Alexander Walther

Natural variation in a homolog of Antirrhinum CENTRORADIALIS contributed to spring growth habit and environmental adaptation in cultivated barley

As early farming spread from the Fertile Crescent in the Near East around 10,000 years before the present, domesticated crops encountered considerable ecological and environmental change. Spring-sown crops that flowered without the need for an extended period of cold to promote flowering and day length–insensitive crops able to exploit the longer, cooler days of higher latitudes emerged and became established. To investigate the genetic consequences of adaptation to these new environments, we identified signatures of divergent selection in the highly differentiated modern-day spring and winter barleys. In one genetically divergent region, we identify a natural variant of the barley homolog of Antirrhinum CENTRORADIALIS (HvCEN) as a contributor to successful environmental adaptation. The distribution of HvCEN alleles in a large collection of wild and landrace accessions indicates that this involved selection and enrichment of preexisting genetic variants rather than the acquisition of mutations after domestication.

Temporal and spatial temperature variability and change over Spain during 1850–2005

We analyze temporal and spatial patterns of temperature change over Spain during the period 1850–2005, using daily maximum (T max), minimum (T min), and mean (T mean) temperatures from the 22 longe ...

Separating the wheat from the chaff – a strategy to utilize plant genetic resources from ex situ genebanks

The need for higher yielding and better-adapted crop plants for feeding the worlds rapidly growing population has raised the question of how to systematically utilize large genebank collections with their wide range of largely untouched genetic diversity. Phenotypic data that has been recorded for decades during various rounds of seed multiplication provides a rich source of information. Their usefulness has remained limited though, due to various biases induced by conservation management over time or changing environmental conditions. Here, we present a powerful procedure that permits an unbiased trait-based selection of plant samples based on such phenotypic data. Applying this technique to the wheat collection of one of the largest genebanks worldwide, we identified groups of plant samples displaying contrasting phenotypes for selected traits. As a proof of concept for our discovery pipeline, we resequenced the entire major but conserved flowering time locus Ppd-D1 in just a few such selected wheat samples – and nearly doubled the number of hitherto known alleles.

Diurnal cycle of precipitation amount and frequency in Sweden: observation versus model simulation

This study investigated the diurnal cycle of precipitation in Sweden using hourly ground observations for 1996–2008. General characteristics of phase and amplitude for the diurnal cycle of precipitation, both in amount and frequency, were identified. In the warm season (April—September), the ‘typical’ afternoon (14–16 LST) peaks are dominant over inland Sweden, whereas late night to early morning (04–06 LST) peaks with relatively weak amplitude are discernable in the east coast along the Baltic Sea. The diurnal variation is almost negligible in the cold season (October—March), due to the weak solar radiation at high latitudes. The variations of convective activity forced by solar heating and modulated by geographical characteristics were suggested as primarily factors to invoke the cycles and spatial variation identified. The observed cycle was compared with the cycle simulated by a regional climate model. The model fairly well captures the spatial pattern of the phase of the diurnal cycle. However, the warm season afternoon peak is simulated too early and too uniformly across the stations, associated with too frequent occurrences of convective rainfall events with relatively light intensity. These discrepancies point to the need to improve the convection parametrization and geographic representation of the model.

Genetic Diversity and Population Structure in a Legacy Collection of Spring Barley Landraces Adapted to a Wide Range of Climates

Global environmental change and increasing human population emphasize the urgent need for higher yielding and better adapted crop plants. One strategy to achieve this aim is to exploit the wealth of so called landraces of crop species, representing diverse traditional domesticated populations of locally adapted genotypes. In this study, we investigated a comprehensive set of 1485 spring barley landraces (Lrc1485) adapted to a wide range of climates, which were selected from one of the largest genebanks worldwide. The landraces originated from 5° to 62.5° N and 16° to 71° E. The whole collection was genotyped using 42 SSR markers to assess the genetic diversity and population structure. With an average allelic richness of 5.74 and 372 alleles, Lrc1485 harbours considerably more genetic diversity than the most polymorphic current GWAS panel for barley. Ten major clusters defined most of the population structure based on geographical origin, row type of the ear and caryopsis type – and were assigned to specific climate zones. The legacy core reference set Lrc648 established in this study will provide a long-lasting resource and a very valuable tool for the scientific community. Lrc648 is best suited for multi-environmental field testing to identify candidate genes underlying quantitative traits but also for allele mining approaches.

Projecting Future Local Precipitation and Its Extremes for Sweden

Abstract A procedure to obtain future local precipitation characteristics focused on extreme conditions has been developed based on a weather generator. The method involves six major steps: (1) the weather generator was calibrated using observed daily precipitation at 220 wedish stations during 1961–2004; (2) present and future daily precipitation characteristics for the wedish stations from two global climate models, namely and HadCM3, were used to calculate weather generator parameters for the present and future climates at global climate model spatial scales; (3) the ratio of the weather generator parameters for the present climate simulated by the global climate models to those calculated for each station falling into the global climate model grid box were computed for all the stations; (4) these ratios were also assumed to be valid in the future climate, that way the future parameters for each station for the global climate model projected future climate could be calculated; (5) using the estimated future parameters of the weather generator, the future daily precipitation at each station could be simulated by the weather generator; (6) the simulated daily precipitation was used to compute eight indices describing mean and extreme precipitation climates. The future mean and extreme precipitation characteristics at the stations under the Second Report on Emission Scenarios A2 scenario were obtained and presented. An overall increasing trend for frequency and intensity of the indices are identified for the majority of the stations studied. The developed downscaling methodology is relatively simple but useful in deriving local precipitation changes, including changes in the precipitation extremes.

Characterizing and visualizing spatio-temporal patterns in hourly precipitation records

We develop new techniques to summarise and visualise spatial patterns of coincidence in weather events such as more or less heavy precipitation at a network of meteorological stations. The cosine similarity measure, which has a simple probabilistic interpretation for vectors of binary data, is generalised to characterise spatial dependencies of events that may reach different stations with a variable time lag. More specifically, we reduce such patterns into three parameters (dominant time lag, maximum cross-similarity, and window-maximum similarity) that can easily be computed for each pair of stations in a network. Furthermore, we visualise such three-parameter summaries by using colour-coded maps of dependencies to a given reference station and distance-decay plots for the entire network. Applications to hourly precipitation data from a network of 93 stations in Sweden illustrate how this method can be used to explore spatial patterns in the temporal synchrony of precipitation events.

Summary of the Estimated Trends

While the previous chapter can be used to find trends for all individual indices at all stations/regions, this chapter attempts to provide an overview of the trends for the three periods. Since there are many maps and figures in the previous chapter, summary statistics of the results are necessary to obtain an overview. This chapter gives statistics of the trends in terms of the trend estimates, fraction of positive and negative trends and their significance (see chapter 3 for definitions) in the form of tables.

Atlas of the Trend Analysis

In this chapter, the results of the trend analysis for each index, station or region are presented in the form of maps and time-series plots. The maps, however, are only used for the most recent period (1901–2000) due to the limited number of stations in earlier periods. For each period, seasonal indices starting with spring (MAM) and ending with winter (DJF) are presented. The order of presentation is Tmin/Tmax, followed by Tmean and Precipitation. To make it easier to find an index in a given season and for a given period, a header is put on each page to indicate the period, season, and index group. The circles in the maps indicate station locations for the two longer periods where results for individual stations are presented. All the maps contain a colour bar symmetric around zero and a title. The range is determined by the highest absolute value appearing in the map. An index dependent general colour scheme is used throughout the whole atlas. For temperature indices, the colour scale ranges blue-green-red where red colours indicate warming and blue colours cooling conditions. For example, an increase in Tmean would be shown in red as well as a decreased number of days below the second percentile. Trends in precipitation indices are visualized using a brown-yellow-green colour scale where brownish colour indicate drier and greenish colours wetter conditions. Trend significance is indicated for each symbol marking a station (circles) or regional averages (squares) using significance levels of p < 0.05 and p < 0.01. Analysis period, season, index and the unit of the trend are provided in every figure title.