Newest publications
Physical geography, isolation by distance and environmental variables shape genomic variation of wild barley (Hordeum vulgare L. ssp. spontaneum) in the Southern Levant
(2022) Chang, Che-Wei; Fridman, Eyal; Mascher, Martin; Himmelbach, Axel; Schmid, Karl
Determining the extent of genetic variation that reflects local adaptation in crop-wild relatives is of interest for the purpose of identifying useful genetic diversity for plant breeding. We investigated the association of genomic variation with geographical and environmental factors in wild barley ( Hordeum vulgare L. ssp. spontaneum ) populations of the Southern Levant using genotyping by sequencing (GBS) of 244 accessions in the Barley 1K+ collection. The inference of population structure resulted in four genetic clusters that corresponded to eco-geographical habitats and a significant association between lower gene flow rates and geographical barriers, e.g. the Judaean Mountains and the Sea of Galilee. Redundancy analysis (RDA) revealed that spatial autocorrelation explained 45% and environmental variables explained 15% of total genomic variation. Only 4.5% of genomic variation was solely attributed to environmental variation if the component confounded with spatial autocorrelation was excluded. A synthetic environmental variable combining latitude, solar radiation, and accumulated precipitation explained the highest proportion of genomic variation (3.9%). When conditioned on population structure, soil water capacity was the most important environmental variable explaining 1.18% of genomic variation. Genome scans with outlier analysis and genome-environment association studies were conducted to identify adaptation signatures. RDA and outlier methods jointly detected selection signatures in the pericentromeric regions, which have reduced recombination, of the chromosomes 3H, 4H, and 5H. However, selection signatures mostly disappeared after correction for population structure. In conclusion, adaptation to the highly diverse environments of the Southern Levant over short geographical ranges had a limited effect on the genomic diversity of wild barley. This highlighted the importance of nonselective forces in genetic differentiation.
Assessing the between-country genetic correlation in maize yield using German and Polish official variety trials
(2022) Malik, Waqas Ahmed; Buntaran, Harimurti; Przystalski, Marcin; Lenartowicz, Tomasz; Piepho, Hans-Peter
Official variety testing is performed in many countries by statutory agencies in order to identify the best candidates and make decisions on the addition to the national list. Neighbouring countries can have similarities in agroecological conditions, so it is worthwhile to consider a joint analysis of data from national list trials to assess the similarity in performance of those varieties tested in both countries. Here, maize yield data from official German and Poland variety trials for cultivation and use (VCU) were analysed for the period from 1987 to 2017. Several statistical models that incorporate environmental covariates were fitted. The best fitting model was used to compute estimates of genotype main effects for each country. It is demonstrated that a model with random genotype-by-country effects can be used to borrow strength across countries. The genetic correlation between cultivars from the two countries equalled 0.89. The analysis based on agroecological zones showed high correlation between zones in the two countries. The results also showed that 22 agroecological zones in Germany can be merged into five zones, whereas the six zones in Poland had very high correlation and can be considered as a single zone for maize. The 43 common varieties which were tested in both countries performed equally in both countries. The mean performances of these common varieties in both countries were highly correlated.
Split N application and DMP based nitrification inhibitors mitigate N2O losses in a soil cropped with winter wheat
(2022) Guzman-Bustamante, Ivan; Schulz, Rudolf; Müller, Torsten; Ruser, Reiner
Nitrogen (N) fertilization to crops might lead to formation and release of reactive N—e.g. nitrate, ammonium, ammonia, nitrous oxide (N2O) —, contributing to eutrophication, atmospheric pollution, and climate change. Use of nitrification inhibitors and splitting of N fertilizer may reduce the N2O emission from arable soils cropped with winter wheat. We tested different N fertilizers treated with 3,4-dimethylpyrazol phosphate (DMPP) and 3,4-dimethylpyrazol succinic acid (DMPSA) by applying 180 kg N ha−1 in different N splitting strategies in a full annual field experiment on a loamy soil in Southwest Germany. A threefold split fertilization led to an emission of 2.3 kg N2O–N ha−1 a−1 (corresponding to a reduction of 19%) compared to a single application of ammonium sulphate nitrate (ASN) (p = 0.07). A single application rate of ASN with DMPP resulted in an emission of 1.9 kg N2O–N ha−1 a−1 and reduced N2O emissions from an ASN treatment without NI by 33%. Calcium ammonium nitrate (CAN) with DMPSA reduced N2O emissions during the vegetation period by 38% compared to CAN without a nitrification inhibitor, but this was offset by high emissions after harvest, which was driven by soil tillage with an annual reduction of 26% (CAN: 2.9 kg N2O–N ha−1 a−1; CAN + DMPSA: 2.1 kg N2O–N ha−1 a−1; p = 0.11). Among our tested treatments, a twofold split application of ASN with DMPP efficiently reduced N2O emissions and maintained grain yield when compared to the traditional system with threefold application without nitrification inhibitor. Despite resulting in lower protein contents in the twofold split application, this treatment should be further investigated as a potential compromise between wheat yield and quality optimization and climate protection.
Boosting the scalability of farm-level models: Efficient surrogate modeling of compositional simulation output
(2023) Troost, Christian; Parussis-Krech, Julia; Mejaíl, Matías; Berger, Thomas
Surrogate modeling can overcome computational and data-privacy constraints of micro-scale economic models and support their incorporation into large-scale simulations and interactive simulation experiments. We compare four data-driven methods to reproduce the aggregated crop area response simulated by farm-level modeling in response to price variation. We use the isometric log-ratio transformation to accommodate the compositional nature of the output and sequential sampling with stability analysis for efficient model selection. Extreme gradient boosting outperforms multivariate adaptive regressions splines, random forest regression, and classical multinomial-logistic regression and achieves high goodness-of-fit from moderately sized samples. Explicitly including ratio terms between price input variables considerably improved prediction, even for highly automatic machine learning methods that should in principle be able to detect such input variable interaction automatically. The presented methodology provides a solid basis for the use of surrogate modeling to support the incorporation of micro-scale models into large-scale integrated simulations and interactive simulation experiments with stakeholders.
The volatility of housing prices: Do different types of financial intermediaries affect housing market cycles differently?
(2024) Braun, Julia; Burghof, Hans-Peter; Langer, Julius; Sommervoll, Dag Einar
Housing markets display several correlations to multiple economic sectors of an economy. Their enormous impact on economies’ health, wealth, and stability is uncontroversial. Interestingly, the forms of financing residential property vary widely between the different countries in terms of both, the available product types and the institutions offering them. This research examines the implications of different financial intermediaries on housing market cycles with special emphasis on two institutional types, conventional banks and building and loan associations. Introducing a heterogeneous agent-based model, the interactions of buyers, sellers, and the two types of credit institutions are assessed. Heterogeneous economic principles and expectations of agents create endogenous market conditions which are strongly influenced by the lending practices of financial intermediaries. Focusing primarily on collateral values to decide about lending, conventional banks may contribute to volatile housing markets which are prone to recessions. Building and loan associations, on the other hand, rely to a greater extent on endogenously created borrower information. Thus, they are able to cushion the volatility of house prices caused by procyclical mortgage lending of conventional banks and increase the stability of the housing market. Simulations show that the most stable market conditions are attained if both types of financial intermediaries serve the mortgage lending market jointly. Furthermore, transaction and homeownership rates are the highest in this market setting. These findings advocate in favor of diversified financial markets.