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.     

Extinction and ecosystem function in the marine benthos

Rapid changes in biodiversity are occurring globally, yet the ecological impacts of diversity loss are poorly understood. Here we use data from marine invertebrate communities to parameterize models that predict how extinctions will affect sediment bioturbation, a process vital to the persistence of aquatic communities. We show that species extinction is generally expected to reduce bioturbation, but the magnitude of reduction depends on how the functional traits of individual species covary with their risk of extinction. As a result, the particular cause of extinction and the order in which species are lost ultimately govern the ecosystem-level consequences of biodiversity loss.     

Forms of memory failure

Memory may fail in a variety of ways. Patients with Korsakoff's syndrome demonstrate global memory deficits similar to those seen in patients with early progressive dementia. Korsakoff's patients, however, may recall rules and principles for organizing information and can gain access to their previously acquired knowledge (semantic memory), whereas recent memory may be grossly impaired. In contrast, dementia patients may have little access to previously acquired knowledge and therefore have great difficulty in organizing and encoding ongoing events. These contrasting forms of memory failure have implications for understanding the structure and mechanisms of memory and learning, particularly the relationship between episodic and semantic memory, as well as the development of therapeutic strategies for cognitive impairments.     

Bioefficacy of compounds from Dittrichia viscosa (Asteraceae) as protectant of chickpea seeds against the cowpea seed beetle Callosobruchus maculatus (Coleoptera: Chrysomelidae)

Journal of Plant Diseases and Protection - The efficacy of four bi- and tri-cyclic sesquiterpenes, namely inuloxins A, B and C and α-costic acid, extracted from aerial parts of Dittrichia...     

Agronomic traits of soybean cultivars released in different decades after grafting record‐yield cultivar as rootstock

Breeders have seldom considered the selection for root traits during the genetic improvement in soybean. It is hypothesized that grain yield would be increased by the root function improvement, especially for the current cultivars. The objective of this grafting experiment was to determine the effect of record‐yield cultivars L14 or Z35 as rootstocks on agronomic traits of cultivars released in different decades. A total of 11 cultivars, released in different decades, were used to graft onto L14 or Z35 rootstocks. The agronomic traits were measured in the pot‐culture experiments. Grafting cultivars released in different decades onto L14 or Z35 rootstocks resulted in higher yield, 100‐seed mass and apparent harvest index as compared with those of non‐grafted or self‐grafted plants. Grain yield gain of cultivars grafted onto record‐yield cultivar rootstocks was 0.40 g/plant/year from 1966 to 2006, which was larger than that of non‐grafts and self‐grafts (0.27 g/plant/year). The yield of current cultivars should increase more if their root functions were improved.     

Characterization of common bean wild populations for their in situ conservation in Northwestern Argentina

In situ conservation of wild species is a method of conservation that allows keeping populations in their natural environments, and set the strategies for maintaining the natural populations. The Active Bank of Northwestern Argentina (BANOA) is in charge of the in situ conservation of wild populations of common bean (Phaseolus vulgaris L.) in Northwestern Argentina (NOA), and has an ex situ collection of 401 landraces and 221 wild accessions from the NOA. We evaluated the phenotypic diversity of 68 common bean wild populations from the NOA both in protected and unprotected areas, finding a moderate variation among them. Ten phenotypic reproductive characteristics related to pod and seed displayed significant differences in the analysis of variance; these traits together with the seed weight were the basis for the multivariate analysis. The cluster analysis ordered the populations in 12 groups but trends in geographical distribution or phenotypical variation were not recognized. For the conservation in situ of the wild bean populations, their diversity should be considered. Two types of populations can be highlighted: (i) candidates for in situ conservation in order to preserve the novel variation generated by convergence with cultivated sympatric germplasm (populations 433, 437, 471, 509, 513 and 517) and (ii) those whose phenotype represents clearly the wild status and should be preserved in situ as such in their current status (populations 480, 495, 496, 525 and 533).     

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.