Urs Albert Treier

Crop wild relatives (CWR) are wild plant taxa that are closely related to crops and other cultivated species. The importance of conserving CWR genetic diversity as a valuable source of variation for plant breeding has been regularly brought forward, and knowledge about the distribution of genetic diversity within and among natural populations can aid in efficient conservation and increased availability of CWR genetic resources. Within the Nordic countries (Iceland, Norway, Denmark, Sweden and Finland), the European wild strawberry, Fragaria vesca L., has been recognized as a CWR of priority. However, information about the distribution of its within- and among-population genetic diversity in the Nordic countries is limited. In total, 180 individuals from twelve populations covering the majority of the Nordic range of F. vesca were genotyped with 14 microsatellite markers. Overall, populations had high inbreeding coefficient F _IS values, although a large variation was observed across the region. In agreement with expectations, populations from higher latitudes tended to have less genetic diversity and a higher presence of genetically identical individuals, possibly the result of clonal propagation. The analysis of molecular variance (AMOVA) showed that genetic diversity was primarily distributed among populations within countries, supporting a regional conservation approach. Analysis of the geographic distribution of the genetic diversity with STRUCTURE and principal component analyses and calculation of pairwise F _ST values revealed that the studied individuals formed clusters which partially, but not completely, corresponded to the geographical origin of the populations. The inclusion of multiple individuals per populations allowed geographic clustering to be detected on a finer scale than previously described. Ex situ conservation of F. vesca is recommended mainly to improve availability of these genetic resources for research and breeding and based on the within- and among-population distribution of genetic diversity, prioritizations are suggested.

Spatiotemporal fields are a fundamental representation for describing spatially continuous phenomena, yet existing models often treat value assignment as an implicit relation between locations and values. This paper introduces the Spatiotemporal Field Ontology Pattern (SFOP), an ontology design pattern that adopts an observation-centered view in which field values are generated through observation processes linking intended spatiotemporal locations, observable properties, and observation results (i.e., the measured or derived values). The pattern distinguishes between a field’s defined domain, representing the locations where observations are intended, and its observed domain, representing the locations for which observations actually exist. This distinction enables an explicit representation of incomplete, evolving, and derived observations. SFOP aligns with existing standards, including SOSA/SSN, GeoSPARQL, and OWL-Time, while supporting the inference of field properties and observed domains from observational evidence. The resulting pattern provides a semantically grounded foundation for representing, querying, and reasoning over spatiotemporal fields in knowledge graphs.

Raster–vector clipping is a fundamental operation in geospatial analysis. In practice, however, it is typically implemented as a binary rule that assigns pixels as either fully inside or outside a target geometry. Although widely used, clipping is rarely defined as a generic spatial operator with explicit inclusion semantics. This paper introduces a Fractional Raster–Vector Clipping Operator that models pixel inclusion through proportional areal overlap and formalizes clipping as a mathematically specified operator. The formulation is independent of any specific software environment and is accompanied by a generic algorithm. The algorithm avoids costly universal containment tests by restricting explicit geometric evaluation to a boundary region derived from pixel dimensions. The operator is implemented natively in PostgreSQL/PostGIS and evaluated using Denmark’s national land-cover dataset (Basemap04, 2021) aggregated across multiple spatial resolutions. The results show that conventional binary clipping produces systematic and resolutiondependent underestimation relative to the fractional reference. Explicit boundary semantics therefore establish a consistent and resolution-aware basis for raster–vector aggregation in multi-scale spatial analysis.

The current global crisis of biodiversity loss calls for urgent conservation actions for many species, not the least wild species related to crop plants. These crop wild relatives are considered harbouring genetic diversity of major importance for future crop plant improvement, e.g. adaptation to climate change. Hence, their conservation needs to be a priority. To ensure the long-term conservation and to maximize the utility value of these species, it is important that as much of their genetic diversity as possible is conserved. Thus, the distribution of intraspecific diversity must be taken into consideration when planning conservation efforts. Caraway, Carum carvi L., has been cultivated since medieval times and is today one of the most important spice crops worldwide. In order to identify populations that would be of particular interest for in situ and ex situ conservation and for use in plant breeding we evaluated the geographic distribution of intraspecific diversity in populations of Carum carvi in the Nordic region (Iceland, Denmark, Norway, Sweden and Finland). Using a genotyping by sequencing approach, we genotyped 198 individuals from 16 Nordic populations. The amount of intrapopulation genetic diversity was similar among populations (mean H_e = 0.29), and the diversity was structured in an east–westerly manner, probably reflecting colonisation patterns associated with different glacial refugia. In addition, some populations likely have a history shaped by human interventions. The results have important conservation implications and based on the outcome of this study, populations of conservation priority are suggested.

Carbon (δ13C) and oxygen (δ18O) isotopes provide key insights into plant physiological processes, including water-use efficiency, water source utilization, and carbon assimilation. In Arctic ecosystems, changes in snow conditions may influence shrub growth, physiology, and isotopic composition by altering soil moisture, temperature, and soil nutrient conditions with carry-over effects from winter to the main growing season. We analyzed δ13C and δ18O values in two dominant Arctic shrub species, Salix glauca (gray willow) and Betula nana (dwarf birch), growing at a snow fence experiment implemented summer 2012 on Disko Island, Greenland. Using novel laser ablation methods with beam sizes of 100μm and 40μm for δ18O and δ13C, respectively, we analyzed growth rings from 20 individuals per species, covering the period 2007-2017. In total, we obtained 255 δ18O measurements (122 for S. glauca and 133 for B. nana) and 352 δ13C measurements (175 for S. glauca and 177 for B. nana). We obtained annual resolution measurements of δ18O for 162 rings and of δ13C for 320 rings, despite narrow rings averaging ~93μm (~85μm for S. glauca and ~100μm for B. nana). Our preliminary results indicate that increased snow depth due to the snow fence did not significantly alter the carbon or oxygen values in either species. While δ18O values were similar between the species, suggesting similar water sources regardless of snow depth, S. glauca had significantly enriched δ13C values than B. nana, indicating greater water-use efficiency, which may give it a competitive advantage during drier periods. These findings suggest that species-specific physiological traits, rather than snow depth changes, may be the primary drivers of isotopic differences in Arctic shrubs, with implications for shrub expansion and Arctic carbon and water cycles.

Aims: We introduce ReSurveyEurope — a new data source of resurveyed vegetation plots in Europe, compiled by a collaborative network of vegetation scientists. We describe the scope of this initiative, provide an overview of currently available data, governance, data contribution rules, and accessibility. In addition, we outline further steps, including potential research questions.Results: ReSurveyEurope includes resurveyed vegetation plots from all habitats. Version 1.0 of ReSurveyEurope contains 283,135 observations (i.e., individual surveys of each plot) from 79,190 plots sampled in 449 independent resurvey projects. Of these, 62,139 (78%) are permanent plots, that is, marked in situ, or located with GPS, which allow for high spatial accuracy in resurvey. The remaining 17,051 (22%) plots are from studies in which plots from the initial survey could not be exactly relocated. Four data sets, which together account for 28,470 (36%) plots, provide only presence/absence information on plant species, while the remaining 50,720 (64%) plots contain abundance information (e.g., percentage cover or cover–abundance classes such as variants of the Braun‐Blanquet scale). The oldest plots were sampled in 1911 in the Swiss Alps, while most plots were sampled between 1950 and 2020.Conclusions: ReSurveyEurope is a new resource to address a wide range of research questions on fine‐scale changes in European vegetation. The initiative is devoted to an inclusive and transparent governance and data usage approach, based on slightly adapted rules of the well‐established European Vegetation Archive (EVA). ReSurveyEurope data are ready for use, and proposals for analyses of the data set can be submitted at any time to the coordinators. Still, further data contributions are highly welcome.

Litter decomposition represents a major path for atmospheric carbon influx into Arctic soils, thereby controlling below‐ground carbon accumulation. Yet, little is known about how tundra litter decomposition varies with microenvironmental conditions, hindering accurate projections of tundra soil carbon dynamics with future climate change. Over 14 months, we measured landscape‐scale decomposition of two contrasting standard litter types (Green tea and Rooibos tea) in 90 plots covering gradients of micro‐climate and ‐topography, vegetation cover and traits, and soil characteristics in Western Greenland. We used the tea bag index (TBI) protocol to estimate relative variation in litter mass loss, decomposition rate ( k ) and stabilisation factor ( S ) across space, and structural equation modelling (SEM) to identify relationships among environmental factors and decomposition. Contrasting our expectations, microenvironmental factors explained little of the observed variation in both litter mass loss, as well as k and S , suggesting that the variables included in our study were not the major controls of decomposer activity in the soil across the studied tundra landscape. We use these unexpected findings of our study combined with findings from the current literature to discuss future avenues for improving our understanding of the drivers of tundra decomposition and, ultimately, carbon cycling across the warming Arctic.