Graham C. D. Griffiths

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.

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.

Background: The genus Pinguicula harbors 110 species, of which 53 are distributed in Mexico. The formation of the Mexican mountains has favored the Pinguicula diversification. Pinguicula specimens collected in the State of México, along the Trans-Mexican Volcanic Belt (TMVB) do not correspond with any known species. Questions: Do the collected specimens belong to a new species? What is its conservation status? How many Pinguicula species are there along the TMVB and how do they differentiate? How is the Pinguicula species richness distributed? Studied species: Pinguicula. Study site and dates: TMVB, 2005-2023. Methods: Based on herbarium specimens and recently collected material, a morphological analysis and description were made. Conservation status was assessed following IUCN Red List Categories and Criteria. Herbarium specimens and digital records of Pinguicula from the TMVB were examined to generate a list and key. We analyzed the richness distribution of Pinguicula by states, vegetation types, elevation ranges, and grid cells. Results: Pinguicula tlahuica is proposed as a new species. It is distinguished by the linear-spatulate summer leaves. The new species falls into the Endangered (EN) category. Along the TMVB, 16 species of Pinguicula are distributed. The State of México, Hidalgo and Michoacán, and the pine-oak forest were the richest. Pinguicula appeared between 759-3,427 m asl. The grid cell analyses revealed different areas with high richness. Conclusions: Along the TMVB, the Pinguicula species richness centered on the Eastern and Western sectors. Pinguicula crassifolia, P. michoacana, P. tlahuica, and P. zamudioana are endemic to the TMVB.

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.

Species occurrence-based climate niche models (CNMs) serve as valuable tools for predicting the future ranges of species’ suitable habitats, aiding the development of climate change adaptation strategies. However, these models do not address an essential aspect - productivity, which holds economic significance for timber production and ecological importance for carbon sequestration and ecosystem services. In this study, we investigated the potential to extend the CNMs to predict species productivity under various climate conditions. Lodgepole pine (Pinus contorta Dougl. ex Loud.) and Douglas-fir (Pseudotsuga menziesii Franco.) were selected as our model species due to their comprehensive range-wide occurrence data and measurement of site productivity. To achieve this, we compared and optimized the performance of four individual modeling algorithms (Random Forest (RF), Maxent, Generalized Boosted Models (GBM), and Generalized Additive Model (GAM)) in reflecting site productivity by evaluating the effect of spatial filtering, and the ratio of presence to absence (p/a ratio) observations. Additionally, we applied a binning process to capture the overarching trend of climatic effects while minimizing the impact of other factors. We observed consistency in optimal performance across both species when using the unfiltered data and a 1:1.5 p/a ratio, which could potentially be extended to other species. Among the modeling algorithms explored, we selected the ensemble model combining RF and Maxent as the final model to predict the range-wide site productivity for both species. The predicted range-wide site productivity was validated with an independent dataset for each species and yielded promising results (R2 above 0.7), affirming our model’s credibility. Our model introduced an innovative approach for predicting species productivity with high accuracy using only species occurrence data, and significantly advanced the application of CNMs. It provided crucial tools and insights for evaluating climate change's impact on productivity and holds a better potential for informed forest management and conservation decisions.

The monarch butterfly is a flagship species and pollinator whose populations have declined by 85% in the recent two decades. Their largest population overwinters in Mexico, then disperses across eastern North America during March to August. During September-December, they return south using two flyways, one that spans the central United States and another that follows the Atlantic coast. Migrating monarchs fly diurnally and roost in groups nocturnally. We sought to determine the criteria this species uses to select roost sites, and the landscape context where those sites are found. We developed species distribution models of the landscape context of Atlantic flyway roost sites via citizen scientist observations and environmental variables that affect monarchs in the adult stage prior to migration, using two algorithms (Maximum Entropy and Genetic Algorithm for Ruleset Prediction). We developed two model validation methods: a citizen scientist smartphone application and peer-informed comparisons with aerial imagery. Proximity to surface water, elevation, and vegetative cover were the most important criteria for monarch roost site selection. Our model predicted 2.6 million ha (2.9% of the study area) of suitable roosting habitat in the Atlantic flyway, with the greatest availability along the Atlantic coastal plain and Appalachian Mountain ridges. Conservation of this species is difficult, as monarchs range over both large areas and various habitat types, and most current monarch research and conservation efforts are focused on the breeding and overwintering periods. These models can serve to help prioritize surveys of roosting sites and conservation efforts during the monarchs’ fall migration.

The genus Malaxis (family Orchidaceae), comprises nearly 183 species available across the globe. The plants of this genus have long been employed in traditional medical practices because of their numerous biological properties, like the treatment of infertility, hemostasis, burning sensation, bleeding diathesis, fever, diarrhea, dysentery, febrifuge, tuberculosis, etc. Various reports highlight their phytochemical composition and biological activities. However, there is a lack of systematic review on the distribution, phytochemistry, and biological properties of this genus. Hence, this study aims to conduct a thorough and critical review of Malaxis species, covering data published from 1965 to 2022 with nearly 90 articles. Also, it examines different bioactive compounds, their chemistry, and pharmacotherapeutics as well as their traditional uses. A total of 191 unique compounds, including the oil constituents were recorded from Malaxis species. The highest active ingredients were obtained from Malaxis acuminata (103) followed by Malaxis muscifera (50) and Malaxis rheedei (33). In conclusion, this review offers an overview of the current state of knowledge on Malaxis species and highlights prospects for future research projects on them. Additionally, it recommends the promotion of domestication studies for rare medicinal orchids like Malaxis and the prompt implementation of conservation measures.

Background Impatiens sect. Impatiens is distributed across the Northern Hemisphere and has diversified considerably, particularly within the Hengduan Mountains (HDM) in southwest China. Yet, the infra-sectional phylogenetic relationships are not well resolved, largely due to limited taxon sampling and an insufficient number of molecular markers. The evolutionary history of its diversification is also poorly understood. In this study, plastome data and the most complete sampling to date were used to reconstruct a robust phylogenetic framework for this section. The phylogeny was then used to investigate its biogeographical history and diversification patterns, specifically with the aim of understanding the role played by the HDM and past climatic changes in its diversification. Results A stable phylogeny was reconstructed that strongly supported both the monophyly of the section and its division into seven major clades (Clades I-VII). Molecular dating and ancestral area reconstruction suggest that sect. Impatiens originated in the HDM and Southeast China around 11.76 Ma, after which different lineages dispersed to Northwest China, temperate Eurasia, and North America, mainly during the Pliocene and Pleistocene. An intercontinental dispersal event from East Asia to western North America may have occurred via the Bering Land Bridge or Aleutian Islands. The diversification rate was high during its early history, especially with the HDM, but gradually decreased over time both within and outside the HDM. Multiple linear regression analysis showed that the distribution pattern of species richness was strongly associated with elevation range, elevation, and mean annual temperature. Finally, ancestral niche analysis indicated that sect. Impatiens originated in a relatively cool, middle-elevation area. Conclusions We inferred the evolutionary history of sect. Impatiens based on a solid phylogenetic framework. The HDM was the primary source or pump of its diversity in the Northern Hemisphere. Orogeny and climate change may have also shaped its diversification rates, as a steady decrease in the diversification rate coincided with the uplift of the HDM and climate cooling. These findings provide insights into the distribution pattern of sect. Impatiens and other plants in the Northern Hemisphere.

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.