Warming of subarctic tundra increases emissions of all three important greenhouse gases – carbon dioxide,methane, and nitrous oxide

Rapidly rising temperatures in the Arctic might cause a greater release of greenhouse gases (GHGs) to the atmosphere. To study the effect of warming on GHG dynamics, we deployed open‐top chambers in a subarctic tundra site in Northeast European Russia. We determined carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) fluxes as well as the concentration of those gases, inorganic nitrogen (N) and dissolved organic carbon (DOC) along the soil profile. Studied tundra surfaces ranged from mineral to organic soils and from vegetated to unvegetated areas. As a result of air warming, the seasonal GHG budget of the vegetated tundra surfaces shifted from a GHG sink of ?300 to ?198 g CO₂–eq m^?2 to a source of 105 to 144 g CO₂–eq m^?2. At bare peat surfaces, we observed increased release of all three GHGs. While the positive warming response was dominated by CO₂, we provide here the first in situ evidence of increasing N₂O emissions from tundra soils with warming. Warming promoted N₂O release not only from bare peat, previously identified as a strong N₂O source, but also from the abundant, vegetated peat surfaces that do not emit N₂O under present climate. At these surfaces, elevated temperatures had an adverse effect on plant growth, resulting in lower plant N uptake and, consequently, better N availability for soil microbes. Although the warming was limited to the soil surface and did not alter thaw depth, it increased concentrations of DOC, CO_2, and CH₄ in the soil down to the permafrost table. This can be attributed to downward DOC leaching, fueling microbial activity at depth. Taken together, our results emphasize the tight linkages between plant and soil processes, and different soil layers, which need to be taken into account when predicting the climate change feedback of the Arctic.     

Morphological and functional traits of herbaceous plants with different functional types in the European Northeast

We aimed to identify marker traits indicating the functional types of plants in the European Northeast. We try to answer the following questions. Which ecological factors make the largest contribution to identifying the functional types of plants in the North and can CO₂-exchange and related traits be used as markers? The data were collected from 1000-km latitudinal gradient across middle, north, and far north boreal forests in the east border of Europe. Comparative analysis of 102 species from 36 plant families enabled us to determine the marker traits indicating plant functional types. Competitor species have maximal plant height, comparatively low leaf dry matter content (LDMC), and accumulate high amounts of nitrogen in leaves. These species also have comparatively high photosynthetic and respiration rates. Ruderal species have low values of LDMC, and maximal photosynthetic rate, respiration rate, and photosynthetic nitrogen-use efficiency (PNUE). Slow-growing stress tolerators have a low photosynthetic rate, low respiration rate, and low levels of nitrogen and PNUE. The specific leaf area (SLA) of these plants shows a highly significant correlation with the light regime. In the boreal zone, SLA was found to be more closely related to light availability than to the plant functional type, indicating that SLA is unsuitable for use as a marker trait. We found strong correlations between plant height, respiration rate, and photosynthetic activity and soil nutrition according to Ellenberg values. Soil mineral element contents and acidity were found to have a significant influence on the functional types of plants.     

The Complexes of Mosquito Species (Diptera: Culicidae) at the Yaksha Site of the Pechora-Ilych Nature Reserve in the Komi Republic

Entomological Review - New data are presented on the biotopic distribution of mosquitoes (Diptera: Culicidae) at the plain (Yaksha) site of the Pechora-Ilych Nature Biosphere Reserve. The species...     

Plant CSR types in the north: comparing the morphological and morpho-physiological approaches

Grime’s competition–stress–ruderal (CSR) theory is widely used to study plant species’ responses to multiple environmental factors. We compared two models to allocate CSR types the global “StrateFy” model (Pierce et al. Funct Ecol, 31:444–457, 2017) and a locally developed morpho-physiological model (Novakovskiy et al. Int J Ecol, p e1323614, 2016). The “StrateFy” model is based on three morphological leaf traits: leaf area (LA), leaf dry matter content (LDMC) and specific leaf area (SLA). The morpho-physiological model additionally uses plant height (PH), leaf dry weight (LDW), photosynthetic capacity (PN) and respiration rate (RD), leaf nitrogen, and carbon concentration (LNC, LCC). We applied both models to 74 plant species, the traits of which were measured at mountain (Northern Urals) and plane (Komi Republic, Russia) landscapes of European Northeast. The comparison of the calculated C, S, and R scores showed two groups of species with large and unidirectional differences. The first group consists of species with a shift from S (morpho-physiological model) to CR (StrateFy model) strategy. Species of this group are typical for deep shaded habitats and characterized by low LDMC (10–25%) and high SLA (30–60 mm² mg⁻¹). The second group consists of C species (morpho-physiological model) which were classified as S (StrateFy model) strategy. This group includes mainly tall shrubs, graminoids, and forbs with relatively small leaves (300–2000 mm²). In our opinion, the CSR strategies obtained by the morpho-physiological model showed better agreement with the basic principles underlying Grime''s theory. The use of a limited number of morphological traits (LA, LDMC, SLA) in the StrateFy model does not always allow to determine the life strategy correctly. For example, these traits are insufficient for a clear separation of deeply shaded stress-tolerant species and ruderals. On the other hand, the use of the morpho-physiological model requires a large number of field measurements, which makes it difficult to use this model to allocate CSR strategies for a large number of species.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12298-021-00973-9.