rise, despite a good simulation quality in terms of IA and RMSE. A calibration of soil‐hydraulic and vegetation parameters such as maximum rooting depth resulted in a better fit between simulated and observed cumulative and annual rates of groundwater recharge and capillary rise, but in some cases also decreased the simulation quality of both models in terms of IA and RMSE. The results of this calibration indicated that, in addition to a precise determination of the soil water‐retention functions, vegetation parameters such as rooting depth should also be observed. Without such information, the rooting depth is a calibration parameter. However, in some cases, the uncalibrated application of both models also led to an acceptable fit between measured and simulated model outputs.     

Combining agent-based and stock-flow modelling approaches in a participative analysis of the integrated land system in Reichraming, Austria

The integrated modelling of coupled socio-ecological systems in land-change science requires innovative model concepts capable of grasping the interrelations between socioeconomic and natural components. Here, we discuss the integrated socio-ecological model SERD (Simulation of Ecological Compatibility of Regional Development) that was developed for the municipality of Reichraming in Upper Austria in a participative 2-year process involving local stakeholders. SERD includes three main components: (1) an agent-based actors module that simulates decisions of farmsteads, the municipal administration and other important actors; (2) a spatially explicit (GIS based) land-use module that simulates land-use change at the level of individual parcels of land and (3) an integrated socio-ecological stock-flow module that simulates carbon and nitrogen flows through both socioeconomic and ecological system compartments. We report on outcomes of a scenario analysis that outlines possible future trajectories depending on both external (e.g. agricultural subsidies and prices) and internal (e.g. innovation, willingness to co-operate) factors. We find that both external and internal factors can affect the behaviour of the integrated system considerably. Local and regional policies are found to be able to counteract adverse global socioeconomic conditions to some extent, but not to reverse the trend altogether. We also find strong interdependencies between socioeconomic and ecological components of the system. Fully evaluating these interdependencies is, however, not possible at the local scale alone and will require explicit consideration of higher-level effects in future research.     

A discussion on and alternative to the Penman-Monteith equation

The Penman-Monteith (PMe) equation that estimates evaporation from leaf/canopy surfaces is based on a few approximations. Several authors discussed ensuing errors and suggested improvements. This paper reminds those discussions which ended in the early nineties. It compares linearized PMe− with non-linear iterative solutions and illustrates resulting deviations. It differentiates between deviations for daily and hourly evaporation rate estimates. The latter are found to be higher. It also demonstrates deviations obtained at two different altitudes above sea level. Considering present tendencies to refine evaporation estimates for practical purposes and making use of easily available methods for solving non-linear equations this paper offers a new method to estimate evaporation.In a first step, a simple algebraic term, the surface temperature control sum, is introduced to find approximate differences between air and evaporating surface (leaf, canopy) temperatures. It suggests to concentrate research on the r_s/r_a ratio. A new formula is derived for estimating leaf/canopy surface temperatures for non-water stressed plants.In a second step, the estimates of temperature differences are used to calculate evaporation estimates. This two-step approximation leads to appreciably smaller errors as compared to the PMe-solution over the full range of input parameters of agro-meteorological relevance. It is, however, less accurate than some of methods proposed in literature. The method is meant for practical application in agricultural water management.     

Large-scale experiment shows that nylon leaders reduce shark bycatch and benefit pelagic longline fishers

We assess the performance of wire leaders, which some jurisdictions have banned to reduce shark mortality from pelagic longline fishing. Experiments were conducted off northeastern Australia on commercial vessels that deployed equal numbers of wire and nylon monofilament leaders randomly along their longlines. Catch rates of several species, including sharks, were lower on nylon than on wire leaders, probably because those animals often escape by biting through the nylon leaders. High bite-off rates indicate that as many animals escape from nylon leaders as are caught on nylon leaders. The fate of escaped animals is not known, although large sharks are more likely to survive than are small animals. By contrast, catch rates of valuable bigeye tuna (Thunnus obesus) were higher on nylon than on wire leaders. Bigeye tuna are probably able to see wire leaders and avoid those hooks. The financial benefits of increased bigeye tuna catches outweigh the costs associated with banning wire leaders, such as increased rates of gear loss. Thus, banning wire leaders is an effective way of reducing shark catches that fishers should be keen to adopt.     

Variability in the composition of lupin (Lupinus angustifolius) meals influences their digestible nutrient and energy value when fed to rainbow trout (Oncorhynchus mykiss)

Over a series of seven separate experiments 76 different lupin (Lupinus angustifolius) meals were assessed for their digestible dry matter, protein, amino acid and energy characteristics when fed to rainbow trout. Two reference diets (a common basal diet and a reference lupin meal) were also included in each experiment. Minimal variance in the digestibility parameters of both reference diets was observed among the experiments ensuring that there was a high degree of robustness in the across-experiment evaluations. Using simple and multiple-regression techniques, principal diet and ingredient composition factors affecting diet and ingredient digestibilities and ingredient digestible values were explored within the dataset. Using simple linear regression, it was shown that nitrogen digestibility of the lupin meals was negatively influenced by ingredient lignin content, but positively affected ingredient protein (N × 6.25) content. The energy digestibility of the lupin meals was positively affected by a range of compositional features including protein, sum of amino acids and negatively affected by carbohydrate content. The digestible nutrient and energy content of the meals reflected the combined effects of both ingredient digestibilities and ingredient composition. The digestible nitrogen content of the lupin meals was positively affected by protein (N × 6.25), sum of amino acids and energy content, but was negatively affected by lignin and carbohydrate content. The digestible sum of amino acids was also positively affected by protein, sum of amino acids, but only negatively affected by carbohydrate content, not lignin content. The digestible energy content of the lupin meals was also positively affected by protein, sum of amino acids and their own energy density, but only negatively affected by carbohydrate content. Multiple linear regression modelling supported that together ingredient protein and lignin content were the strongest predictors of digestible protein value, explaining close to 60% of the variability in this parameter. Discrete reassessment of these relationships using non-linear analysis methods provided a stronger interpretation of the ingredient composition effects. In recognition of this, a functional model including terms for ingredient protein and lignin content on the digestible protein value was defined. This study demonstrates that within one raw material type that not only does significant variability in the digestible value of the raw materials exist, but that it is possible to identify compositional features of that raw material that are intrinsically influencing their own digestible value.     

Using unsupervised learning techniques to assess interactions among complex traits in soybeans

Soybean yield components and agronomic traits are connected through physiological pathways that impose tradeoffs through genetic and environmental constraints. Our primary aim is to assess the interdependence of soybean traits by using unsupervised machine learning techniques to divide phenotypic associations into environmental and genetic associations. This study was performed on large scale, jointly analyzing 14 quantitative traits in a large multi-parental population designed for genetic studies. We collected phenotypes from 2012 to 2015 from a soybean nested association panel with 40 families of approximately 140 individuals each. Pearson and Spearman correlations measured phenotypic associations. A multivariate mixed linear model provided genotypic and environmental correlations. To evaluate relationships among traits, the study used principal component and undirected graphical models from phenotypic, genotypic, and environmental correlation matrices. Results indicate that high phenotypic correlation occurs when traits display both genetic and environmental correlations. In genetic terms, length of reproductive period, node number, and canopy coverage play important roles in determining yield potential. Optimal grain yield production occurs when the growing environment favors faster canopy closure and extended reproductive length. Environmental associations found among yield components give insight into the nature of yield component compensation. The use of unsupervised learning methods provides a good framework for investigating interactions among various quantitative traits and defining target traits for breeding.     

CRISPR-Cas Technology in Plant Science

CRISPR-Cas technology has raised considerable interest among plant scientists, both in basic science and in plant breeding. Presently, the generation of random mutations at a predetermined site of the genome is well mastered, just like the targeted insertion of transgenes, although both remain restricted to species or genotypes amenable for plant transformation. On the other hand, true genome editing, i.e. the deliberate replacement of one or several nucleotides of the genome in a predetermined fashion, is limited to some rather particular examples that generally concern genes allowing positive selection, for example tolerance to herbicides. Therefore, further technological developments are necessary to fully exploit the potential of genome editing in enlarging the gene pool beyond the natural variability available in a given species. In principle, the technology can be applied to any quality related, agronomical or ecological trait, under the condition of upstream knowledge on the genes to be targeted and the precise modifications necessary to improve alleles. Published proof of concepts concern a wide range of agronomical traits, the most frequent being disease resistance, herbicide tolerance and the biochemical composition of harvested products. The regulatory status of the plants obtained by CRISPR-Cas technology raises numerous questions, in particular with regard to the plants that carry in their genomes the punctual modifications caused by the presence of the Cas9 nuclease but not the nuclease itself. Without clarification by the competent authorities, CRISPR-Cas technology would continue to be a powerful tool in functional genomics, but its potential in plant breeding would remain untapped.