Bioenergetics of iron snow fueling life on Europa.

The main sources of redox gradients supporting high-productivity life in the Europan and other icy ocean world oceans were proposed to be photolytically derived oxidants, such as reactive oxygen species (ROS) from the icy shell, and reductants (Fe(II), S(-II), CH4, H2) from bottom waters reacting with a (ultra)mafic seafloor. Important roadblocks to maintaining life, however, are that the degree of ocean mixing to combine redox species is unknown, and ROS damage biomolecules. Here, we envisage a unique solution using an acid mine drainage (AMD)-filled pit lakes analog system for the Europan ocean, which previous models predicted to be acidic. We hypothesize that surface-generated ROS oxidize dissolved Fe(II) resulting in Fe(III) (hydr)oxide precipitates, that settle to the seafloor as "iron snow." The iron snow provides a respiratory substrate for anaerobic microorganisms ("breathing iron"), and limits harmful ROS exposure since they are now neutralized at the ice-water interface. Based on this scenario, we calculated Gibbs energies and maximal biomass productivities of various anaerobic metabolisms for a range of pH, temperatures, and H2 fluxes. Productivity by iron reducers was greater for most environmental conditions considered, whereas sulfate reducers and methanogens were more favored at high pH. Participation of Fe in the metabolic redox processes is largely neglected in most models of Europan biogeochemistry. Our model overcomes important conceptual roadblocks to life in icy ocean worlds and broadens the potential metabolic diversity, thus increasing total primary productivity, the diversity and volume of habitable environmental niches and, ultimately, the probability of biosignature detection.

Fungal diversity present in snow sampled in summer in the north-west Antarctic Peninsula and the South Shetland Islands, Maritime Antarctica, assessed using metabarcoding.

We assessed the fungal diversity present in snow sampled during summer in the north-west Antarctic Peninsula and the South Shetland Islands, maritime Antarctica using a metabarcoding approach. A total of 586,693 fungal DNA reads were obtained and assigned to 203 amplicon sequence variants (ASVs). The dominant phylum was Ascomycota, followed by Basidiomycota, Mortierellomycota, Chytridiomycota and Mucoromycota. Penicillium sp., Pseudogymnoascus pannorum, Coniochaeta sp., Aspergillus sp., Antarctomyces sp., Phenoliferia sp., Cryolevonia sp., Camptobasidiaceae sp., Rhodotorula mucilaginosa and Bannozyma yamatoana were assessed as abundant taxa. The snow fungal diversity indices were high but varied across the different locations sampled. Of the fungal ASVs detected, only 28 were present all sampling locations. The 116 fungal genera detected in the snow were dominated by saprotrophic taxa, followed by symbiotrophic and pathotrophic. Our data indicate that, despite the low temperature and oligotrophic conditions, snow can host a richer mycobiome than previously reported through traditional culturing studies. The snow mycobiome includes a complex diversity dominated by cosmopolitan, cold-adapted, psychrophilic and endemic taxa. While saprophytes dominate this community, a range of other functional groups are present.

Bacterial and fungal communities in sub-Arctic tundra heaths are shaped by contrasting snow accumulation and nutrient availability.

Climate change is affecting winter snow conditions significantly in northern ecosystems but the effects of the changing conditions for soil microbial communities are not well-understood. We utilized naturally occurring differences in snow accumulation to understand how the wintertime subnivean conditions shape bacterial and fungal communities in dwarf shrub-dominated sub-Arctic Fennoscandian tundra sampled in mid-winter, early, and late growing season. Phospholipid fatty acid (PLFA) and quantitative PCR analyses indicated that fungal abundance was higher in windswept tundra heaths with low snow accumulation and lower nutrient availability. This was associated with clear differences in the microbial community structure throughout the season. Members of Clavaria spp. and Sebacinales were especially dominant in the windswept heaths. Bacterial biomass proxies were higher in the snow-accumulating tundra heaths in the late growing season but there were only minor differences in the biomass or community structure in winter. Bacterial communities were dominated by members of Alphaproteobacteria, Actinomycetota, and Acidobacteriota and were less affected by the snow conditions than the fungal communities. The results suggest that small-scale spatial patterns in snow accumulation leading to a mosaic of differing tundra heath vegetation shapes bacterial and fungal communities as well as soil carbon and nutrient availability.

Global reduction of snow cover in ski areas under climate change.

Ongoing climate change substantially alters snowfall patterns with severe but diverging consequences for global ski areas. A global assessment as well as the investigation of potential implications for mountain ecosystems is currently lacking. We quantify future trends in natural snow cover days under different climate change scenarios until 2100 in seven major global skiing regions and discuss implications for mountainous biodiversity by analysing how natural snow cover days relate to regional human population density. Within all major skiing regions, snow cover days are projected to decrease substantially under every assessed climate change scenario. Thirteen percent of all current ski areas are projected to completely lose natural annual snow cover and one fifth will experience a reduction of more than 50% by 2071-2100 relative to historic baselines. Future skiable areas will concentrate in less populated areas, towards continental regions and inner parts of the mountain ranges. As skiable areas will be located at greater distances to highly populated areas in the future, we expect an expansion of infrastructure and increasing intervening actions (i.e., artificial snowmaking, slope grooming) to prolong snow duration. Our results are concerning for both the recreational and economic value of skiing as well as for mountain biodiversity since vulnerable high-altitude species might be threatened by space reductions with ski area expansion.

Later-melting rather than thickening of snowpack enhance the productivity and alter the community composition of temperate grassland.

Snowpack is closely related to vegetation green-up in water-limited ecosystems, and has effects on growing-season ecosystem processes. However, we know little about how changes in snowpack depth and melting timing affect primary productivity and plant community structure during the growing season. Here, we conducted a four-year snow manipulation experiment exploring how snow addition, snowmelt delay and their combination affect aboveground net primary productivity (ANPP), species diversity, community composition and plant reproductive phenology in seasonally snow-covered temperate grassland in northern China. Snow addition alone increased soil moisture and nutrient availability during early spring, while did not change plant community structure and ANPP. Instead, snowmelt delay alone postponed plant reproductive phenology, and increased ANPP, decreased species diversity and altered species composition. Grasses are more sensitive to changes in snowmelt timing than forbs, and early-flowering forbs showed a higher sensitivity compared to late-flowering forbs. The effect of snowmelt delay on ANPP and species diversity was offset by snow addition, probably because the added snow unnecessarily lengthens the snow-covering duration. The disparate effects of changes in snowpack depth and snowmelt timing necessitate their discrimination for more mechanistic understanding on the effects of snowpack changes on ecosystems. Our study suggests that it is essential to incorporate non-growing-season climate change events (in particular, snowfall and snowpack changes) to comprehensively disclose the effects of climate change on community structure and ecosystem functions.

Snow Contamination by Metals and Metalloids in a Polar Town: A Case Study of Nadym, Russia.

Snow composition depends on the long-range transport of pollutants. This article examines aspects of snow composition in the town of Nadym in Western Siberia. During fieldwork conducted in 2021 and 2022, we determined dust load, concentrations and ratio of dissolved and suspended forms of metals and metalloids (MMs). Moreover, we analyzed air mass trajectories using the HYSPLIT model, and the results showed that industrial regions of the southern Urals, southeastern Siberia, and Kazakhstan were the sources of MMs. Content of the insoluble fraction was increased by 23-fold in Nadym. The dust load in Nadym was higher than that in urban communities situated in the temperate zone, even though this town is relatively small in population and has little industrial infrastructure. This significant increase in dust load led to a ten- to 100-fold increase in the content MMs. Local soils (Fe, Al), vehicles (W), building dust (Mg, Ca), and anti-icing agents (Na) were found to be the sources of pollution. We found that the high dust load is caused by meteorological factors, such as temperature inversion and a large number of calm days, which reduce the dispersion of pollution. This case study demonstrates that winter air quality in polar settlements can be worse than that in urban areas in the temperate zone, even with few local sources of pollution. Furthermore, the trend toward an increase in the number of windless days, such as observed in Siberia as a result of global climate change, increases the risk of anthropogenic pollution of the atmosphere of polar cities.

Ice cage: new records and cryptic, isolated lineages in wingless snow flies (Diptera, Limoniidae: Chionea spp.) in German lower mountain ranges.

In Earth's history warm and cold periods have alternated. Especially, during the Pleistocene, the alternation between these different climatic conditions has led to frequent range expansions and retractions of many species: while thermophilic species dispersed during warm periods, cold adapted species retracted to cold refugia and vice versa. After the last Pleistocene cycle many cold adapted taxa found refuges in relict habitats in mountain ranges. One example for such a cold adapted relict is the flightless snow fly Chionea araneoides (Dalman, 1816). It can be found in lower mountain ranges of Central Europe exclusively in stone runs and stony accumulations which provide cold microclimates. Imagines develop only in winter. They have strongly restricted ranges and hence experienced strong isolation predicting that local populations may show local adaptation and hence also genetic differentiation. We investigated this for several middle mountain ranges of Germany using the COI barcoding gene. Our analyses revealed two distinct lineages, one in the Bavarian Forest and a second one in all other more northern locations up to Scandinavia. These lineages likely go back to post-Pleistocene isolation and should be studied in more detail in the future, also to confirm the taxonomic status of both lineages. Further, we confirmed former records of the species for Germany and report new records for the federal states of Saxony, Lower Saxony, Saxony-Anhalt and Thuringia. Finally, we provide the first evidence of two types of males for the species, a small and a larger male type.

A ticket to where? Dwindling snow cover impacts the winter tourism sector as a consequence of climate change.

Climate change affects human activities, including tourism across various sectors and time frames. The winter tourism industry, dependent on low temperatures, faces significant impacts. This paper reviews the implications of climate change on winter tourism, emphasising challenges for activities like skiing and snowboarding, which rely on consistent snowfall and low temperatures. As the climate changes, these once taken-for-granted conditions are no longer as commonplace. Through a comprehensive review supported by up-to-date satellite imagery, this paper presents evidence suggesting that the reliability of winter snow is decreasing, with findings revealing a progressive reduction in snow levels associated with temperature and precipitation changes in some regions. The analysis underscores the need for concerted efforts by stakeholders who must recognize the reality of diminishing snow availability and work towards understanding the specific changes in snow patterns. This should involve multi-risk and multi-instrument assessments, including ongoing satellite data monitoring to track snow cover changes. The practical implications for sports activities and the tourism industry reliant on snow involve addressing challenges by diversifying offerings. This includes developing alternative winter tourism activities less dependent on snow, such as winter hiking, nature walks, or cultural experiences.

Decreased snow depth inhibits litter decomposition via changes in litter microbial biomass and enzyme activity.

Decreased snow depth resulting from global warming has the potential to significantly impact biogeochemical cycles in cold forests. However, the specific mechanisms of how snow reduction affects litter decomposition and the underlying microbial processes remain unclear, this knowledge gap limits our ability to precisely predict ecological processes within cold forest ecosystems under climate change. Hence, a field experiment was conducted in a subalpine forest in southwestern China, involving a gradient of snow reduction levels (control, 50 %, 100 %) to investigate the effects of decreased snow on litter decomposition, as well as microbial biomass and activity, specifically focused on two common species: red birch (Betula albosinensis) and masters larch (Larix mastersiana). After one year of incubation, the decomposition rate (k-value) of the two types of litter ranged from 0.12 to 0.24 across three snow treatments. A significant lower litter mass loss, microbial biomass and enzyme activity were observed under decreased snow depth in winter. Furthermore, a hysteresis inhibitory effect of snow reduction on hydrolase activity was observed in the following growing season. Additionally, the high initial quality (lower C/N ratio) of red birch litter facilitated the colonization by a greater quantity of microorganisms, making it more susceptible to snow reduction compared to the low-quality masters larch litter. Structural equation models indicated that decreased snow depth hindered litter decomposition by altering the biological characterization of litter (e.g., microbial biomass and enzyme activity) and environmental variables (e.g., mean temperature and moisture content). The findings suggest that the potential decline in snow depth could inhibit litter decomposition by reducing microbial biomass and activity, implying that the future climate change may alter the material cycling processes in subalpine forest ecosystems.

Measuring Pb isotope ratios in fresh snow filtrate refines the apportioning of contaminant sources in the Arctic.

The remoteness and low population in the Arctic allow us to study global environmental processes, where the analysis of indicators can provide useful information about local and distant pollution sources. Fresh snow represents a convenient indicator of regional and transboundary atmospheric contamination sources, entrapping aerosols, and particulates like a natural autosampler of the environment. Lead stable isotopes are widely used to trace and monitor local and distant pollution sources. However, the behavior of Pb within different snow components is still not thoroughly studied, and its significance could be underestimated if only larger particulates are accounted for. We collected snow and samples from potential sources (fuel, rocks, coal) in three Arctic localities: Nuuk (Greenland), Reykjavik (Iceland), and Longyearbyen (Svalbard). We separated the filtrate from the filter residue through 0.45 µm nitrocellulose membranes to isolate the low-diameter particles associated with long-range transport from larger particles of mostly local natural origin. Filtrates yielded higher EFs (enrichment factor as the Pb/Al ratio relative to the upper crust) than filtration residues (80 ± 104 and 2.1 ± 1.1, respectively), and Pb isotope signals similar to fuel and coal (206Pb/207Pb are 1.199 ± 0.028 in coal, 1.168 ± 0.029 in filtrates, 1.163 ± 0.013 in fuel, 1.137 ± 0.045 in residues, and 0.985 ± 0.020 in rocks). In contrast to filtrates, the filter residues present wider ranges of Pb isotope compositions and crustal contributions and lower EFs, so we suggest that filtrate contains Pb from fuel combustion more selectively, while the residue carries a more considerable contribution of local mineral dust that can mask the contribution of other anthropogenic or distant natural sources. These findings add weight to the notion that filtrates are a more selective measure of metal deposition from long-range anthropogenic emissions compared to analyzing bulk melted snow or only filter residues.

Chionobium takahashii, gen. et sp. nov., associated with snow blight of conifers in Japan.

Gremmenia abietis (Dearn.) Crous (syn: Phacidium abietis) was originally described in North America to accommodate the species associated with snow blight of Abies and Pseudotsuga spp. In Japan, this species was first observed on the dead needles on Abies sachalinensis and Picea jezoensis var. jezoensis in 1969. However, the identity of Japanese species was unclear due to the lack of molecular data and the absence of anamorph description. In this study, we collected fresh specimens from various conifer species (A. sachalinensis, A. veitchii, Pic. jezoensis var. jezoensis, Pic. jezoensis var. hondoensis, Pinus koraiensis, and Pin. pumila) in Japan and revised the taxonomy based on morphological and phylogenetic analyses. Phylogenetic analyses based on nuc rDNA internal transcribed spacer ITS1-5.8S-ITS2 (ITS), nuc 28S rDNA (28S), and RNA polymerase II second largest subunit (RPB2) regions indicated that the species belongs to Phacidiaceae. Conidiomata formed in vitro produced pyriform, hyaline conidia without mucoid appendage, which distinguished the species from phylogenetically related genera. Consequently, we established Chionobium takahashii to accommodate the snow blight fungus in Japan. Further phylogenetic analyses also indicated that C. takahashii includes several distinct clades corresponding to the host genera (Abies, Picea, Pinus). Morphological differences among those clades were unclear, suggesting that C. takahashii may contain host-specific cryptic species.

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.

The Slip and Fall Index: Assessing the risk of slipping and falling on ice.

OBJECTIVES: Canadians are at an increased risk of outdoor slip and fall accidents during periods of ice and snow. The aim of this study was to create an index to alert the public of slippery outdoor conditions and promote pedestrian safety. METHODS: Emergency department (ED) presentations from the four adult hospitals in Calgary, Alberta, Canada, over an 11-year period (January 2008‒December 2018) were extracted and filtered using the ICD-10 code W00 (fall due to ice and snow). Multivariable dispersion-corrected Poisson regression models were used to determine the variables most predictive of these presentations. Month of year, the presence of ice, snow on ground (per 10 cm), and interactions between ice and snow, all up to 3 days prior, were used to create the Slip and Fall Index (SFI). RESULTS: The dataset included 14,977 slip and fall on ice/snow ED presentations. Females (57.36%, n = 8591) accounted for more presentations than males (42.64%, n = 6386). All months had a significant effect, either being predictive or protective of slip and falls on ice/snow. Current-day ice, snow on ground, and ice up to 3 days prior were predictive of increased presentations. Month and measurements of ice and snow can be input into the SFI, which generates the level of daily risk. CONCLUSION: The SFI is the first Canadian index with the purpose of measuring the risk of having a slip and fall accident on ice/snow.

RéSUMé: OBJECTIFS: Les Canadiennes et les Canadiens courent un risque accru de glissades et de chutes accidentelles à l'extérieur en période de glace et de neige. Notre étude visait à créer un indice pour avertir le public des conditions glissantes à l'extérieur et promouvoir la sécurité des piétons. MéTHODE: Les visites aux services des urgences (SU) des quatre hôpitaux pour adultes de Calgary (Alberta), au Canada, sur une période de 11 ans (janvier 2008‒décembre 2018) ont été extraites et filtrées à l'aide du code W00 (chute due à la glace et à la neige) de la CIM-10. Nous avons utilisé des modèles de régression de Poisson multivariés avec correction de la surdispersion pour déterminer les variables les plus susceptibles de prédire ces visites. Le mois de l'année, la présence de glace ou de neige au sol (par tranche de 10 cm) et les interactions entre la glace et la neige, tout cela au cours des trois jours précédents, ont servi à créer notre « indice des glissades et des chutes ¼ (IGC). RéSULTATS: Le jeu de données comprenait 14 977 visites aux SU en raison de glissades et de chutes sur la glace ou la neige. Les femmes (57,36%, n = 8 591) ont effectué plus de visites que les hommes (42,64%, n = 6 386). Tous les mois avaient un effet significatif, que ce soit comme variable prédictive ou préventive des glissades et des chutes sur la glace ou la neige. La présence de glace ou de neige au sol le jour même, et la présence de glace jusqu'à trois jours avant, ont permis de prédire les hausses des visites. Le mois et la hauteur de la glace et de la neige peuvent être saisis dans l'IGC, ce qui génère le niveau de risque quotidien. CONCLUSION: L'IGC est le premier indice canadien qui mesure le risque de glissades et de chutes accidentelles sur la glace ou la neige.

Snow cover-related camouflage mismatch increases detection by predators.

Camouflage expressed by animals is an adaptation to local environments that certain animals express to maximize survival and fitness. Animals at higher latitudes change their coat color according to a seasonally changing environment, expressing a white coat in winter and a darker coat in summer. The timing of molting is tightly linked to the appearance and disappearance of snow and is mainly regulated by photoperiod. However, due to climate change, an increasing mismatch is observed between the coat color of these species and their environment. Here, we conducted an experiment in northern Sweden, with white and brown decoys to study how camouflage (mis)-match influenced (1) predator attraction to decoys, and (2) predation events. Using camera trap data, we showed that mismatching decoys attracted more predators and experienced a higher likelihood of predation events in comparison to matching decoys, suggesting that camouflage mismatched animals experience increased detection by predators. These results provide insight into the function of a seasonal color coat and the need for this adaptation to maximize fitness in an environment that is exposed to high seasonality. Thus, our results suggest that, with increasing climate change and reduced snow cover, animals expressing a seasonal color coat will experience a decrease in survival.

Evidence of human influence on Northern Hemisphere snow loss.

Documenting the rate, magnitude and causes of snow loss is essential to benchmark the pace of climate change and to manage the differential water security risks of snowpack declines1-4. So far, however, observational uncertainties in snow mass5,6 have made the detection and attribution of human-forced snow losses elusive, undermining societal preparedness. Here we show that human-caused warming has caused declines in Northern Hemisphere-scale March snowpack over the 1981-2020 period. Using an ensemble of snowpack reconstructions, we identify robust snow trends in 82 out of 169 major Northern Hemisphere river basins, 31 of which we can confidently attribute to human influence. Most crucially, we show a generalizable and highly nonlinear temperature sensitivity of snowpack, in which snow becomes marginally more sensitive to one degree Celsius of warming as climatological winter temperatures exceed minus eight degrees Celsius. Such nonlinearity explains the lack of widespread snow loss so far and augurs much sharper declines and water security risks in the most populous basins. Together, our results emphasize that human-forced snow losses and their water consequences are attributable-even absent their clear detection in individual snow products-and will accelerate and homogenize with near-term warming, posing risks to water resources in the absence of substantial climate mitigation.

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.

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.

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.