Jakob Friedrich Ehrhart

Abstract After many decades of effective control of stem rust caused by the Puccinia graminis f.sp. tritici, (hereafter Pgt) the reported emergence of race TTKSK/Ug99 of Pgt in Uganda reignited concerns about epidemics worldwide because ∼90% of world wheat cultivars had no resistance to the new race. Since it was initially detected in Uganda in 1998, Ug99 variants have now been identified in thirteen countries in Africa and the Middle East. Stem rust has been a major problem in the past, and concern is increasing about the risk of return to Central and East Asia. Whilst control programs in North America and Europe relied on the use of resistant cultivars in combination with eradication of barberry (Berberis spp.), the alternate host required for the stem rust pathogen to complete its full lifecycle, the focus in East Asia was principally on the use of resistant wheat cultivars. Here, we investigate potential airborne transmission pathways for stem rust outbreaks in the Middle East to reach East Asia using an integrated modelling framework combining estimates of fungal spore deposition from an atmospheric dispersion model, environmental suitability for spore germination, and crop calendar information. We consider the role of mountain ranges in restricting transmission pathways, and we incorporate a representation of a generic barberry species into the lifecycle. We find viable transmission pathways to East Asia from the Middle East to the north via Central Asia and to the south via South Asia and that an initial infection in the Middle East could persist in East Asia for up to three years due to the presence of the alternate host. Our results indicate the need for further assessment of barberry species distributions in East Asia and appropriate methods for targeted surveillance and mitigation strategies should stem rust incidence increase in the Middle East region.

The Colorado potato beetle (CPB, Leptinotarsa decemlineata) is a protected zone quarantine pest in the southern parts of Finland and Sweden. The units responsible for pest risk assessments in Finland and Sweden were requested to identify the geographical areas likely to be suitable for establishment of the CPB given a climate change scenario that covers the years 2023–2040.

The Khanka Lowland forest-steppe is the most eastern outpost of the Eurasian steppe biome. It includes unique grassland plant communities with rare steppe species. These coenosis have changed under the influence of anthropogenic activity, especially during the last 100 years and included both typical steppe species and nemoral mesophytic species. To distinguish these ecological groups of plants the random forest method with three datasets of environmental variables was applied. Specifically, a model of classification with the most important bioindices to predict a mesophytic ecological group of plants with a sensitivity greater than 80% was constructed. The data demonstrated the presence of steppe species that arrived at different times in the Primorye Territory. Most of these species are associated with the Mongolian-Daurian relict steppe complex and habit in the Khanka Lowland. Other species occur only in mountains in Primorye Territory and do not persist in the Khanka Lowland. These findings emphasize the presence of relict steppe communities with a complex of true steppe species in the Khanka Lowland. Steppe communities exhibit features of anthropogenic influence definitely through the long land use period but are not anthropogenic in origin. The most steppe species are located at the eastern border of distribution in the Khanka Lowlands and are valuable in terms of conservation and sources of information about steppe species origin and the emergence of the steppe biome as a whole.

Coniferous forests are under severe threat of the rapid anthropogenic climate warming. Abies (firs), the fourth‐largest conifer genus, is a keystone component of the boreal and temperate dark‐coniferous forests and harbors a remarkably large number of relict taxa. However, the uncertainty of the phylogenetic and biogeographic history of Abies significantly impedes our prediction of future dynamics and efficient conservation of firs. In this study, using 1,533 nuclear genes generated from transcriptome sequencing and a complete sampling of all widely recognized species, we have successfully reconstructed a robust phylogeny of global firs, in which four clades are strongly supported and all intersectional relationships are resolved, although phylogenetic discordance caused mainly by incomplete lineage sorting and hybridization was detected. Molecular dating and ancestral area reconstruction suggest a Northern Hemisphere high‐latitude origin of Abies during the Late Cretaceous, but all extant firs diversified during the Miocene to the Pleistocene, and multiple continental and intercontinental dispersals took place in response to the late Neogene climate cooling and orogenic movements. Notably, four critically endangered firs endemic to subtropical mountains of China, including A. beshanzuensis, A. ziyuanensis, A. fanjingshanensis and A. yuanbaoshanensis from east to west, have different origins and evolutionary histories. Moreover, three hotspots of species richness, including western North America, central Japan, and the Hengduan Mountains, were identified in Abies. Elevation and precipitation, particularly precipitation of the coldest quarter, are the most significant environmental factors driving the global distribution pattern of fir species diversity. Some morphological traits are evolutionarily constrained, and those linked to elevational variation (e.g., purple cone) and cold resistance (e.g., pubescent branch and resinous bud) may have contributed to the diversification of global firs. Our study sheds new light on the spatiotemporal evolution of global firs, which will be of great help to forest management and species conservation in a warming world.

How to effectively obtain species‐related low‐dimensional data from massive environmental variables has become an urgent problem for species distribution models (SDMs). In this study, we will explore whether dimensionality reduction on environmental variables can improve the predictive performance of SDMs. We first used two linear (i.e., principal component analysis (PCA) and independent components analysis) and two nonlinear (i.e., kernel principal component analysis (KPCA) and uniform manifold approximation and projection) dimensionality reduction techniques (DRTs) to reduce the dimensionality of high‐dimensional environmental data. Then, we established five SDMs based on the environmental variables of dimensionality reduction for 23 real plant species and nine virtual species, and compared the predictive performance of those with the SDMs based on the selected environmental variables through Pearson's correlation coefficient (PCC). In addition, we studied the effects of DRTs, model complexity, and sample size on the predictive performance of SDMs. The predictive performance of SDMs under DRTs other than KPCA is better than using PCC. And the predictive performance of SDMs using linear DRTs is better than using nonlinear DRTs. In addition, using DRTs to deal with environmental variables has no less impact on the predictive performance of SDMs than model complexity and sample size. When the model complexity is at the complex level, PCA can improve the predictive performance of SDMs the most by 2.55% compared with PCC. At the middle level of sample size, the PCA improved the predictive performance of SDMs by 2.68% compared with the PCC. Our study demonstrates that DRTs have a significant effect on the predictive performance of SDMs. Specifically, linear DRTs, especially PCA, are more effective at improving model predictive performance under relatively complex model complexity or large sample sizes.

Chestnut, Castanea sativa Miller (Fagales: Fagaceae), is an ecologically and economically important tree species of the forest ecosystem in Southern Europe, North-Western Europe, Western Asia, North Africa, and the Caucasus. The distributional range of chestnut in Europe has been highly modified by humans since ancient times. Biotic and abiotic factors have dramatically changed its distribution. Historic anthropogenic range expansion makes it difficult to identify habitat requirements for natural stands of chestnut. In the Caucasus, natural stands of chestnut survived in glacial forest refugia and landscapes that have been difficult for humans to colonize. To identify the species reliable habitat requirements, we estimated the relationship between climatic variables and 620 occurrence locations of natural chestnut stands from the Caucasus and validated the model using GBIF data from outside the Caucasus. We found that our best model is reasonably accurate and the data from the Caucasus characterize chestnut stands throughout the species range well.

Aim Patterns of individual variation are key to testing hypotheses about the mechanisms underlying biogeographic patterns. If species distributions are determined by environmental constraints, then populations near range margins may have reduced performance and be adapted to harsher environments. Model organisms are potentially important systems for biogeographical studies, given the available range‐wide natural history collections, and the importance of providing biogeographical context to their genetic and phenotypic diversity.LocationGlobal.TaxonArabidopsis thaliana (‘Arabidopsis’).MethodsWe fit occurrence records to climate data, and then projected the distribution of Arabidopsis under last glacial maximum, current and future climates. We confronted model predictions with individual performance measured on 2194 herbarium specimens, and we asked whether predicted suitability was associated with life history and genomic variation measured on ~900 natural accessions.ResultsThe most important climate variables constraining the Arabidopsis distribution were winter cold in northern and high elevation regions and summer heat in southern regions. Herbarium specimens from regions with lower habitat suitability in both northern and southern regions were smaller, supporting the hypothesis that the distribution of Arabidopsis is constrained by climate‐associated factors. Climate anomalies partly explained interannual variation in herbarium specimen size, but these did not closely correspond to local limiting factors identified in the distribution model. Late‐flowering genotypes were absent from the lowest suitability regions, suggesting slower life histories are only viable closer to the centre of the realized niche. We identified glacial refugia farther north than previously recognized, as well as refugia concordant with previous population genetic findings. Lower latitude populations, known to be genetically distinct, are most threatened by future climate change. The recently colonized range of Arabidopsis was well‐predicted by our native‐range model applied to certain regions but not others, suggesting it has colonized novel climates.Main ConclusionsIntegration of distribution models with performance data from vast natural history collections is a route forward for testing biogeographical hypotheses about species distributions and their relationship with evolutionary fitness across large scales.

Predicting the likelihood that non-native species will be introduced into new areas remains one of conservation’s greatest challenges and, consequently, it is necessary to adopt adequate management measures to mitigate the effects of future biological invasions. At present, not much information is available on the areas in which non-native aquatic plant species could establish themselves in the Iberian Peninsula. Species distribution models were used to predict the potential invasion risk of (1) non-native aquatic plant species already established in the peninsula (32 species) and (2) those with the potential to invade the peninsula (40 species). The results revealed that the Iberian Peninsula contains a number of areas capable of hosting non-native aquatic plant species. Areas under anthropogenic pressure are at the greatest risk of invasion, and the variable most related to invasion risk is temperature. The results of this work were used to create the Invasion Risk Atlas for Alien Aquatic Plants in the Iberian Peninsula, a novel online resource that provides information about the potential distribution of non-native aquatic plant species. The atlas and this article are intended to serve as reference tools for the development of public policies, management regimes, and control strategies aimed at the prevention, mitigation, and eradication of non-native aquatic plant species.

Background Poa annua (annual bluegrass) is an allotetraploid turfgrass, an agronomically significant weed, and one of the most widely dispersed plant species on earth. Here, we report the chromosome-scale genome assemblies of P. annua’s diploid progenitors, P. infirma and P. supina, and use multi-omic analyses spanning all three species to better understand P. annua’s evolutionary novelty. Results We find that the diploids diverged from their common ancestor 5.5 – 6.3 million years ago and hybridized to form P. annua  ≤ 50,000 years ago. The diploid genomes are similar in chromosome structure and most notably distinguished by the divergent evolutionary histories of their transposable elements, leading to a 1.7 × difference in genome size. In allotetraploid P. annua, we find biased movement of retrotransposons from the larger (A) subgenome to the smaller (B) subgenome. We show that P. annua’s B subgenome is preferentially accumulating genes and that its genes are more highly expressed. Whole-genome resequencing of several additional P. annua accessions revealed large-scale chromosomal rearrangements characterized by extensive TE-downsizing and evidence to support the Genome Balance Hypothesis. Conclusions The divergent evolutions of the diploid progenitors played a central role in conferring onto P. annua its remarkable phenotypic plasticity. We find that plant genes (guided by selection and drift) and transposable elements (mostly guided by host immunity) each respond to polyploidy in unique ways and that P. annua uses whole-genome duplication to purge highly parasitized heterochromatic sequences. The findings and genomic resources presented here will enable the development of homoeolog-specific markers for accelerated weed science and turfgrass breeding .

Modelling was carried out using maximum entropy model (MaxEnt) to explore and predict the invasion potential of littleseed canarygrass (Phalaris minor Retz.) in India under current as well as future climatic conditions under Representative Concentration Pathways (RCPs) 4.5 and 8.5 for the years 2050 and 2070. Mutually least correlated 8 bioclimatic variables along with soil and elevation data were used for the modelling over 223 occurrence locations of the species. Jackknife test revealed the significance of temperature derived variables viz. temperature seasonality, annual mean temperature and minimum temperature of the coldest month in governing the potential distribution of P. minor. Currently, 21% of India’s area is either highly (9%) or moderately (12%) suitable as habitat for P. minor. Our model predicts approximately 90% contraction in the area considered to be highly or moderately suitable climatically between 2050 and 2070 under both moderate and high emissions scenarios. Thus, under future climate, a significant niche shift by the species and decreased suitability was observed compared to the current distribution. The present study is first of its kind in exploring the invasion potential of alien invasive weed P. minor under climate change scenarios which is a current threat to rice-wheat system in Indo-Gangetic plains of India.