California's 2023 snow deluge: Contextualizing an extreme snow year against future climate change.

The increasing prevalence of low snow conditions in a warming climate has attracted substantial attention in recent years, but a focus exclusively on low snow leaves high snow years relatively underexplored. However, these large snow years are hydrologically and economically important in regions where snow is critical for water resources. Here, we introduce the term "snow deluge" and use anomalously high snowpack in California's Sierra Nevada during the 2023 water year as a case study. Snow monitoring sites across the state had a median 41 y return interval for April 1 snow water equivalent (SWE). Similarly, a process-based snow model showed a 54 y return interval for statewide April 1 SWE (90% CI: 38 to 109 y). While snow droughts can result from either warm or dry conditions, snow deluges require both cool and wet conditions. Relative to the last century, cool-season temperature and precipitation during California's 2023 snow deluge were both moderately anomalous, while temperature was highly anomalous relative to recent climatology. Downscaled climate models in the Shared Socioeconomic Pathway-370 scenario indicate that California snow deluges-which we define as the 20 y April 1 SWE event-are projected to decline with climate change (58% decline by late century), although less so than median snow years (73% decline by late century). This pattern occurs across the western United States. Changes to snow deluge, and discrepancies between snow deluge and median snow year changes, could impact water resources and ecosystems. Understanding these changes is therefore critical to appropriate climate adaptation.

Snowmelt duration controls red algal blooms in the snow of the European Alps.

Algae populate multiple habitats, including snow and ice, where they can form red blooms. These decrease snow albedo, accelerating snowmelt and potentially feeding back on snow and glacier decline caused by climate change. Quantifying this feedback requires the understanding of bloom evolution with climate change. Little, however, is known about the drivers of red snow blooms. Here, we develop an algorithm to analyze 5 y of satellite data from the European Alps and separate bloom occurrences from similarly colored Saharan dust depositions. In a second step, we combine the occurrences of blooms with meteorological data and snow simulations to identify the drivers of blooms. Results show that the upward migration of algae from the ground and blooming requires the presence of liquid water throughout the whole snow column for at least 46 d. Our limited data suggest that moderate dust amounts provide nutrients favorable to bloom, whereas large dust amounts hasten snowmelt and reduce its duration below the threshold required for blooming. Over the period studied, blooms cover 1.3% of the area above 1,800 m elevation, advancing the snow melt-out date by 4 to 21 d in these areas. Under warmer climates, maximum snow mass will decrease whereas snowmelt duration, that controls algal blooms' occurrences, is less sensitive to global temperature increase. In this respect, the impact of bloom on snowmelt will either remain stable (RCP4.5) or decrease (RCP8.5). Algal blooms in the Alps therefore do not constitute a positive climate feedback.

Effect of skull morphology on fox snow diving.

Certain fox species plunge-dive into snow to catch prey (e.g., rodents), a hunting mechanism called mousing. Red and arctic foxes can dive into snow at speeds ranging between 2 and 4 m/s. Such mousing behavior is facilitated by a slim, narrow facial structure. Here, we investigate how foxes dive into snow efficiently by studying the role of skull morphology on impact forces it experiences. In this study, we reproduce the mousing behavior in the lab using three-dimensional (3D) printed fox skulls dropped into fresh snow to quantify the dynamic force of impact. Impact force into snow is modeled using hydrodynamic added mass during the initial impact phase. This approach is based on two key facts: the added mass effect in granular media at high Reynolds numbers and the characteristics of snow as a granular medium. Our results show that the curvature of the snout plays a critical role in determining the impact force, with an inverse relationship. A sharper skull leads to a lower average impact force, which allows foxes to dive head-first into the snow with minimal tissue damage.

Increasing wildfire impacts on snowpack in the western U.S.

Wildfire area has been increasing in most ecoregions across the western United States, including snow-dominated regions. These fires modify snow accumulation, ablation, and duration, but the sign and magnitude of these impacts can vary substantially between regions. This study compares spatiotemporal patterns of western United States wildfires between ecoregions and snow zones. Results demonstrate significant increases in wildfire area from 1984 to 2020 throughout the West, including the Sierra Nevada, Cascades, Basin and Range, and Northern to Southern Rockies. In the late snow zone, where mean annual snow-free date is in May or later, 70% of ecoregions experienced significant increases in wildfire area since 1984. The distribution of burned area shifted from earlier melt zones to later-melt snow zones in several ecoregions, including the Southern Rockies, where the area burned in the late snow zone during 2020 exceeded the total burned area over the previous 36 y combined. Snow measurements at a large Southern Rockies fire revealed that burning caused lower magnitude and earlier peak snow-water equivalent as well as an 18-24 d estimated advance in snow-free dates. Latitude, a proxy for solar radiation, is a dominant driver of snow-free date, and fire advances snow-free timing through a more-positive net shortwave radiation balance. This loss of snow can reduce both ecosystem water availability and streamflow generation in a region that relies heavily on mountain snowpack for water supply.

Elongation enhances encounter rates between phytoplankton in turbulence.

Phytoplankton come in a stunning variety of shapes but elongated morphologies dominate-typically 50% of species have aspect ratio above 5, and bloom-forming species often form chains whose aspect ratios can exceed 100. How elongation affects encounter rates between phytoplankton in turbulence has remained unknown, yet encounters control the formation of marine snow in the ocean. Here, we present simulations of encounters among elongated phytoplankton in turbulence, showing that encounter rates between neutrally buoyant elongated cells are up to 10-fold higher than for spherical cells and even higher when cells sink. Consequently, we predict that elongation can significantly speed up the formation of marine snow compared to spherical cells. This unexpectedly large effect of morphology in driving encounter rates among plankton provides a potential mechanistic explanation for the rapid clearance of many phytoplankton blooms.

Avalanche burial pathophysiology - a unique combination of hypoxia, hypercapnia and hypothermia.

For often unclear reasons, the survival times of critically buried avalanche victims vary widely from minutes to hours. Individuals can survive and sustain organ function if they can breathe under the snow and maintain sufficient delivery of oxygen and efflux of carbon dioxide. We review the physiological responses of humans to critical avalanche burial, a model which shares similarities and differences with apnoea and accidental hypothermia. Within a few minutes of burial, an avalanche victim is exposed to hypoxaemia and hypercapnia, which have important effects on the respiratory and cardiovascular systems and pose a major threat to the central nervous system. As burial time increases, an avalanche victim also develops hypothermia. Despite progressively reduced metabolism, reduced oxygen and increased carbon dioxide tensions may exacerbate the pathophysiological consequences of hypothermia. Hypercapnia seems to be the main cause of cardiovascular instability, which, in turn, is the major reason for reduced cerebral oxygenation despite reductions in cerebral metabolic activity caused by hypothermia. 'Triple H syndrome' refers to the interaction of hypoxia, hypercapnia and hypothermia in a buried avalanche victim. Future studies should investigate how the respiratory gases entrapped in the porous snow structure influence the physiological responses of buried individuals and how haemoconcentration, blood viscosity and cell deformability affect blood flow and oxygen delivery. Attention should also be devoted to identifying strategies to prolong avalanche survival by either mitigating hypoxia and hypercapnia or reducing core temperature so that neuroprotection occurs before the onset of cerebral hypoxia.

Long-Term Alpine Plant Responses to Global Change Drivers Depend on Functional Traits.

Forecasting plant responses under global change is a critical but challenging endeavour. Despite seemingly idiosyncratic responses of species to global change, greater generalisation of 'winners' and 'losers' may emerge from considering how species functional traits influence responses and how these responses scale to the community level. Here, we synthesised six long-term global change experiments combined with locally measured functional traits. We quantified the change in abundance and probability of establishment through time for 70 alpine plant species and then assessed if leaf and stature traits were predictive of species and community responses across nitrogen addition, snow addition and warming treatments. Overall, we found that plants with more resource-acquisitive trait strategies increased in abundance but each global change factor was related to different functional strategies. Nitrogen addition favoured species with lower leaf nitrogen, snow addition favoured species with cheaply constructed leaves and warming showed few consistent trends. Community-weighted mean changes in trait values in response to nitrogen addition, snow addition and warming were often different from species-specific trait effects on abundance and establishment, reflecting in part the responses and traits of dominant species. Together, these results highlight that the effects of traits can differ by scale and response of interest.

Comparative plastome analysis and taxonomic classification of snow lotus species (Saussurea, Asteraceae) in Central Asia and Southern Siberia.

Four species of Saussurea, namely S. involucrata, S. orgaadayi, S. bogedaensis, and S. dorogostaiskii, are known as the "snow lotus," which are used as traditional medicines in China (Xinjiang), Kyrgyzstan, Mongolia, and Russia (Southern Siberia). These species are threatened globally, because of illegal harvesting and climate change. Furthermore, the taxonomic classification and identification of these threatened species remain unclear owing to limited research. The misidentification of medicinal species can sometimes be harmful to health. Therefore, the phylogenetic and genomic features of these species need to be confirmed. In this study, we sequenced five complete chloroplast genomes and seven nuclear ITS regions of four snow lotus species and other Saussurea species. We further explored their genetic variety, selective pressure at the sequence level, and phylogenetic relationships using the chloroplast genome, nuclear partial DNA sequences, and morphological features. Plastome of the snow lotus species has a conserved structure and gene content similar to most Saussurea species. Two intergenic regions (ndhJ-ndhK and ndhD-psaC) show significantly high diversity among chloroplast regions. Thus, ITS and these markers are suitable for identifying snow lotus species. In addition, we characterized 43 simple sequence repeats that may be useful in future population genetic studies. Analysis of the selection signatures identified three genes (rpoA, ndhB, and ycf2) that underwent positive selection. These genes may play important roles in the adaptation of the snow lotus species to alpine environments. S. dorogostaiskii is close to S. baicalensis and exhibits slightly different adaptation from others. The taxonomic position of the snow lotus species, confirmed by morphological and molecular evidence, is as follows: (i) S. involucrata has been excluded from the Mongolian flora due to misidentification as S. orgaadayi or S. bogedaensis for a long time; (ii) S. dorogostaiskii belongs to section Pycnocephala subgenus Saussurea, whereas other the snow lotus species belong to section Amphilaena subgenus Amphilaena; and (iii) S. krasnoborovii is synonymous of S. dorogostaiskii. This study clarified the speciation and lineage diversification of the snow lotus species in Central Asia and Southern Siberia.

Extremes of snow and temperature affect patterns of genetic diversity and differentiation in the alpine butterfly Parnassius smintheus.

Weather is an important short-term, local driver of population size and dispersal, which in turn contribute to patterns of genetic diversity and differentiation within species. Climate change is leading to greater weather variability and more frequent extreme weather events. While the effects of long-term and broad-scale mean climate conditions on genetic variation are well studied, our understanding of the effects of weather variability and extreme conditions on genetic variation is less developed. We assessed the influence of temperature and snow depth on genetic diversity and differentiation of populations of the alpine butterfly, Parnassius smintheus. We examined the relationships between a suite of variables, including those representing extreme conditions, and population-level genetic diversity and differentiation across 1453 single nucleotide polymorphisms, using both linear and gravity models. We additionally examined effects of land cover variables known to influence dispersal and gene flow in this species. We found that extreme low temperature events and the lowest recorded mean snow depth were significant predictors of genetic diversity. Extreme low temperature events, mean snow depth and land cover resistance were significant predictors of genetic differentiation. These results are congruent with known effects of early winter weather on population size and habitat connectivity on dispersal in P. smintheus. Our results demonstrate the potential for changes in the frequency or magnitude of extreme weather events to alter patterns of genetic diversity and differentiation.

Climate change disrupts the seasonal coupling of plant and soil microbial nutrient cycling in an alpine ecosystem.

The seasonal coupling of plant and soil microbial nutrient demands is crucial for efficient ecosystem nutrient cycling and plant production, especially in strongly seasonal alpine ecosystems. Yet, how these seasonal nutrient cycling processes are modified by climate change and what the consequences are for nutrient loss and retention in alpine ecosystems remain unclear. Here, we explored how two pervasive climate change factors, reduced snow cover and shrub expansion, interactively modify the seasonal coupling of plant and soil microbial nitrogen (N) cycling in alpine grasslands, which are warming at double the rate of the global average. We found that the combination of reduced snow cover and shrub expansion disrupted the seasonal coupling of plant and soil N-cycling, with pronounced effects in spring (shortly after snow melt) and autumn (at the onset of plant senescence). In combination, both climate change factors decreased plant organic N-uptake by 70% and 82%, soil microbial biomass N by 19% and 38% and increased soil denitrifier abundances by 253% and 136% in spring and autumn, respectively. Shrub expansion also individually modified the seasonality of soil microbial community composition and stoichiometry towards more N-limited conditions and slower nutrient cycling in spring and autumn. In winter, snow removal markedly reduced the fungal:bacterial biomass ratio, soil N pools and shifted bacterial community composition. Taken together, our findings suggest that interactions between climate change factors can disrupt the temporal coupling of plant and soil microbial N-cycling processes in alpine grasslands. This could diminish the capacity of these globally widespread alpine ecosystems to retain N and support plant productivity under future climate change.

Drivers of contemporary and future changes in Arctic seasonal transition dates for a tundra site in coastal Greenland.

Climate change has had a significant impact on the seasonal transition dates of Arctic tundra ecosystems, causing diverse variations between distinct land surface classes. However, the combined effect of multiple controls as well as their individual effects on these dates remains unclear at various scales and across diverse land surface classes. Here we quantified spatiotemporal variations of three seasonal transition dates (start of spring, maximum normalized difference vegetation index (NDVImax ) day, end of fall) for five dominating land surface classes in the ice-free Greenland. Using a distributed snow model, structural equation modeling, and a random forest model, based on ground observations and remote sensing data, we assessed the indirect and direct effects of climate, snow, and terrain on seasonal transition dates. We then presented new projections of likely changes in seasonal transition dates under six future climate scenarios. The coupled climate, snow cover, and terrain conditions explained up to 61% of seasonal transition dates across different land surface classes. Snow ending day played a crucial role in the start of spring and timing of NDVImax . A warmer June and a decline in wind could advance the NDVImax day. Increased precipitation and temperature during July-August are the most important for delaying the end of fall. We projected that a 1-4.5°C increase in temperature and a 5%-20% increase in precipitation would lengthen the spring-to-fall period for all five land surface classes by 2050, thus the current order of spring-to-fall lengths for the five land surface classes could undergo notable changes. Tall shrubs and fens would have a longer spring-to-fall period under the warmest and wettest scenario, suggesting a competitive advantage for these vegetation communities. This study's results illustrate controls on seasonal transition dates and portend potential changes in vegetation composition in the Arctic under climate change.

Extended ozone depletion and reduced snow and ice cover-Consequences for Antarctic biota.

Stratospheric ozone, which has been depleted in recent decades by the release of anthropogenic gases, is critical for shielding the biosphere against ultraviolet-B (UV-B) radiation. Although the ozone layer is expected to recover before the end of the 21st century, a hole over Antarctica continues to appear each year. Ozone depletion usually peaks between September and October, when fortunately, most Antarctic terrestrial vegetation and soil biota is frozen, dormant and protected under snow cover. Similarly, much marine life is protected by sea ice cover. The ozone hole used to close before the onset of Antarctic summer, meaning that most biota were not exposed to severe springtime UV-B fluxes. However, in recent years, ozone depletion has persisted into December, which marks the beginning of austral summer. Early summertime ozone depletion is concerning: high incident UV-B radiation coincident with snowmelt and emergence of vegetation will mean biota is more exposed. The start of summer is also peak breeding season for many animals, thus extreme UV-B exposure (UV index up to 14) may come at a vulnerable time in their life cycle. Climate change, including changing wind patterns and strength, and particularly declining sea ice, are likely to compound UV-B exposure of Antarctic organisms, through earlier ice and snowmelt, heatwaves and droughts. Antarctic field research conducted decades ago tended to study UV impacts in isolation and more research that considers multiple climate impacts, and the true magnitude and timing of current UV increases is needed.

Long-term changes in the daytime growing season carbon dioxide exchange following increased temperature and snow cover in arctic tundra.

Increasing temperatures and winter precipitation can influence the carbon (C) exchange rates in arctic ecosystems. Feedbacks can be both positive and negative, but the net effects are unclear and expected to vary strongly across the Arctic. There is a lack of understanding of the combined effects of increased summer warming and winter precipitation on the C balance in these ecosystems. Here we assess the short-term (1-3 years) and long-term (5-8 years) effects of increased snow depth (snow fences) (on average + 70 cm) and warming (open top chambers; 1-3°C increase) and the combination in a factorial design on all key components of the daytime carbon dioxide (CO2 ) fluxes in a wide-spread heath tundra ecosystem in West Greenland. The warming treatment increased ecosystem respiration (ER) on a short- and long-term basis, while gross ecosystem photosynthesis (GEP) was only increased in the long term. Despite the difference in the timing of responses of ER and GEP to the warming treatment, the net ecosystem exchange (NEE) of CO2 was unaffected in the short term and in the long term. Although the structural equation model (SEM) indicates a direct relationship between seasonal accumulated snow depth and ER and GEP, there were no significant effects of the snow addition treatment on ER or GEP measured over the summer period. The combination of warming and snow addition turned the plots into net daytime CO2 sources during the growing season. Interestingly, despite no significant changes in air temperature during the snow-free time during the experiment, control plots as well as warming plots revealed significantly higher ER and GEP in the long term compared to the short term. This was in line with the satellite-derived time-integrated normalized difference vegetation index of the study area, suggesting that more factors than air temperature are drivers for changes in arctic tundra ecosystems.

Deep learning to extract the meteorological by-catch of wildlife cameras.

Microclimate-proximal climatic variation at scales of metres and minutes-can exacerbate or mitigate the impacts of climate change on biodiversity. However, most microclimate studies are temperature centric, and do not consider meteorological factors such as sunshine, hail and snow. Meanwhile, remote cameras have become a primary tool to monitor wild plants and animals, even at micro-scales, and deep learning tools rapidly convert images into ecological data. However, deep learning applications for wildlife imagery have focused exclusively on living subjects. Here, we identify an overlooked opportunity to extract latent, ecologically relevant meteorological information. We produce an annotated image dataset of micrometeorological conditions across 49 wildlife cameras in South Africa's Maloti-Drakensberg and the Swiss Alps. We train ensemble deep learning models to classify conditions as overcast, sunshine, hail or snow. We achieve 91.7% accuracy on test cameras not seen during training. Furthermore, we show how effective accuracy is raised to 96% by disregarding 14.1% of classifications where ensemble member models did not reach a consensus. For two-class weather classification (overcast vs. sunshine) in a novel location in Svalbard, Norway, we achieve 79.3% accuracy (93.9% consensus accuracy), outperforming a benchmark model from the computer vision literature (75.5% accuracy). Our model rapidly classifies sunshine, snow and hail in almost 2 million unlabelled images. Resulting micrometeorological data illustrated common seasonal patterns of summer hailstorms and autumn snowfalls across mountains in the northern and southern hemispheres. However, daily patterns of sunshine and shade diverged between sites, impacting daily temperature cycles. Crucially, we leverage micrometeorological data to demonstrate that (1) experimental warming using open-top chambers shortens early snow events in autumn, and (2) image-derived sunshine marginally outperforms sensor-derived temperature when predicting bumblebee foraging. These methods generate novel micrometeorological variables in synchrony with biological recordings, enabling new insights from an increasingly global network of wildlife cameras.

Differences in spatial niche of terrestrial mammals when facing extreme snowfall: the case in east Asian forests.

BACKGROUND: Recent climate changes have produced extreme climate events. This study focused on extreme snowfall and intended to discuss the vulnerability of temperate mammals against it through interspecies comparisons of spatial niches in northern Japan. We constructed niche models for seven non-hibernating species through wide-scaled snow tracking on skis, whose total survey length was 1144 km. RESULTS: We detected a low correlation (rs < 0.4) between most pairs of species niches, indicating that most species possessed different overwintering tactics. A morphological advantage in locomotion cost on snow did not always expand niche breadth. In contrast, a spatial niche could respond to (1) drastic landscape change by a diminishing understory due to snow, possibly leading to changes in predator-prey interactions, and (2) the mass of cold air, affecting thermoregulatory cost and food accessibility. When extraordinary snowfall occurred, the nonarboreal species with larger body sizes could niche shift, whereas the smaller-sized or semi-arboreal mammals did not. In addition, compared to omnivores, herbivores were prone to severe restriction of niche breadth due to a reduction in food accessibility under extreme climates. CONCLUSIONS: Dietary habits and body size could determine the redundancy of niche width, which may govern robustness/vulnerability to extreme snowfall events.

Muscae volitantes: A 19th-century precursor of visual snow syndrome?

PURPOSE: Visual snow syndrome comprises a whole-field static-like visual disturbance, with increased awareness of entopic phenomena, an inability to suppress the 'just seen' and photophobia. Visual snow syndrome is often associated with other problems such as headache, tinnitus, and anxiety. The earliest reported case of a patient experiencing symptoms consistent with visual snow syndrome dates only to 1995. This paper seeks to find patterns of experience in the medical literature of the past that are reminiscent of visual snow syndrome, to challenge the view that it is in any sense a novel disorder. Descriptions of subjective visual sensations such as experienced by patients suffering from visual snow syndrome were sought in treatises, textbooks and other literature generated by leading figures in 19th-century ophthalmology, physiology and physics. CONCLUSION: While retrospective diagnosis of modern illness categories in historical medical literature is an enterprise fraught with pitfalls, it is nonetheless possible to see patterns of experience in the 19th-century medical literature that are strongly reminiscent of visual snow syndrome.

High freezing sensitivity of legumes relative to other herbaceous species in northern temperate plant communities.

BACKGROUND AND AIMS: Reduced snow cover and increased air temperature variability are predicted to expose overwintering herbaceous plants to more severe freezing in some northern temperate regions. Legumes are a key functional group that may exhibit lower freezing tolerance than other species in these regions, but this trend has been observed only for non-native legumes. Our aim was to confirm if this trend is restricted to non-native legumes or whether native legumes in these regions also exhibit low freezing tolerance. METHODS: First, we transplanted legumes (five non-native species and four native species) into either an old field (non-native) or a prairie (native) and used snow removal to expose the plots to increased soil freezing. Second, we grew plants in mesocosms (old field) and pots (prairie species) and exposed them in controlled environment chambers to a range of freezing treatments (control, 0, -5 or -10 °C) in winter or spring. We assessed freezing responses by comparing differences in biomass, cover and nodulation between freezing (or snow removal) treatments and controls. KEY RESULTS: Among legume species, lower freezing tolerance was positively correlated with a lower proportion of nodulated plants and active nodules, and under controlled conditions, freezing-induced reductions in above-ground biomass were lower on average in native legumes than in non-native legumes. Nevertheless, both non-native and native legumes (except Desmodium canadense) exhibited greater reductions in biomass in response to increased freezing than their non-leguminous neighbours, both in controlled environments and in the field. CONCLUSIONS: These results demonstrate that both native and non-native legumes exhibit low freezing tolerance relative to other herbaceous species in northern temperate plant communities. By reducing legume biomass and nodulation, increased soil freezing could reduce nitrogen inputs into these systems.

Prevalence and characteristics of visual snow syndrome in a cohort of young Italian adults.

BACKGROUND: Visual snow (VS) and visual snow syndrome (VSS) are becoming increasingly recognized. However, their prevalence worldwide is unknown. This study aimed to investigate lifetime prevalence and describe the clinical characteristics of VS and VSS in a representative population sample from Italy. METHODS: This cross-sectional study was conducted among students attending different faculties in three universities in the central and southern regions of Italy. Eligible participants completed a self-administered questionnaire. In patients fulfilling possible criteria for VS/VSS, the diagnosis was validated by an on-site visit conducted by experienced neurologists and neuro-ophthalmologists that included optical coherence tomography angiography (OCTA). RESULTS: A total of 750 participants completed the study. Seven (0.9%) reported symptoms compatible with VS (mean age 24.8 ± 3.85 years). Among the seven patients, five (0.7%) also met the phenomenological and temporal criteria for VSS. Neuroimaging and ophthalmological examinations showed normal results upon review or during the on-site visit including OCTA. For the five patients with full VSS, the other visual symptoms reported were enhanced entoptic phenomenon (n = 5), photophobia (n = 5), palinopsia (n = 1), and nyctalopia (n = 4). In four of the seven patients (57%) reporting VS symptoms, there was a concomitant diagnosis of migraine with aura, and in one (14%) migraine without aura. All patients (n = 7) reported tinnitus. Six of the seven (85.7%) patients with VS/VSS had never used specific treatments for the condition. None of the seven patients had received a previous diagnosis of VS/VSS. CONCLUSIONS: The prevalence in Italy of VSS is around 1%. However, there is a limited tendency for affected individuals to seek medical attention, leading to a low rate of diagnosis and treatment.

Genetic consequences of Last Glacial-Holocene changes in snowfall regime in Arnica mallotopus populations: A plant confined to heavy-snow areas of Japan.

PREMISE: Snow is an important environmental factor affecting plant distribution. Past changes in snowfall regimes may have controlled the demographies of snow-dependent plants. However, our knowledge of changes in the distribution and demographies of such plants is limited because of the lack of fossil records. METHODS: Population genetic and landscape genetic analyses were used to investigate the response of population dynamics of Arnica mallotopus (Asteraceae)-a plant confined to heavy-snow areas of Japan-to changes in snowfall regimes from the Last Glacial Period to the Holocene. RESULTS: The population genetic analysis suggested that the four geographic lineages diverged during the Last Glacial Period. The interaction between reduced snowfall and lower temperatures during this period likely triggered population isolation in separate refugia. Subpopulation differentiation in the northern group was lower than in the southern group. Our ecological niche model predicted that the current distribution was patchy in the southern region; that is, the populations were isolated by topologically flat and climatically unsuitable lowlands. The landscape genetic analysis suggested that areas with little snowfall acted as barriers to the Holocene expansion of species distribution and continued limiting gene flow between local populations. CONCLUSIONS: These findings indicate that postglacial population responses vary among regions and are controlled by environmental and geographic factors. Thus, changes in snowfall regime played a major role in shaping the distribution and genetic structure of the snow-dependent plant.

Vertical Flux of Microplastics in the Deep Subtropical Pacific Ocean: Moored Sediment-Trap Observations within the Kuroshio Extension Recirculation Gyre.

The Kuroshio Extension recirculation gyre in the western North Pacific is an accumulation site of plastic litter transported by the Kuroshio Current. A sediment trap was moored at a depth of 4900 m at Station KEO within the Kuroshio Extension recirculation gyre, and the vertical flux of microplastics in sinking particles of size <1 mm was observed. Forty-one sediment-trap samples collected from July 1, 2014, to October 2, 2016, were analyzed with a micro-Fourier transform infrared spectrometer and microplastics were detected in all samples. Seventeen polymer types were identified, and 90% of the microplastics were less than 100 µm in size. Microplastic sinking was driven by the action of the biological pump, which was in turn driven by seasonal variations in solar radiation and increased surface primary production typical of the spring season. Microplastic mass flux varied from 4.5 × 10-3 to 0.38 mg m-2 day-1 during the sampling period, with a mean and standard deviation of 0.054 ± 0.075 mg m-2 day-1. Extrapolating the annual microplastic mass flux at Station KEO to the entire Kuroshio Extension recirculation gyre, it is estimated that 0.028 million metric tons of microplastics are transported annually to 4900 m depth in this area.