Science Enabled by Specimen Data

Zhang, H., W. Guo, and W. Wang. 2023. The dimensionality reductions of environmental variables have a significant effect on the performance of species distribution models. Ecology and Evolution 13. https://doi.org/10.1002/ece3.10747

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.

Metreveli, V., H. Kreft, I. Akobia, Z. Janiashvili, Z. Nonashvili, L. Dzadzamia, Z. Javakhishvili, and A. Gavashelishvili. 2023. Potential Distribution and Suitable Habitat for Chestnut (Castanea sativa). Forests 14: 2076. https://doi.org/10.3390/f14102076

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.

Yim, C., E. S. Bellis, V. L. DeLeo, D. Gamba, R. Muscarella, and J. R. Lasky. 2023. Climate biogeography of Arabidopsis thaliana: Linking distribution models and individual variation. Journal of Biogeography. https://doi.org/10.1111/jbi.14737

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.

Rodríguez-Merino, A. 2023. Identifying and Managing Areas under Threat in the Iberian Peninsula: An Invasion Risk Atlas for Non-Native Aquatic Plant Species as a Potential Tool. Plants 12: 3069. https://doi.org/10.3390/plants12173069

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.

Benson, C. W., M. R. Sheltra, P. J. Maughan, E. N. Jellen, M. D. Robbins, B. S. Bushman, E. L. Patterson, et al. 2023. Homoeologous evolution of the allotetraploid genome of Poa annua L. BMC Genomics 24. https://doi.org/10.1186/s12864-023-09456-5

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 .

Gharde, Y., R. P. Dubey, P. K. Singh, and J. S. Mishra. 2023. Littleseed canarygrass (Phalaris minor Retz.) a major weed of rice-wheat system in India is predicted to experience range contraction under future climate. International Journal of Pest Management: 1–12. https://doi.org/10.1080/09670874.2023.2199258

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.

Huang, T., J. Chen, K. E. Hummer, L. A. Alice, W. Wang, Y. He, S. Yu, et al. 2023. Phylogeny of Rubus (Rosaceae): Integrating molecular and morphological evidence into an infrageneric revision. TAXON. https://doi.org/10.1002/tax.12885

Rubus (Rosaceae), one of the most complicated angiosperm genera, contains about 863 species, and is notorious for its taxonomic difficulty. The most recent (1910–1914) global taxonomic treatment of the genus was conducted by Focke, who defined 12 subgenera. Phylogenetic results over the past 25 years suggest that Focke's subdivisions of Rubus are not monophyletic, and large‐scale taxonomic revisions are necessary. Our objective was to provide a comprehensive phylogenetic analysis of the genus based on an integrative evidence approach. Morphological characters, obtained from our own investigation of living plants and examination of herbarium specimens are combined with chloroplast genomic data. Our dataset comprised 196 accessions representing 145 Rubus species (including cultivars and hybrids) and all of Focke's subgenera, including 60 endemic Chinese species. Maximum likelihood analyses inferred phylogenetic relationships. Our analyses concur with previous molecular studies, but with modifications. Our data strongly support the reclassification of several subgenera within Rubus. Our molecular analyses agree with others that only R. subg. Anoplobatus forms a monophyletic group. Other subgenera are para‐ or polyphyletic. We suggest a revised subgeneric framework to accommodate monophyletic groups. Character evolution is reconstructed, and diagnostic morphological characters for different clades are identified and discussed. Based on morphological and molecular evidence, we propose a new classification system with 10 subgenera: R. subg. Anoplobatus, R. subg. Batothamnus, R. subg. Chamaerubus, R. subg. Cylactis, R. subg. Dalibarda, R. subg. Idaeobatus, R. subg. Lineati, R. subg. Malachobatus, R. subg. Melanobatus, and R. subg. Rubus. The revised infrageneric nomenclature inferred from our analyses is provided along with synonymy and type citations. Our new taxonomic backbone is the first systematic and complete global revision of Rubus since Focke's treatment. It offers new insights into deep phylogenetic relationships of Rubus and has important theoretical and practical significance for the development and utilization of these important agronomic crops.

Jacquemyn, H., T. Pankhurst, P. S. Jones, R. Brys, and M. J. Hutchings. 2023. Biological Flora of Britain and Ireland: Liparis loeselii. Journal of Ecology. https://doi.org/10.1111/1365-2745.14086

This account presents information on all aspects of the biology of Liparis loeselii (L.) Rich. (Fen Orchid) that are relevant to understanding its ecological characteristics and behaviour. The main topics are presented within the standard framework of the Biological Flora of Britain and Ireland: distribution, habitat, communities, responses to biotic factors, responses to environment, structure and physiology, phenology, floral and seed characters, herbivores and disease, history and conservation.Liparis loeselii is a small terrestrial orchid that has a circumboreal distribution and is widespread in Europe and North America. Despite its wide distribution, the species is locally rare and has declined considerably in most of its range. In Britain, the species has a disjunct distribution and is now known to occur consistently at only six sites in eastern England and three in south Wales. It is absent from Ireland. Its most characteristic habitats in Britain are inland fens and coastal dune slacks, but outside Britain it can also be found in wet meadows, marshes, forested seep springs, at lake borders or on mats of floating peat.Populations of Liparis loeselii in dune slacks tend to be short‐lived, and can rapidly increase in size or decrease and disappear as environmental conditions change. The species does not tolerate high nutrient concentrations or low pH. It is susceptible to drought, which reduces seed germination, seedling recruitment and adult survival. Heavy predation by rabbits and rodents has been observed under drought conditions.Liparis loeselii reproduces both by sexual reproduction, and by vegetative propagation through the production of pseudobulbs. Although flowers are accessible to insects, entomophilous pollination is unusual, and most sexual reproduction is the result of selfing. Fruits ripen late in the growing season (mid‐October) and the dust‐like seeds are dispersed during winter by wind and water. Germination occurs during the following growing season and is supported by a wide variety of mycorrhizal fungi.Since the late 19th century Liparis loeselii has declined considerably in Britain and elsewhere in Europe, primarily due to habitat destruction and loss, natural succession, and habitat desiccation due to drainage. As a result, the species has been listed as endangered in the Bern Convention and the European Habitat Directive (92/43/EEC), and is the focus of intensive conservation efforts in many countries. Restoration of habitat by mowing, extensive grazing, peat removal, and the creation of new habitat by dune slack formation in dune systems and peat removal in fens may prolong population persistence and promote establishment of new populations.

Reichgelt, T., A. Baumgartner, R. Feng, and D. A. Willard. 2023. Poleward amplification, seasonal rainfall and forest heterogeneity in the Miocene of the eastern USA. Global and Planetary Change 222: 104073. https://doi.org/10.1016/j.gloplacha.2023.104073

Paleoclimate reconstructions can provide a window into the environmental conditions in Earth history when atmospheric carbon dioxide concentrations were higher than today. In the eastern USA, paleoclimate reconstructions are sparse, because terrestrial sedimentary deposits are rare. Despite this, the eastern USA has the largest population and population density in North America, and understanding the effects of current and future climate change is of vital importance. Here, we provide terrestrial paleoclimate reconstructions of the eastern USA from Miocene fossil floras. Additionally, we compare proxy paleoclimate reconstructions from the warmest period in the Miocene, the Miocene Climatic Optimum (MCO), to those of an MCO Earth System Model. Reconstructed Miocene temperatures and precipitation north of 35°N are higher than modern. In contrast, south of 35°N, temperatures and precipitation are similar to today, suggesting a poleward amplification effect in eastern North America. Reconstructed Miocene rainfall seasonality was predominantly higher than modern, regardless of latitude, indicating greater variability in intra-annual moisture transport. Reconstructed climates are almost uniformly in the temperate seasonal forest biome, but heterogeneity of specific forest types is evident. Reconstructed Miocene terrestrial temperatures from the eastern USA are lower than modeled temperatures and coeval Atlantic sea surface temperatures. However, reconstructed rainfall is consistent with modeled rainfall. Our results show that during the Miocene, climate was most different from modern in the northeastern states, and may suggest a drastic reduction in the meridional temperature gradient along the North American east coast compared to today.

Wilson Brown, M. K., and E. B. Josephs. 2023. Evaluating niche changes during invasion with seasonal models in Capsella bursa‐pastoris. American Journal of Botany. https://doi.org/10.1002/ajb2.16140

Premise Researchers often use ecological niche models to predict where species might establish and persist under future or novel climate conditions. However, these predictive methods assume species have stable niches across time and space. Furthermore, ignoring the time of occurrence data can obscure important information about species reproduction and ultimately fitness. Here, we assess compare ecological niche models generated from full-year averages to seasonal models Methods In this study, we generate full-year and monthly ecological niche models for Capsella bursa-pastoris in Europe and North America to see if we can detect changes in the seasonal niche of the species after long-distance dispersal. Key Results We find full-year ecological niche models have low transferability across continents and there are continental differences in the climate conditions that influence the distribution of C. bursa-pastoris. Monthly models have greater predictive accuracy than full-year models in cooler seasons, but no monthly models are able to predict North American summer occurrences very well. Conclusions The relative predictive ability of European monthly models compared to North American monthly models suggests a change in the seasonal timing between the native range to the non-native range. These results highlight the utility of ecological niche models at finer temporal scales in predicting species distributions and unmasking subtle patterns of evolution.