Stanley Jay Smith

AbstractIn 2023, field research in south-western Poland led to the noteworthy discovery of two hornworts: Notothylasorbicularis, a species previously unrecorded in this country, and the rediscovery of Anthocerosneesii for the Polish bryoflora. These findings are significant as they suggest a response to climate change, which is facilitating the range expansion of hornworts within Central Europe. Detailed descriptions of the new localities for both species are provided, highlighting the specific environmental conditions and habitats where they were found. Distribution maps for Notothylasorbicularis and Anthocerosneesii in Poland are provided, as well as SEM micrographs of spores. Additionally, a key to the identification of Polish hornwort species is also included. Furthermore, a model projecting the potential future spread of these hornworts within Poland and the broader Central European region is presented. This model considers climatic variables and habitat availability, offering insights into possible range shifts. This study contributes to the growing body of evidence that climate change is a driving factor in the redistribution of bryophytes.

The use of non-pollen palynomorphs (NPP), particularly fossil fungi and algae, as palaeobiological proxies for Late Cretaceous palaeoenvironmental and palaeoclimatic reconstructions of warm-to-hot greenhouse conditions, can enhance our understanding of climate change impacts on modern Patagonian environments. This study aimed to reconstruct the Maastrichtian palaeoenvironment and palaeoclimate in the Cañadón Asfalto Basin (CAB, Chubut Province) by testing these NPPs as proxies using the Nearest Living Relative method (NLR). Moreover, using modern ecological requirements from open-source databases, such as GBIF and processing it with an open-source, cross-platform tool like QGIS, linked with Köppen-Geiger shapefiles, provided evidence of climate-driven palaeo-distribution patterns of fungal and algal diversity at CAB. Applying modern ecological requirements and biogeographic distribution data, we reconstructed the palaeoclimate as temperate with evenly distributed precipitation and warm summers, corresponding to the Cfb climate zone in Köppen-Geiger classifications. Additionally, our methodology produced reliable results regarding Cenozoic floras’ physiognomies based on fossil fungi, revealing a transition from sparsely wooded areas with palms and prairies to complex forest ecosystems with palms, deciduous trees, and shrubland. Furthermore, testing Cretaceous algae with the NLR method, for the first time, provided comprehensive insights into past water body characteristics, including trophic state and water quality.

Non‐native annual grasses can dramatically alter fire frequency and reduce forage quality and biodiversity in the ecosystems they invade. Effective management techniques are needed to reduce these undesirable invasive species and maintain ecosystem services. Well‐timed management strategies, such as grazing, that are applied when invasive grasses are active prior to native plants can control invasive species spread and reduce their impact; however, anticipating the timing of key phenological stages that are susceptible to management over vast landscapes is difficult, as the phenology of these species can vary greatly over time and space. To address this challenge, we created range‐wide phenology forecasts for two problematic invasive annual grasses: cheatgrass (Bromus tectorum), and red brome (Bromus rubens). We tested a suite of 18 mechanistic phenology models using observations from monitoring experiments, volunteer science, herbarium records, timelapse camera imagery, and downscaled gridded climate data to identify the models that best predicted the dates of flowering and senescence of the two invasive grass species. We found that the timing of flowering and senescence of cheatgrass and red brome were best predicted by photothermal time models that had been adjusted for topography using gridded continuous heat‐insolation load index values. Phenology forecasts based on these models can help managers make decisions about when to schedule management actions such as grazing to reduce undesirable invasive grasses and promote forage production, quality, and biodiversity in grasslands; to predict the timing of greatest fire risk after annual grasses dry out; and to select remote sensing imagery to accurately map invasive grasses across topographic and latitudinal gradients. These phenology models also have the potential to be operationalized for within‐season or within‐year decision support.

Premise Vertical surfaces in urban environments represent a potential expansion of niche space for lithophytic fern species. There are, however, few records of differential success rates of fern species in urban environments.MethodsThe occurrence rates of 16 lithophytic fern species native to the northeastern USA in 14 biomes, including four urban environments differentiated by percentage of impervious surfaces, were evaluated. In addition, the natural macroclimatic ranges of these species were analyzed to test whether significant differences existed in climatic tolerance between species that occur in urban environments and species that do not.ResultsThree species appear to preferentially occur in urban environments, two species may facultatively occur in urban environments, and the remaining 11 species preferentially occur in nondeveloped rural environments. The natural range of fern species that occur in urban environments had higher summer temperatures than the range of species that do not, whereas other macroclimatic variables, notably winter temperatures and precipitation, were less important or insignificant.ConclusionsVertical surfaces in urban environments may represent novel niche space for some native lithophytic fern species in northeastern USA. However, success in this environment depends, in part, on tolerance of the urban heat island effect, especially heating of impervious surfaces in summer.

Species are often expected to shift their distributions either poleward or upslope to evade warming climates and colonise new suitable climatic niches. However, from 18‐years of fixed transect monitoring data on 88 species of butterfly in the midwestern United States, we show that butterflies are shifting their centroids in all directions, except towards regions that are warming the fastest (southeast).Butterflies shifted their centroids at a mean rate of 4.87 km year−1. The rate of centroid shift was significantly associated with local climate change velocity (temperature by precipitation interaction), but not with mean climate change velocity throughout the species' ranges.Species tended to shift their centroids at a faster rate towards regions that are warming at slower velocities but increasing in precipitation velocity.Surprisingly, species' thermal niche breadth (range of climates butterflies experience throughout their distribution) and wingspan (often used as metric for dispersal capability) were not correlated with the rate at which species shifted their ranges.We observed high phylogenetic signal in the direction species shifted their centroids. However, we found no phylogenetic signal in the rate species shifted their centroids, suggesting less conserved processes determine the rate of range shift than the direction species shift their ranges.This research shows important signatures of multidirectional range shifts (latitudinal and longitudinal) and uniquely shows that local climate change velocities are more important in driving range shifts than the mean climate change velocity throughout a species' entire range.

Fungal pathogens are responsible for 30% of emerging infectious diseases (EIDs) in plants. The risk of a pathogen emerging on a new host is strongly tied to its host breadth; however, the determinants of host range are still poorly understood. Here, we explore the factors that shape host breadth of plant pathogens within Botryosphaeriaceae, a fungal family associated with several devastating diseases in economically important crops. While most host plants are associated with just one or a few fungal species, some hosts appear to be susceptible to infection by multiple fungi. However, the variation in the number of fungal taxa recorded across hosts is not easily explained by heritable plant traits. Nevertheless, we reveal strong evolutionary conservatism in host breadth, with most fungi infecting closely related host plants, but with some notable exceptions that seem to have escaped phylogenetic constraints on host range. Recent anthropogenic movement of plants, including widespread planting of crops, has provided new opportunities for pathogen spillover. We suggest that constraints to pathogen distributions will likely be further disrupted by climate change, and we may see future emergence events in regions where hosts are present but current climate is unfavorable.

AbstractAimSpreading infectious diseases associated with introduced pathogens can have devastating effects on native biota and human livelihoods. We analyse the global distribution of 100 major alien fungal and oomycete pathogens with substantial socio‐economic and environmental impacts and examine their taxonomy, ecological characteristics, temporal accumulation trajectories, regional hot‐ and coldspots of taxon richness and taxon flows between continents.LocationGlobal.TaxonAlien/cryptogenic fungi and fungus‐like oomycetes, pathogenic to plants or animals.MethodsTo identify over/underrepresented classes and phyla, we performed Chi2 tests of independence. To describe spatial patterns, we calculated the region‐wise richness and identified hot‐ and coldspots, defined as residuals after correcting taxon richness for region area and sampling effort via a quasi‐Poisson regression. We examined the relationship with environmental and socio‐economic drivers with a multiple linear regression and evaluated a potential island effect. Regional first records were pooled over 20‐year periods, and for global flows the links between the native range to the alien regions were mapped.ResultsPeronosporomycetes (Oomycota) were overrepresented among taxa and regional taxon richness was positively correlated with area and sampling effort. While no island effect was found, likely due to host limitations, hotspots were correlated with human modification of terrestrial land, per capita gross domestic product, temperate and tropical forest biomes, and orobiomes. Regional first records have increased steeply in recent decades. While Europe and Northern America were major recipients, about half of the taxa originate from Asia.Main ConclusionsWe highlight the putative importance of anthropogenic drivers, such as land use providing a conducive environment, contact opportunities and susceptible hosts, as well as economic wealth likely increasing colonisation pressure. While most taxa were associated with socio‐economic impacts, possibly partly due to a bias in research focus, about a third show substantial impacts to both socio‐economy and the environment, underscoring the importance of maintaining a wholescale perspective across natural and managed systems.

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.

Pisolithus is a genus of gasteroid mycorrhizal symbionts associated with trees of several families of angiosperms and gymnosperms and distributed almost worldwide. Here we report a new record of Pisolithus arhizus from Tashkent, Uzbekistan, the first record of this species in Central Asia. The fruit bodies of P. arhizus were collected in several locations within the city and identified based on morphological characters. The ectomycorrhizal fungus formed symbiotic relationships with Juniperus sp. and Quercus sp. We provide its morphological description and photographs and also discuss our findings in the context of previously known records of this species.

Fossils from tropical Asia, which are far from fully investigated, are important for understanding the evolution of plant diversity and the associated surrounding environment there. In this study, we report, as the first record in Thailand, the well-preserved leaf fossils of Calophyllum Linnaeus (Calophyllaceae) from the upper Oligocene–Lower Miocene lacustrine deposits in Li Basin, northern Thailand. The fossils were identified through detailed comparison with leaves of extant and fossil species. These leaf fossils are assigned to Calophyllum based on several key leaf characteristics such as oblanceolate or oblong in shape and parallel secondary veins, nearly perpendicular to the midvein, as well as secondary veins alternate, closely placed, craspedodromous, parallel, dense, and distinct on surface, forming marginal veins. Based on detailed morphological comparison, these fossil leaves are assigned to C. suraikholaensis Awasthi and Prasad, 1990 and Calophyllum sp. The discovery of Calophyllum indicates a montane subtropical to tropical climate in northern Thailand during the Oligocene–Miocene. Together with previous fossil records, these results suggest that this genus probably originated in India during the Paleogene, and spread from India to Indochina during the Neogene, leading to its modern distribution, which currently prefers tropical climates.