Entire Species Research Articles

The Promise of Environmental RNA Research Beyond mRNA.

Environmental RNA (eRNA) studies have primarily focused on species detection and community composition through metabarcoding or metatranscriptomics, and on gene expression through messenger RNA (mRNA) abundance analysis. While valuable, this focus overlooks the broader functional roles of other RNA types in cellular metabolism. Beyond mRNA, noncoding RNAs as well as structural RNAs play critical roles in gene regulation during stress responses, development and adaptation. Additionally, RNA processes like RNA methylation or alternative splicing also respond to similar environmental or developmental signals. When applied to eRNA research, these additional RNA types and RNA processes hold significant potential as powerful, noninvasive tools for monitoring the physiological state of entire species communities. In this roadmap, we present underexplored RNA types and processes relevant for eRNA research, outlining their functions and the challenges of integrating them into the field. Expanding eRNA research to include more diverse aspects of RNA biology will require improved experimental techniques for sensitive and reliable detection and quantification of specific RNAs in eRNA samples, along with enhanced tools for taxonomic and functional annotation and the expansion of genetic reference databases. Where species-level resolution is not possible, functional inferences could be drawn at higher taxonomic levels. Expanding the scope of eRNA studies to encompass more diverse RNA types and RNA processes will provide additional insights into species communities' state, their adaptation potential and responses to stressors in a noninvasive way.

Diversification, loss, and virulence gains of the major effector AvrStb6 during continental spread of the wheat pathogen Zymoseptoria tritici.

Interactions between plant pathogens and their hosts are highly dynamic and mainly driven by pathogen effectors and plant receptors. Host-pathogen co-evolution can cause rapid diversification or loss of pathogen genes encoding host-exposed proteins. The molecular mechanisms that underpin such sequence dynamics remains poorly investigated at the scale of entire pathogen species. Here, we focus on AvrStb6, a major effector of the global wheat pathogen Zymoseptoria tritici, evolving in response to the cognate receptor Stb6, a resistance widely deployed in wheat. We comprehensively captured effector gene evolution by analyzing a global thousand-genome panel using reference-free sequence analyses. We found that AvrStb6 has diversified into 59 protein isoforms with a strong association to the pathogen spreading to new continents. Across Europe, we found the strongest differentiation of the effector consistent with high rates of Stb6 deployment. The AvrStb6 locus showed also a remarkable diversification in transposable element content with specific expansion patterns across the globe. We detected AvrStb6 gene losses and evidence for transposable element-mediated disruptions. We used virulence datasets of genome-wide association mapping studies to predict virulence changes across the global panel. Genomic predictions suggested marked increases in virulence on Stb6 cultivars concomitant with the spread of the pathogen to Europe and the subsequent spread to further continents. Finally, we genotyped French bread wheat cultivars for Stb6 and monitored resistant cultivar deployment concomitant with AvrStb6 evolution. Taken together, our data provides a comprehensive view of how a rapidly diversifying effector locus can undergo large-scale sequence changes concomitant with gains in virulence on resistant cultivars. The analyses highlight also the need for large-scale pathogen sequencing panels to assess the durability of resistance genes and improve the sustainability of deployment strategies.

In vitro assays for clinical isolates of sequence type 131 Escherichia coli do not recapitulate in vivo infectivity using a murine model of urinary tract infection.

Urinary tract infections (UTIs) affect 150 million people annually, and E. coli ST131, a pandemic clone, has become responsible for a significant portion of those UTIs. How ST131 E. coli has become such a successful strain remains to be elucidated. When evaluating bacterial pathogenicity, it is customary to use in vitro assays to predict isolate virulence and fitness due to lower cost and ease of experimentation compared with in vivo models. It is common to use model organisms like pathogenic E. coli CFT073 or a non-pathogenic K12 lab strain as representatives for the entire species. However, our research has shown that model organisms differ from ST131 E. coli, and in vitro assays are poor predictors of ST131 isolate infectivity in a murine model of UTI. As such, research into the mechanisms of fitness/pathogenesis for ST131 infectivity needs to focus on these organisms rather than other types of UPEC.

Evaluation of Sampling Precision for Native and Nonnative Fish in the Gila River Basin, New Mexico

Biologists commonly use standard sampling protocols to ensure that data are comparable spatiotemporally. Data also need to be precise to allow for statistically meaningful comparisons. However, the effort needed to precisely sample desert fishes is unclear. We used a resampling approach to evaluate the effort requirements needed to precisely sample fishes among six wadeable rivers in the Gila River basin, New Mexico. We evaluated the number of samples that are necessary to obtain relative density estimates that had 25% relative standard error 80% of the time. We also estimated the effort needed to precisely characterize species richness. Our results indicate that precisely sampling fish in the Gila River basin is difficult. Sonora Sucker Catostomus insignis, Desert Sucker C. clarkii, Longfin Dace Agosia chrysogaster, and Speckled Dace Rhinicthyes osculus were generally the only species that could be precisely sampled. Characterizing the native species assemblage in the Gila River basin required between two and seven reaches, whereas the entire species assemblage could only be characterized in 50% of the study systems. The challenge of precisely sampling fish in the Gila River basin suggests that alternative sampling methods may be required to characterize changes in density or species distribution in desert Southwest systems.

Concise Overview of Methodologies Employed in the Study of Bacterial DNA Replication.

DNA replication is a fundamental process in the cell on which the functioning of the entire cell as well as the maintenance of the entire species depends. This process is synchronized with all other processes within the cell as well as with external, environmental factors. This complex network of interconnections presents significant challenges in the field of DNA replication research, both in terms of identifying an appropriate approach to a question posed and in terms of methodology. This article aims to provide a roadmap to assist in navigating (to help overcome) these challenges and in selecting an appropriate research methodology. It should help to establish a research pathway, starting with arranging the host genetic background for analysis at different cellular levels, which can be achieved using complex or simple single-purpose techniques.

Introduction to deep learning methods for multi‐species predictions

Abstract Predicting species distributions and entire communities is crucial for ecologists, to enhance our understanding of the drivers behind species distributions and community assembly and to provide quantitative data for conservation efforts. Popular species distribution models use statistical and machine learning methods but face limitations with multi‐species predictions at the community level, hindered by scalability and data imbalance sensitivity. This paper explores the potential of deep learning methods to overcome these challenges and provide more accurate multi‐species predictions. Specifically, we introduced four distinct deep learning models that use site × species community data but differ in their internal structure or on the input environmental data structure: (1) a multi‐layer perceptron (MLP) model for tabular data (e.g. in‐situ/raster climate or soil data), (2) a convolutional neural network (CNN) and (3) a vision transformer (ViT) models tailored for image data (e.g. aerial ortho‐photographs, satellite imagery), and a multimodal model that integrates both tabular and image data. We also show how adapted loss functions can address imbalance issues. We applied these deep learning models to a plant community dataset comprising 130,582 vegetation surveys encompassing 2522 species located in the French Alps. The tabular environmental data consisted of climate, terrain and soil information, while the images were derived from aerial photographs. All models achieved approximately 70% true skill statistics on hold‐out data, demonstrating high predictive capacity for community data, the multimodal model being the best performing one. Additionally, we showcased how interpretability tools can illuminate community structure as seen by deep learning models. Deep learning models offer a broad array of features for predicting entire species communities. They handle imbalance issues and accommodate various data types, from tabular datasets to images, while also being equipped with insightful interpretation tools. The versatility extends to tabular datasets and images, with no clear superiority between the two. The last hidden layers can provide valuable features for modelling other species, and the trained models can be used to support transfer learning to related tasks. The field of ecology now possesses an additional, potent tool in its arsenal that can foster basic and fundamental research.

Identification of SNPs Associated with Drought Resistance in Hybrid Populations of Picea abies (L.) H. Karst.-P. obovata (Ledeb.).

The spruces of the Picea abies-P. obovata complex have a total range that is the most extensive in the world flora of woody conifers. Hybridization between the nominative species has led to the formation of a wide introgression zone, which probably increases the adaptive potential of the entire species complex. This study aimed to search the genes associated with drought resistance, develop primers for the informative loci of these genes, identify and analyze SNPs, and establish the parameters of nucleotide diversity in the studied populations. The objects of this study were eight natural populations of the spruce complex in the Urals. Nucleotide sequences related to drought resistance spruce genes with pronounced single-nucleotide substitutions were selected, based on which 16 pairs of primers to their loci were developed and tested. Based on the developed primers, six pairs of primers were chosen to identify SNPs and assess the nucleotide diversity of the studied populations. All selected loci were highly polymorphic (6 to 27 SNPs per locus). It was found that the Pic01 locus is the most variable (Hd = 0.947; π = 0.011) and selectively neutral, and the Pic06 locus is the most conservative (Hd = 0.516; π = 0.002) and has the most significant adaptive value. The nucleotide diversity data for the studied populations reveal similar values among the populations and are consistent with the literature data. The discovered SNPs can be used to identify adaptive genetic changes in spruce populations, which is essential for predicting the effects of climate change.

Artificial Canon

Widespread concern over threats that pose an existential risk to the entire human species has provoked increasing attention and commitment to religious views of digital technology. These apocalyptic expectations of a glorious new digital world draw on American Christianity and play a visible role in tech culture and public life. The reshaping of traditional religions into new, but parallel, technological religions is characterized by a triple transformation of humanity into machines, machines into gods, and the universe into a cosmic and cosmically meaningful computer.

Physiological and morphological traits affect contemporary range expansion and implications for species distribution modelling in an amphibian species.

Species range shifts due to climate alterations have been increasingly well-documented. Although amphibians are one of the most sensitive groups of animals to environmental perturbations due to climate change, almost no studies have offered evidence of poleward distribution shifts in this taxon in response to climate warming. Range shifts would be facilitated by variation in traits associated with the ability of species to persist and/or shift their range in the face of climate change, but the extent and consequences of intraspecific variation in these traits is unclear. We studied the role of intraspecific variation in the ongoing range shift of green treefrogs (Hyla cinerea) in response to climate change. We explored factors that are often associated with range shifts to test the hypothesis that there are differences in these traits between recently range-expanded and nearby historical populations. We then tested the consequences of intraspecific variation for modelling climate-induced range shifts by comparing species distribution models (SDMs) that used as input either data from the entire species range or separate inputs from 'subpopulations' corresponding to the historical range or the recently expanded range. We expected that building a separate SDM for each population would more accurately characterize the species range if historical and expanded populations differed in traits related to their response to climate. We found that critical thermal minimum decreased and thermal breadth increased with latitude, but the effect of latitude was significantly stronger for expanded populations compared to historical populations. Additionally, we found that individuals from expanded populations had longer leg lengths when compared to their historical counterparts. Finally, we found higher model accuracy for one of the population-level SDMs than the species-level SDM. Our results suggest that thermal tolerance and dispersal morphologies are associated with amphibian distributional shifts as these characteristics appear to facilitate rapid range expansion of a native anuran. Additionally, our modelling results emphasize that SDM accuracy could be improved by dividing a species range to consider potential differences in traits associated with climate responses. Future research should identify the mechanisms underlying intraspecific variation along climate gradients to continue improving SDM prediction of range shifts under climate change.

Cross-continental comparison of plant reproductive phenology shows high intraspecific variation in temperature sensitivity.

The success of plant species under climate change will be determined, in part, by their phenological responses to temperature. Despite the growing need to forecast such outcomes across entire species ranges, it remains unclear how phenological sensitivity to temperature might vary across individuals of the same species. In this study, we harnessed community science data to document intraspecific patterns in phenological temperature sensitivity across the multicontinental range of six herbaceous plant species. Using linear models, we correlated georeferenced temperature data with 23 220 plant phenological records from iNaturalist to generate spatially explicit estimates of phenological temperature sensitivity across the shared range of species. We additionally evaluated the geographic association between local historic climate conditions (i.e. mean annual temperature [MAT] and interannual variability in temperature) and the temperature sensitivity of plants. We found that plant temperature sensitivity varied substantially at both the interspecific and intraspecific levels, demonstrating that phenological responses to climate change have the potential to vary both within and among species. Additionally, we provide evidence for a strong geographic association between plant temperature sensitivity and local historic climate conditions. Plants were more sensitive to temperature in hotter climates (i.e. regions with high MAT), but only in regions with high interannual temperature variability. In regions with low interannual temperature variability, plants displayed universally weak sensitivity to temperature, regardless of baseline annual temperature. This evidence suggests that pheno-climatic forecasts may be improved by accounting for intraspecific variation in phenological temperature sensitivity. Broad climatic factors such as MAT and interannual temperature variability likely serve as useful predictors for estimating temperature sensitivity across species' ranges.

Behavioral laterality in Greater Flamingo (Phoenicopterus roseus)

Abstract From a behavioral adaptation perspective, lateralization in gregarious species likely evolved to maintain cohesiveness among individuals, particularly in behaviors related to social life that require higher levels of cognitive capabilities. Thus, we hypothesized that motor coordination (lateralization) would be observed at the population level rather than at the individual level. To test this hypothesis, we studied population-level laterality in a wild population of Greater Flamingos (Phoenicopterus roseus) during the winter in Eilat, Israel. In November and December 2019, we recorded 176 behaviors in 220 flamingos, observing four behaviors: ‘At rest,’ ‘Vigilant,’ ‘Scratching,’ and ‘Preening’. The laterality indices for ‘At rest’ and ‘Vigilant’ were similar to those of ambidextrous simulated populations, indicating that these behaviors were not lateralized. However, ‘Preening’ and ‘Scratching’ were significantly left-lateralized. We conclude that at the population level, the symmetry of these behaviors results from flock pressure to coordinate population-level behaviors. Furthermore, the mechanism of lateralization is characteristic not only of the local population but of the entire species sensu stricto.

The Range‐Wide Genetic Structure of a High‐Elevation Conifer Species, Subalpine Larch

ABSTRACTAimSubalpine larch is a long‐lived conifer with a restricted distribution at treeline in the mountains of western North America. Climate change is reducing the availability of this habitat and subalpine larch is unlikely to adapt to its changing environment due to its long generation time, relatively low levels of standing genetic variation and the high degree of habitat fragmentation across the species' range. This study seeks to elucidate the genetic structure of subalpine larch to inform future conservation and management efforts.LocationWestern North America.TaxonSubalpine larch (Larix lyallii Parl.).MethodsTissue was collected from high‐elevation populations across the entire species range. Restriction site associated DNA sequencing was used to generate single nucleotide polymorphism (SNP) data. Population genetic analyses identified genetic differentiation.ResultsClustering analyses performed using 751 neutral SNPs identified three genetically differentiated regions: the Cascade Range, the southern Rocky Mountains and the northern Rocky Mountains. AMOVA confirmed significant genetic differentiation among regions. A discriminant analysis of principal components and a dendrogram of Provesti's genetic distance both supported the hypothesis that genetically distinct lineages arose after dispersal from a single Pleistocene refugium. Significant isolation by distance (IBD) supported the key role of dispersal in shaping modern patterns of genetic variation in subalpine larch.Main ConclusionsPost‐Pleistocene dispersal resulted in genetic differentiation among groups of subalpine larch in the Cascade Range, the southern Rocky Mountains and the northern Rocky Mountains. These three regions should be prioritised for future management.

A Multi‐Modelling Approach for Informing the Conservation of a Cold‐Adapted Terrestrial Amphibian in the Face of Climate Change

ABSTRACTAimWe aimed to assess potential climate change impacts on the distribution of a cold‐adapted terrestrial amphibian that shows strong intraspecific differentiation.LocationAlps and Dinarides.TaxonAlpine salamander (Salamandra atra).MethodsWe built SDMs for each of two major intraspecific lineages (S. a. atra, which is found throughout the Northern Alps, and S. a. prenjensis, which appears sparsely along the Dinarides) and for the entire species, using occurrence points from a carefully curated database, climate data with 1 km2 spatial resolution and eight modelling techniques. We projected climatically suitable areas to 2070 under two climate scenarios (RCP2.6 and RCP8.5), using 24 general circulation models.ResultsFor S. a. atra, under RCP2.6 scenario, we detected a 3% increase in the extent of climatically suitable areas in the Alps (although with low model agreement), yet a 6% decrease under the RCP8.5 scenario. For S. a. prenjensis, we detected a decrease in the extent of climatically suitable areas in the Dinarides between 7% and 45% (RCP2.6 and RCP8.5, respectively). The SDM predictions for the entire species were most in line with those of the S. a. atra model. Although climate variables were not equally strong in predicting the climatic suitability for both lineages, the minimum temperature of the coldest month revealed an important predictor for the entire species, with clear decreases in suitability towards higher temperature.Main ConclusionsAll models reveal a considerable decrease in climate suitability throughout most of the range of S. atra, which is particularly visible in the Dinarides. We highlight the importance of considering intraspecific variation when modelling climate change impacts on geographically differentiated species whose populations vary in their climatic niche. We provide our study results (occurrence data and maps) via a web application that can be useful for guiding conservation efforts.

Viviparity is associated with larger female size and higher sexual size dimorphism in a reproductively bimodal lizard.

Squamate reptiles are central for studying phenotypic correlates of evolutionary transitions from oviparity to viviparity because these transitions are numerous, with many of them being recent. Several models of life-history theory predict that viviparity is associated with increased female size, and thus more female-biased sexual size dimorphism (SSD). Yet, the corresponding empirical evidence is overall weak and inconsistent. The lizard Zootoca vivipara, which occupies a major part of Northern Eurasia and includes four viviparous and two non-sister oviparous lineages, represents an excellent model for testing these predictions. We analysed how sex-specific body size and SSD is associated with parity mode, using body length data for nearly 14,000 adult individuals from 97 geographically distinct populations, which cover almost the entire species' range and represent all six lineages. Our analyses controlled for lineage identity, climatic seasonality (the strongest predictor of geographic body size variation in previous studies of this species) and several aspects of data heterogeneity. Parity mode, lineage and seasonality are significantly associated with female size and SSD; the first two predictors accounted for 14%-26% of the total variation each, while seasonality explained 5%-7%. Viviparous populations exhibited a larger female size than oviparous populations, with no concomitant differences in male size. The variation of male size was overall low and poorly explained by our predictors. Albeit fully expected from theory, the strong female bias of the body size differences between oviparous and viviparous populations found in Z. vivipara is not evident from available data on three other lizard systems of closely related lineages differing in parity mode. We confront this pattern with the data on female reproductive traits in the considered systems and the frequencies of evolutionary changes of parity mode in the corresponding lizard families and speculate why the life-history correlates of live-bearing in Z. vivipara are distinct. Comparing conspecific populations, our study provides the most direct evidence for the predicted effect of parity mode on adult body size but also demonstrates that the revealed pattern may not be general. This might explain why across squamates, viviparity is only weakly associated with larger size.

Genomic implications of the repeated shift to self-fertilization across a species' geographic distribution.

The ability to self-fertilize often varies among closely related hermaphroditic plant species, though, variation can also exist within species. In the North American Arabidopsis lyrata, the shift from self-incompatibility (SI) to selfing established in multiple regions independently, mostly since recent postglacial range expansion. This has made the species an ideal model for the investigation of the genomic basis of the breakdown of SI and its population genetic consequences. By comparing nearby selfing and outcrossing populations across the entire species' geographic distribution, we investigated variation at the self-incompatibility (S-)locus and across the genome. Furthermore, a diallel crossing experiment on one mixed-mating population was performed to gain insight into the inheritance of mating system variation. We confirmed that the breakdown of SI had evolved in several S-locus backgrounds. The diallel suggested the involvement of biparental contributions with dominance relations. Though, the population-level genome-wide association study did not single out clear-cut candidate genes but several regions with one near the S-locus. On the implication side, selfing as compared to outcrossing populations had less than half of the genomic diversity, while the number and length of runs of homozygosity (ROHs) scaled with the degree of inbreeding. Selfing populations with a history of long expansion had the longest ROHs. The results highlight that mating system shift to selfing, its genetic underpinning and the likely negative genomic consequences for evolutionary potential can be strongly interlinked with past range dynamics.

On the Trail of Morphological Traits: Morphometry Helps to Clarify Morphological Variation in Section Viperella (Sisyrinchium).

Sisyrinchium, a large genus of the Iridaceae family, is divided into ten sections and defined by genetic, morphological and phylogenetic traits. The section Viperella, though monophyletic, encounters taxonomic hurdles, particularly within the Sisyrinchium palmifolium L. and Sisyrinchium vaginatum Spreng complexes, resulting in numerous misidentifications. The taxonomic confusion in the group may stem from various factors, emphasizing extensive morphological variations, leading to overlapping characteristics. We used morphometric approaches to better characterize the species belonging to two complexes, assess their variation and identify diagnostic traits for taxonomy enhancement. We assessed 16 quantitative traits for the S. palmifolium complex and 15 for the S. vaginatum complex, totaling 652 specimens recorded across 15 herbaria covering the entire species' distribution area. In the S. vaginatum complex, 66.5% of the variations were accounted for in the first two axes, while in the S. palmifolium complex, the first two axes explained 55.3%. Our findings revealed that both complexes exhibited many morphological variations, leading to a characteristic overlap. These characteristics may have arisen due to recent diversifications of the group and niche overlaps. Additionally, we identified some morphological characteristics that are useful for distinguishing species. Finally, we compiled a section gathering all useful characteristics for species delimitation within the group, aiming to facilitate non-experts in deciphering this species complex.

The genetic consequences of population marginality: A case study in maritime pine

AbstractAimMarginal tree populations, either those located at the edges of the species' range or in suboptimal environments, are often a valuable genetic resource for biological conservation. However, there is a lack of knowledge about the genetic consequences of population marginality, estimated across entire species' ranges. Our study addresses this gap by providing information about several genetic indicators and their variability in marginal and core populations identified using quantitative marginality indices.LocationSouthwestern Europe and North Africa.MethodsUsing 10,185 SNPs across 82 populations of maritime pine (Pinus pinaster Ait.), a widespread conifer characterised by a fragmented range, we modelled the relationship of seven genetic indicators potentially related to population evolutionary resilience, namely genetic diversity (based on both all SNPs and outlier SNPs), inbreeding, genetic differentiation, recessive genetic load and genomic offset, with population geographical, demo‐historical and ecological marginality (as estimated by nine quantitative indices). Models were constructed for both regional (introducing gene pool as a random factor) and range‐wide spatial scales.ResultsWe showed a trend towards decreasing overall genetic diversity and increasing differentiation with geographic marginality, supporting the centre‐periphery hypothesis (CPH). However, we found no correlation between population inbreeding and marginality, while geographically marginal populations had a lower recessive genetic load (only models without the gene pool effect). Ecologically marginal populations had a higher genomic offset, suggesting higher maladaptation to future climate, albeit some of these populations also had high genetic diversity for climate outliers.Main ConclusionsOverall genetic diversity (but not outlier‐based estimates) and differentiation patterns support the CPH. Ecologically marginal populations and those at the southern edge could be more vulnerable to climate change due to higher climate maladaptation, as predicted by genomic offsets, and/or lower potentially adaptive genetic diversity. This risk is exacerbated by typically small effective population sizes and increasing human impact in marginal populations.

Chemical Orderings in CuCo Nanoparticles: Topological Modeling Using DFT Calculations.

The orderings of atoms in bimetallic 1.6-2.1 nm-large CuCo nanoparticles, important as catalytic and magnetic materials, were studied using a combination of DFT calculations with a topological approach. The structure and magnetism of Cu50Co151, Cu101Co100, Cu151Co50, and Cu303Co102 nanoparticles; their resistance to disintegrating into separate Cu and Co species; as well as the exposed surface sites, were quantified and analyzed, showing a clear preference for Cu atoms to occupy surface positions while the Co atoms tended to form a compact cluster in the interior of the nanoparticles. The surface segregation of Co atoms that are encapsulated by less-active Cu atoms, induced by the adsorption of CO molecules, was already enabled at a low coverage of adsorbed CO, providing the energy required to displace the entire compact Co species inside the Cu matrices due to a notable adsorption preference of CO for the Co sites over the Cu ones. The calculated adsorption energies and vibrational frequencies of adsorbed CO should be helpful indicators for experimentally monitoring the nature of the surface sites of CuCo nanoparticles, especially in the case of active Co surface sites emerging in the presence of CO.

Range-Wide Assessment of Recent Longleaf Pine (Pinus palustris Mill.) Area and Regeneration Trends

Longleaf pine (Pinus palustris Mill.) is a conifer historically associated with an open forest ecosystem that extended across much of the coastal plain of the Southeastern United States. It now exists mainly in isolated fragments following the conversion of forests and the long-term disruption of the low-intensity fire regime upon which the species depends. Recent decades have seen efforts to restore longleaf pine forests by government and private landowners. This was reflected in analyses of national forest inventory data during two time periods, ca. 2009–2015 and 2016–2021, that showed increases in the estimated number of longleaf pine trees, the area of the longleaf pine forest type, and the number and area of planted longleaf pine, along with growth in mean plot-level longleaf pine carbon and importance value. At the same time, we found a decrease in the overall forest area containing longleaf pine, manifested across a variety of other forest types. These results point to a dynamic through which forests dominated by longleaf pine are becoming more widespread via restoration, while forests in which the species is a less important component are transitioning to other forest types or land uses. We also detected a decrease over time in the estimated number of longleaf seedlings across most states and forest types and a decline in naturally regenerated longleaf pine. To further assess regeneration trends in longleaf pine, we calculated the estimated proportion of small trees (seedlings and saplings) for the entire species and for seed zone sub-populations. We found a species-wide decrease in the proportion of small trees, from 82.1 percent to 75.1 percent. This reduction was most pronounced along the edges of the species distribution and could indicate less sustainable levels of regeneration in some areas. These results underscore the challenges of facilitating natural regeneration in this important species.

Tree species explain only half of explained spatial variability in plant water sensitivity.

Spatiotemporal patterns of plant water uptake, loss, and storage exert a first-order control on photosynthesis and evapotranspiration. Many studies of plant responses to water stress have focused on differences between species because of their different stomatal closure, xylem conductance, and root traits. However, several other ecohydrological factors are also relevant, including soil hydraulics, topographically driven redistribution of water, plant adaptation to local climatic variations, and changes in vegetation density. Here, we seek to understand the relative importance of the dominant species for regional-scale variations in woody plant responses to water stress. We map plant water sensitivity (PWS) based on the response of remotely sensed live fuel moisture content to variations in hydrometeorology using an auto-regressive model. Live fuel moisture content dynamics are informative of PWS because they directly reflect vegetation water content and therefore patterns of plant water uptake and evapotranspiration. The PWS is studied using 21,455 wooded locations containing U.S. Forest Service Forest Inventory and Analysis plots across the western United States, where species cover is known and where a single species is locally dominant. Using a species-specific mean PWS value explains 23% of observed PWS variability. By contrast, a random forest driven by mean vegetation density, mean climate, soil properties, and topographic descriptors explains 43% of observed PWS variability. Thus, the dominant species explains only 53% (23% compared to 43%) of explainable variations in PWS. Mean climate and mean NDVI also exert significant influence on PWS. Our results suggest that studies of differences between species should explicitly consider the environments (climate, soil, topography) in which observations for each species are made, and whether those environments are representative of the entire species range.