Arctic Plants Research Articles

The potential for evolutionary rescue in an Arctic seashore plant threatened by climate change.

The impacts of climate change may be particularly severe for geographically isolated populations, which must adjust through plastic responses or evolve. Here, we study an endangered Arctic plant, Primula nutans ssp. finmarchica, confined to Fennoscandian seashores and showing indications of maladaptation to warming climate. We evaluate the potential of these populations to evolve to facilitate survival in the rapidly warming Arctic (i.e. evolutionary rescue) by utilizing manual crossing experiments in a nested half-sibling breeding design. We estimate G-matrices, evolvability and genetic constraints in traits with potentially conflicting selection pressures. To explicitly evaluate the potential for climate change adaptation, we infer the expected time to evolve from a northern to a southern phenotype under different selection scenarios, using demographic and climatic data to relate expected evolutionary rates to projected rates of climate change. Our results indicate that, given the nearly 10-fold greater evolvability of vegetative than of floral traits, adaptation in these traits may take place nearly in concert with changing climate, given effective climate mitigation. However, the comparatively slow expected evolutionary modification of floral traits may hamper the evolution of floral traits to track climate-induced changes in pollination environment, compromising sexual reproduction and thus reducing the likelihood of evolutionary rescue.

Predicting plants in the wild: Mapping arctic and boreal plants with UAS-based visible and near infrared reflectance spectra

Biophysical changes in the Arctic and boreal zones drive shifts in vegetation, such as increasing shrub cover from warming soil or loss of living mat species due to fire. Understanding current and future responses to these factors requires mapping vegetation at a fine taxonomic resolution and landscape scale. Plants vary in size and spectral signatures, which hampers mapping of meaningful functional groups at coarse spatial resolution. Fine spatial grain of remotely sensed data (<10 cm pixels) is often necessary to resolve patches of many Arctic and boreal plant groups, such as bryophytes and lichens, which are significant components of terrestrial vegetation cover. Separation of co-occurring small vegetation patches in images also requires high spectral resolution. Our goal here was to test the capabilities of UAS-based imaging spectroscopy for mapping plant functional types (PFT) using high spatial and spectral resolution data over Arctic and boreal vegetation at four sites in central Alaska. We then tested several Machine and Deep learning models of PFT cover using the reflectance spectra. The best models were very simple, balancing both bias (overfitting caused by imbalance sample sizes) and variance (fit to the independent validation data), explaining > 50 % of the independent ground cover estimation and > 84 % accuracy in estimating validation pixels. We explored the impact of spectral resolution on PFT mapping by including vegetation indices and a gradient of narrow (5 nm) to wide (50 nm) band features in our classification models across. Vegetation indices were the most important predictors for classifying PFTs, while including band features improved models, with narrow and wide bandwidths having similar importance but models with wide bandwidths performing slightly better. We conclude that Arctic and boreal PFT reflectance can be pooled across sites for mapping with relatively few labeled pixels. Underfit, simple algorithms outperformed deep learning, at least with these small sample sizes, in classifying PFTs by balancing bias and variance. Future work should aim to increase the number of labeled pixels and the detail of labels to further improve mapping taxonomic precision.

Whole-genome sequencing of 13 Arctic plants and draft genomes of Oxyria digyna and Cochlearia groenlandica

To understand the genomic characteristics of Arctic plants, we generated 28–44 Gb of short-read sequencing data from 13 Arctic plants collected from the High Arctic Svalbard. We successfully estimated the genome sizes of eight species by using the k-mer-based method (180–894 Mb). Among these plants, the mountain sorrel (Oxyria digyna) and Greenland scurvy grass (Cochlearia groenlandica) had relatively small genome sizes and chromosome numbers. We obtained 45 × and 121 × high-fidelity long-read sequencing data. We assembled their reads into high-quality draft genomes (genome size: 561 and 250 Mb; contig N50 length: 36.9 and 14.8 Mb, respectively), and correspondingly annotated 43,105 and 29,675 genes using ~46 and ~85 million RNA sequencing reads. We identified 765,012 and 88,959 single-nucleotide variants, and 18,082 and 7,698 structural variants (variant size ≥ 50 bp). This study provided high-quality genome assemblies of O. digyna and C. groenlandica, which are valuable resources for the population and molecular genetic studies of these plants.

Traditional Fish Leather Dyeing Methods with Indigenous Arctic Plants

Along the Arctic and sub-Arctic coasts of Alaska, Siberia, north-eastern China, Hokkaido, Scandinavia and Iceland, people have dressed in clothes or worn shoes made of fish skin for millennia. (Within this article, the terms fish skin and fish leather are used to indicate different processes of the same material. Fish skin: Skin indicates the superficial dermis of an animal. Fish skin is referred to as the historical raw material that is tanned following traditional methods such as mechanical, oiling and smoking tanning, using materials such as bark, brain, urine, fish eggs and corn flour. Fish leather is used to refer that the fish skin has passed one or more stages of industrial vegetable or chrome tanning production and is ready to be used to produce leather goods). These items are often decorated with a rich colour palette of natural dyes provided by nature. In this study, minerals and raw materials of plant origin were collected from riverbanks and processed by Arctic seamstresses who operated as designers, biochemists, zoologists, and climatologists simultaneously. During our research, an international team of fashion, tanning and education specialists used local Arctic and sub-Arctic flora from Sweden, Iceland, and Japan to dye fish leather. Several plants were gathered and sampled on a small scale to test the process and determine the colours they generated based on the historical literature and verbal advice from local experts. This paper describes the process and illustrates the historical use of natural dyes by the Arctic groups originally involved in this craft, building on the traditional cultural heritage that has enabled us to develop sustainable dyeing processes. The results are promising and confirm the applicability of these local plants for dyeing fish skins, providing a basis for a range of natural dye colours from local Arctic flora. The aim is to develop a moderate-sized industrial production of fish leather in this colour palette to replace current unsustainable chemical dyeing processes. This project represents an innovation in material design driven by traditional technologies, addressing changes in interactions between humans and with our environment. The results indicate that new materials, processes, and techniques are often the fruitful marriage of fashion and historical research of traditional methods, helping the industry move towards a more sustainable future.

Recovery of metabolites via subnivean photosynthesis in Arctic tundra plants: Implications for climate change

AbstractPlants have evolved numerous strategies for surviving the harsh conditions of the Arctic. One strategy for Arctic evergreen and semi‐evergreen species is to photosynthesize beneath the snow during spring. However, the prevalence of this photosynthesis and how recent photosynthates are used is still unknown. Here we ask, how is newly acquired carbon beneath the snow allocated? To answer this question, we delivered isotopically labeled 13CO2 to tussock tundra plants before snowmelt. Soluble sugars and starches were preferentially enriched with 13C in all five species tested, with lipids having comparatively low 13C enrichment. These results provide evidence of the recovery of metabolites used over the long winter. Additionally, these new soluble sugars may function in photoprotection and cold tolerance as plants release from snow cover. Climate change, by reducing the duration of subnivean photosynthesis of these species, will limit metabolite production before snowmelt, which may lead to a reduction in the ability of these species to compete effectively during the growing season, potentially leading to changes in community structure.

Extreme overall mushroom genome expansion in Mycena s.s. irrespective of plant hosts or substrate specializations

Mycena s.s. is a ubiquitous mushroom genus whose members degrade multiple dead plant substrates and opportunistically invade living plant roots. Having sequenced the nuclear genomes of 24 Mycena species, we find them to defy the expected patterns for fungi based on both their traditionally perceived saprotrophic ecology and substrate specializations. Mycena displayed massive genome expansions overall affecting all gene families, driven by novel gene family emergence, gene duplications, enlarged secretomes encoding polysaccharide degradation enzymes, transposable element (TE) proliferation, and horizontal gene transfers. Mainly due to TE proliferation, Arctic Mycena species display genomes of up to 502 Mbp (2-8× the temperate Mycena), the largest among mushroom-forming Agaricomycetes, indicating a possible evolutionary convergence to genomic expansions sometimes seen in Arctic plants. Overall, Mycena show highly unusual, varied mosaic-like genomic structures adaptable to multiple lifestyles, providing genomic illustration for the growing realization that fungal niche adaptations can be far more fluid than traditionally believed.

Genomics- and Transcriptomics-Guided Discovery of Clavatols from Arctic Fungi Penicillium sp. MYA5.

Clavatols exhibit a wide range of biological activities due to their diverse structures. A genome mining strategy identified an A5cla cluster from Penicillium sp. MYA5, derived from the Arctic plant Dryas octopetala, is responsible for clavatol biosynthesis. Seven clavatols, including one new clavatol derivate named penicophenone F (1) and six known clavatols (2-7), were isolated from Penicillium sp. MYA5 using a transcriptome mining strategy. These structures were elucidated by comprehensive spectroscopic analysis. Antibacterial, aldose reductase inhibition, and siderophore-producing ability assays were conducted on compounds 1-7. Compounds 1 and 2 demonstrated inhibitory effects on the ALR2 enzyme with inhibition rates of 75.3% and 71.6% at a concentration of 10 μM, respectively. Compound 6 exhibited antibacterial activity against Staphylococcus aureus and Escherichia coli with MIC values of 4.0 μg/mL and 4.0 μg/mL, respectively. Additionally, compounds 1, 5, and 6 also showed potential iron-binding ability.

Scale-dependent effects of herbivory on moss communities in Arctic wetlands: A 25-year experiment.

Arctic ecosystems are undergoing rapid changes, including increasing disturbance by herbivore populations, which can affect plant species coexistence and community assemblages. Although the significance of mosses in Arctic wetlands is well recognized, the long-term influence of medium-sized herbivores on the composition of moss communities has received limited attention. We used data from a long-term (25 years) Greater Snow Goose (Anser caerulescens atlanticus) exclusion experiment in Arctic tundra wetlands to assess changes in the composition of moss communities at multiple spatial scales (cell, 4 cm2; quadrat, 100 cm2; exclosure, 16 m2). We investigated how snow goose grazing and grubbing can alter the composition of the moss community by measuring changes in alpha and beta diversity, as well as in the strength of plant interspecific interactions between moss species. Our results indicate that goose foraging significantly increased species diversity (richness, evenness, and inverse Simpson index) of moss communities at the cell and quadrat scales but not the exclosure scale. Goose foraging reduced the dissimilarity (beta diversity) of moss communities at all three scales, mainly due to decreased species turnover. Furthermore, goose foraging increased positive interaction between moss species pairs. These findings emphasize the critical role of geese in promoting moss species coexistence and increasing homogeneity in Arctic wetlands. This study illustrates how top-down regulation by herbivores can alter plant communities in Arctic wetlands and highlights the importance of considering herbivores when examining the response of Arctic plant biodiversity to future climate change.

Summer drought weakens land surface cooling of tundra vegetation

Siberia experienced a prolonged heatwave in the spring of 2020, resulting in extreme summer drought and major wildfires in the North-Eastern Siberian lowland tundra. In the Arctic tundra, plants play a key role in regulating the summer land surface energy budget by contributing to land surface cooling through evapotranspiration. Yet we know little about how drought conditions impact land surface cooling by tundra plant communities, potentially contributing to high air temperatures through a positive plant-mediated feedback. Here we used high-resolution land surface temperature and vegetation maps based on drone imagery to determine the impact of an extreme summer drought on land surface cooling in the lowland tundra of North-Eastern Siberia. We found that land surface cooling differed strongly among plant communities between the drought year 2020 and the reference year 2021. Further, we observed a decrease in the normalized land surface cooling (measured as water deficit index) in the drought year 2020 across all plant communities. This indicates a shift towards an energy budget dominated by sensible heat fluxes, contributing to land surface warming. Overall, our findings suggest significant variation in land surface cooling among common Arctic plant communities in the North-Eastern Siberian lowland tundra and a pronounced effect of drought on all community types. Based on our results, we suggest discriminating between functional tundra plant communities when predicting the drought impacts on energy flux related processes such as land surface cooling, permafrost thaw and wildfires.

The Arctic Plant Aboveground Biomass Synthesis Dataset

Plant biomass is a fundamental ecosystem attribute that is sensitive to rapid climatic changes occurring in the Arctic. Nevertheless, measuring plant biomass in the Arctic is logistically challenging and resource intensive. Lack of accessible field data hinders efforts to understand the amount, composition, distribution, and changes in plant biomass in these northern ecosystems. Here, we present The Arctic plant aboveground biomass synthesis dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass (g m−2) on 2,327 sample plots from 636 field sites in seven countries. We created the synthesis dataset by assembling and harmonizing 32 individual datasets. Aboveground biomass was primarily quantified by harvesting sample plots during mid- to late-summer, though tree and often tall shrub biomass were quantified using surveys and allometric models. Each biomass measurement is associated with metadata including sample date, location, method, data source, and other information. This unique dataset can be leveraged to monitor, map, and model plant biomass across the rapidly warming Arctic.

The specific molecular signature of dissolved organic matter extracted from different arctic plant species persists after biodegradation

Dissolved organic matter (DOM) is a small but very reactive pool of organic matter (OM) in the environment. Its role is related to its composition, which depends on its source. In soils, vegetation is the main source of DOM, and biodegradation is the main regulating mechanism. This study aims to characterise DOM produced by contrasted arctic vegetation species and their biodegradation products.The water-extractable organic matter (WEOM) was produced from C. stellaris (lichen), E. vaginatum (sedge), A. polifolia (dwarf evergreen shrub) and B. nana (deciduous dwarf shrub). The WEOM were inoculated with a common aerobic heterotrophic soil bacteria (P. aureofaciens) and incubated for 7 days. During the experiment, WEOM was characterised through a wide range of analytical methods (TOC, UV–Vis absorbance, high-performance ion chromatography and HRMS Orbitrap).The results showed bacteria consumed a significantly greater proportion of WEOM produced by C. stellaris than by A. polifolia and B. nana at the end of the experiment (p < 0.05). Furthermore, the number of features in WEOM decreased for C. stellaris and E. vaginatum, whereas it increased for B. nana. These findings shed light on the species-specific biodegradation processes that rely on the initial composition of DOM, specifically influenced by the vegetation's capacity to produce recalcitrant compounds. Furthermore, our results emphasised that even though bacterial activity greatly impacted molecular characteristics, the WEOM produced by different vegetation species maintained their distinct molecular signatures. As a result, it can be inferred that the DOM found in natural environments directly reflects the relevant vegetation cover despite the strong influence of biogeochemical processes on DOM molecular composition. This should be considered when developing models to assess the influence of climate change on vegetation cover composition and its subsequent effects on DOM dynamics in soil and surface waters.

Current and past climate co-shape community-level plant species richness in the Western Siberian Arctic.

The Arctic ecosystems and their species are exposed to amplified climate warming and, in some regions, to rapidly developing economic activities. This study assesses, models, and maps the geographic patterns of community-level plant species richness in the Western Siberian Arctic and estimates the relative impact of environmental and anthropogenic factors driving these patterns. With our study, we aim at contributing toward conservation efforts for Arctic plant diversity in the Western Siberian Arctic. Western Siberian Arctic, Russia. We investigated the relative importance of environmental and anthropogenic predictors of community-level plant species richness in the Western Siberian Arctic using macroecological models trained with an extensive geobotanical dataset. We included vascular plants, mosses and lichens in our analysis, as non-vascular plants substantially contribute to species richness and ecosystem functions in the Arctic. We found that the mean community-level plant species richness in this vast Arctic region does not decrease with increasing latitude. Instead, we identified an increase in species richness from South-West to North-East, which can be well explained by environmental factors. We found that paleoclimatic factors exhibit higher explained deviance compared to contemporary climate predictors, potentially indicating a lasting impact of ancient climate on tundra plant species richness. We also show that the existing protected areas cover only a small fraction of the regions with highest species richness. Our results reveal complex spatial patterns of community-level species richness in the Western Siberian Arctic. We show that climatic factors such as temperature (including paleotemperature) and precipitation are the main drivers of plant species richness in this area, and the role of relief is clearly secondary. We suggest that while community-level plant species richness is mostly driven by environmental factors, an improved spatial sampling will be needed to robustly and more precisely assess the impact of human activities on community-level species richness patterns. Our approach and results can be used to design conservation strategies and to investigate drivers of plant species richness in other arctic regions.

Remote Sensing Revolution: Mapping Land Productivity and Vegetation Trends with Unmanned Aerial Vehicles (UAVs)

Abstract: This review paper offers a comprehensive exploration of the multifaceted applications of Unmanned Aerial Vehicles (UAVs) in various domains, showcasing their transformative impact in addressing complex challenges. The evaluation of cloud-based UAV systems' stability reveals their robustness and reliability, underlining their significance in numerous industries. Additionally, their role in enhancing robot navigation in intricate environments signifies a substantial advancement in robotics and automation. The integration of blockchain technology for secure Internet of Things (IoT) data transfer emphasizes the critical importance of data integrity and confidentiality in the IoT era. Furthermore, the optimization of energy-efficient data collection in IoT networks through UAVs demonstrates their potential to revolutionize data-driven decision-making processes, particularly in fields reliant on data accuracy and timeliness. The paper also highlights the application of deep reinforcement learning to enhance UAV-assisted IoT data collection, showcasing the synergy between advanced machine learning techniques and UAV technology. Finally, the discussion underscores the pivotal role of UAVs in precision agriculture, where they facilitate ecological farming practices and monitor environmental conditions, contributing to the pursuit of sustainable and efficient agriculture. This review reaffirms UAVs' status as transformative tools, reshaping industries and unlocking new frontiers of innovation and problem-solving. With ongoing technological advancements, UAVs are poised to play an increasingly central role in a wide range of applications, promising a future marked by ground breaking possibilities. Key findings include the dominance of the United States and China in the field, exploration of characteristics such as crop production, and innovative UAV-based methods for grassland mapping, maize growth assessment, and Arctic plant species monitoring. The research underscores the potential of UAVs in bridging field data and satellite mapping, providing valuable insights into diverse applications, from soil analysis to yield predictions, highlighting their transformative role in environmental monitoring and precision agriculture

Thermal germination characteristics of three High Arctic plants: Implications for their response to climate warming

Although temperature plays a crucial role in governing seed reproduction in High Arctic plants, little is known about the germination response of these plants to climate warming. We conducted a germination experiment to examine the thermal germination characteristics of three common High Arctic plant species in Svalbard: Dryas octopetala, Oxyria digyna, and Salix polaris. We exposed the seeds to two temperature regimes: gradually increasing and decreasing temperatures between 4 and 15 °C. Additionally, we measured the ground surface temperatures at the study site. All three High Arctic plant species exhibited no specific temperature requirements for germination, with minimum germination temperatures falling within the range of 4–8 °C. Based on the ground surface temperature data, the period during which the weekly average ground surface temperature exceeded this minimum germination temperature range (period available for germination) spanned from mid-June to mid-August. By simulating a warming scenario of 2 and 4 °C, we estimated that the onset of the period available for germination would advance by 1–2 and 2–3 weeks, respectively. Furthermore, our results suggest the possibility of autumn germination in the High Arctic region under future warming conditions.

Characterization and discrimination of tundra plant leaves by Attenuated Total Reflection Fourier transform infrared spectroscopy

Attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy is a powerful tool for investigating the biochemical fingerprint of plants, but its applicability to tundra plant leaves has yet to be addressed. The present study aimed to apply ATR-FTIR measurement to characterize tundra plant leaves and to discriminate these among plant species with different growth forms. The ATR-FTIR spectra in the fingerprint region (1800–800 cm−1) of live and dead leaves from 14 tundra plant species of shrubs, forbs, graminoids, and mosses showed a variability in overall appearance among plant species and a degree of similarity between live and dead leaves of the same plant species. Four highest peaks were found at 1637–1575 cm−1, 1452–1406 cm−1, 1325–1313 cm−1, and 1058–1022 cm−1 in these spectra and are attributed to chemical features of lignin, cellulose, and/or oxalate. Principal component analyses showed that leaves of Oxyria digyna and other forbs had distinctive spectral characteristics attributable to the content of oxalate and other putative compounds and that contents of lignin relative to cellulose were generally greater in shrubs than in graminoids and mosses. These results demonstrated that ATR-FTIR spectroscopy is useful for future applications in polar biology and ecology, for example the description of functional traits of arctic plants and decomposition processes by microbes.

Spectral unmixing-based Arctic plant species analysis using a spectral library and terrestrial hyperspectral Imagery: A case study in Adventdalen, Svalbard

Remote sensing is an invaluable tool for monitoring the rapid changes in Arctic vegetation distribution caused by global warming. Although hyperspectral data consisting of contiguous spectral bands enables the quantitative analysis of remote sensing data, mapping Arctic vegetation using hyperspectral remote sensing remains challenging due to the difficulty in acquiring data from the region. Additionally, the mixed pixel issue, which represents a mixture of more than one plant species due to low-spatial resolution, hinders accurate mapping of Arctic vegetation. To address these limitations, we collected hyperspectral information on the dominant plant species, such as shrubs and graminoids, in Adventdalen, Svalbard, and investigated effective methods for mapping Arctic vegetation using spectral unmixing. First, labeled datasets were constructed for Arctic plant species by extracting pixel data from terrestrial hyperspectral images. A spectral library was developed using the labeled datasets and used for spectral unmixing as endmembers. We employed three established classifiers, random forest, support vector machine, and one-dimensional convolutional neural network (1D-CNN) for hyperspectral image classification. Subsequently, we quantitatively and qualitatively compared the classification performances of these machine learning-based classifiers to determine the optimal classification method for validation purposes. The first derivative spectra of smoothed reflectance (RS,FD) and the 1D-CNN classifier were used to identify ground truth by classifying pixels of Arctic vegetation because they achieved the highest statistical accuracies of 0.9892 (Kappa = 0.9880) and 0.9352 (Kappa = 0.9280) for the two independent test sets and produced the most accurate vegetation maps. The spectral library using the RS,FD spectrum showed high spectral discriminability and potential for estimating the abundance of classes from simulated mixed pixels, resulting in good agreement with the ground truth. Accordingly, our findings provide valuable insights and references for large-scale mapping studies using remote sensing data and offer effective monitoring strategies for Arctic vegetation changes in response to climate change.

PiCAM: A Raspberry Pi‐based open‐source, low‐power camera system for monitoring plant phenology in Arctic environments

Abstract Time‐lapse cameras have been widely used as a tool to monitor the timing of seasonal vegetation growth. These simple, relatively inexpensive systems can provide high‐frequency observations of leaf development and demography which are critical data sets needed to characterize plant phenology from species to landscapes. This is important for understanding how plants are responding to global changes, as well as for validating satellite‐derived phenology products. However, in remote regions including the high‐latitude Arctic, deploying time‐lapse cameras could be challenging. The remoteness and lack of widespread power and telecommunications infrastructure limit options for the installation, maintenance and retrieval of data and equipment, and make it difficult for cameras to survive in extreme weather (e.g. long cold winters). To improve our understanding of Arctic phenology, new technologies are required to address these challenges. Here, we present a novel, low‐power, compact, lightweight time‐lapse camera system, called power‐interval camera automation module (PiCAM). The PiCAM was designed with explicit consideration to simplify deployment (i.e. without a need for external power supplies) of camera systems and to address the challenges of camera survival in harsh Arctic environments. In this paper, we describe the design, setup and technical details of the PiCAM and provide a roadmap for how to build and operate these systems. As proof of concept, we deployed 26 PiCAMs at three low‐Arctic tundra sites on the Seward Peninsula, Alaska in early August 2021 for characterizing Arctic plant phenology. Of the 26 PiCAMs, 70% remained active at the point of our revisit in late July 2022 despite the extreme winter temperatures they experienced (&lt; −30°C, heavy snow cover). We extracted key plant phenology metrics from the PiCAMs and captured strong differences across key Arctic plant species. We showed that the PiCAM has the potential to be widely used for monitoring plant phenology across the broader Arctic region, addressing the need for ground‐based understanding of Arctic phenological diversity to develop knowledge of plant response to climate change and to validate remote sensing products.

Climate-induced hydrological fluctuations shape Arctic Alaskan peatland plant communities

Rapidly increasing temperatures in high-latitude regions are causing major changes in wetland ecosystems. To assess the impact of concomitant hydroclimatic fluctuations, mineral deposition, and autogenous succession on the rate and direction of changing arctic plant communities in Arctic Alaska, we conducted detailed palaeoecological analyses using plant macrofossil, pollen, testate amoebae, elemental analyses, and radiocarbon and lead (210Pb) dating on two replicate monoliths from a peatland that developed in a river valley on the northern foothills of the Books Range. We observed an expansion of Sphagnum populations and vascular plants preferring dry habitats, such as Sphagnum warnstorfii, Sphagnum teres/squarrosum, Polytrichum strictum, Aulacomnium palustre and Salix sp., in recent decades between 2000 and 2015 CE, triggered by an increase in temperature and deepening water tables. Deepening peatland water tables became accentuated over the last two decades, when it reached its lowest point in the last 700 years. Conversely, a higher water-table between ca. 1500 and 1950 CE led to a recession of Sphagnum communities and an expansion of sedges. The almost continuous supply of mineral matter during this time led to a dominance of minerotrophic plant communities, although with varying species composition throughout the study period. The replicate cores show similar patterns, but nuanced differences are also visible, depicting fine spatial scale differences particularly in peat-forming plant distribution and the different timings of their presence. In conclusion, our study provides valuable insights into the impact of hydroclimatic fluctuations on peatland vegetation in Arctic Alaska, highlighting their tendency to dry out in recent decades. It also highlights the importance of river valley peatlands in paleoenvironmental reconstructions.

Arctic Plant Responses to Summer Climates and Flooding Events: A Study of Carbon and Nitrogen‐Related Larch Growth and Ecosystem Parameters in Northeastern Siberia

AbstractBuilt upon a 5‐year field investigation and a 13‐year satellite data set, this study examines the intricate interrelationships among ecophysiological parameters of Larix gmelinii trees and the prevailing ecosystem, climatic, and environmental factors present in the Indigirka lowlands of northeastern Siberia. It identified spatial‐temporal patterns in July needle nitrogen (N) content as an indicator of N availability from 2009 to 2013. Needle N content (%) revealed distinct yearly values: 2012 (1.31 ± 0.24), 2013 (1.67 ± 0.39), 2009 (1.72 ± 0.15), 2011 (1.84 ± 0.34), and 2010 (2.08 ± 0.25). Positive correlations were found between ecosystem and larch parameters, as well as between September temperature or February/May precipitation and subsequent July ecosystem productivity. Soil moisture (SM) primarily influences N availability across sites, with higher SM levels reducing N availability. However, July air temperature (AT) is the primary driver of interannual N availability changes, with higher temperatures enhancing N availability. Larch photosynthesis is mainly influenced by solar radiation (SR), temperature, N availability, and SM. Annual fluctuations in SR positively impact larch photosynthesis, while high temperatures or wetting events impose limitations on photosynthesis, even if N availability has increased. Consequently, a moderate correlation exists between N availability and photosynthesis across various sites and years (r = 0.422, P = 0.133, n = 14). In summary, this research provides valuable insights into climatic and environmental impacts on larch trees and ecosystems, emphasizing the significance of SM, AT, and SR for predicting future growth patterns of larch.

The Perspective of Arctic-Alpine Species in Southernmost Localities: The Example of Kalmia procumbens in the Pyrenees and Carpathians.

High-mountain and arctic plants are considered especially sensitive to climate change because of their close adaptation to the cold environment. Kalmia procumbens, a typical arctic-alpine species, reaches southernmost European localities in the Pyrenees and Carpathians. The aim of this study was the assessment and comparison of the current potential niche areas of K. procumbens in the Pyrenees and Carpathians and their possible reduction due to climate change, depending on the scenario. The realized niches of K. procumbens in the Pyrenees are compact, while those in the Carpathians are dispersed. In both mountain chains, the species occurs in the alpine and subalpine vegetation belts, going down to elevations of about 1500-1600 m, while the most elevated localities in the Pyrenees are at ca. 3000 m, about 500 m higher than those in the Carpathians. The localities of K. procumbens in the Carpathians have a more continental climate than those in the Pyrenees, with lower precipitation and temperatures but higher seasonality of temperature and precipitation. The species covered a larger area of geographic range during the Last Glacial Maximum, but its geographic range was reduced during the mid-Holocene. Due to climate warming, a reduction in the potential area of occurrence could be expected in 2100; this reduction is expected to be strong in the Carpathians and moderate in the Pyrenees.