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Earthworms, as detritivores, play a significant role in breaking down soil organic carbon (SOC). The introduction of non-native earthworms to arctic ecosystems has, therefore, raised concerns about the potential impact they may have on one of the world's largest SOC reservoirs. Earthworms could also have considerable effects on plant productivity, and the lack of experimental studies quantifying their impact on carbon (C) reservoirs in both soil and plants makes it difficult to predict the effect of earthworms on ecosystem C storage. Here we experimentally tested how earthworms known to be non-native to arctic ecosystems (Aporrectodea spp. and Lumbricus spp.) affect C reservoirs in soil and plants (above and belowground separately) in two common tundra vegetation types (heath and meadow). Earthworms lowered the mean SOC pool and substantially altered SOC quality in meadow soils by increasing the proportion of aromatic-C compounds. Simultaneously, earthworms increased the C pool stored in plant biomass, which counteracted earthworm-induced SOC losses in meadow ecosystems. A positive earthworm effect on belowground biomass in heath soil facilitated a net ecosystem uptake of ∼0.84 kg C m−2 over the 4-year study period. The higher C uptake into plant biomass in the heath resulted in a notable increase of SOC but lower δ13C values, likely because of recently captured C being sourced from roots or litter. Our observations of vegetation-specific feedbacks between plants, earthworms, and soils advance our understanding of non-native earthworms' impact on SOC dynamics and C budgets in high-latitude ecosystems.

The below-ground growing season often extends beyond the above-ground growing season in tundra ecosystems and as the climate warms, shifts in growing seasons are expected. However, we do not yet know to what extent, when and where asynchrony in above- and below-ground phenology occurs and whether variation is driven by local vegetation communities or spatial variation in microclimate. Here, we combined above- and below-ground plant phenology metrics to compare the relative timings and magnitudes of leaf and fine-root growth and senescence across microclimates and plant communities at five sites across the Arctic and alpine tundra biome. We observed asynchronous growth between above- and below-ground plant tissue, with the below-ground season extending up to 74% (~56 days) beyond the onset of above-ground leaf senescence. Plant community type, rather than microclimate, was a key factor controlling the timing, productivity, and growth rates of fine roots, with graminoid roots exhibiting a distinct ‘pulse’ of growth later into the growing season than shrub roots. Our findings indicate the potential of vegetation change to influence below-ground carbon storage as the climate warms and roots remain active in unfrozen soils for longer. Taken together, our findings of increased root growth in soils that remain thawed later into the growing season, in combination with ongoing tundra vegetation change including increased shrub and graminoid abundance, indicate increased below-ground productivity and altered carbon cycling in the tundra biome.

Human-mediated dispersal of non-native earthworms can cause substantial changes to the functioning and composition of ecosystems previously earthworm-free. Some of these earthworm species have the potential to “geoengineer” soils and increase plant nitrogen (N) uptake. Yet the possible consequences of increased plant N concentrations on rodent grazing remains poorly understood. In this study, we present findings from a common garden experiment with two tundra communities, meadow (forb dominated) and heath (shrub dominated), half of them subjected to 4 years of earthworm presence (Lumbricus spp. and Aporrectodea spp.). Within four summers, our earthworm treatment changed plant community composition by increasing graminoid density by, on average, 94% in the heath vegetation and by 49% in the meadow. Rodent winter grazing was more intense on plants growing in soils with earthworms, an effect that coincided with higher N concentrations in plants, indicating a higher palatability. Even though earthworms reduced soil moisture, plant community productivity, as indicated by vegetation greenness (normalized difference vegetation index), was not negatively impacted. We conclude that earthworm-induced changes in plant composition and trophic interactions may fundamentally alter the functioning of tundra ecosystems.

Targeted removal experiments are a powerful tool to assess the effects of plant species or (functional) groups on ecosystem functions. However, removing plant biomass in itself can bias the observed responses. This bias is commonly addressed by waiting until ecosystem recovery, but this is inherently based on unverified proxies or anecdotal evidence. Statistical control methods are efficient, but restricted in scope by underlying assumptions.

We propose accounting for such biases within the experimental design, using a gradient of biomass removal controls. We demonstrate the relevance of this design by presenting (1) conceptual examples of suspected biases and (2) how to observe and control for these biases.

Using data from a mycorrhizal association-based removal experiment, we show that ignoring biomass removal biases (including by assuming ecosystem recovery) can lead to incorrect, or even contrary conclusions (e.g. false positive and false negative). Our gradient design can prevent such incorrect interpretations, regardless of whether aboveground biomass has fully recovered.

Our approach provides more objective and quantitative insights, independently assessed for each variable, than using a proxy to assume ecosystem recovery. Our approach circumvents the strict statistical assumptions of, for example, ANCOVA and thus offers greater flexibility in data analysis.

• Seasonal dynamics of root growth play an important role in large-scale ecosystem processes; they are largely governed by growth regulatory compounds and influenced by environmental conditions. Yet, our knowledge about physiological drivers of root growth is mostly limited to laboratory-based studies on model plant species.
• We sampled root tips of Eriophorum vaginatum and analyzed their auxin concentrations and meristem lengths biweekly over a growing season in situ in a subarctic peatland, both in surface soil and at the permafrost thawfront.
• Auxin concentrations were almost five times higher in surface than in thawfront soils and increased over the season, especially at the thawfront. Surprisingly, meristem length showed an opposite pattern and was almost double in thawfront compared with surface soils. Meristem length increased from peak to late season in the surface soils but decreased at the thawfront.
• Our study of in situ seasonal dynamics in root physiological parameters illustrates the potential for physiological methods to be applied in ecological studies and emphasizes the importance of in situ measurements. The strong effect of root location and the unexpected opposite patterns of meristem length and auxin concentrations likely show that auxin actively governs root growth to ensure a high potential for nutrient uptake at the thawfront.

Vegetation changes in a warming Arctic may affect plant-associated soil microbial communities with possible consequences for the biogeochemical cycling of carbon (C) and nitrogen (N). In a sub-arctic tundra heath, we factorially removed plant species with ecto- and ericoid mycorrhizal associations. After two years, we explored how mycorrhizal type-specific plant removal influences microbial communities, soil and microbial C and N pools, and extracellular enzymatic activities. Removal of ecto- and ericoid mycorrhizal plants did not change the soil fungal or bacterial community composition or their extracellular enzyme activities. However, ericoid plant removal decreased microbial C:N ratio, suggesting a stoichiometric effect decoupled from microbial community composition. In other words, microbial communities appear to show initial plasticity in response to major changes in tundra vegetation. This highlights the importance of longer-term perspectives when investigating the effects of vegetation changes on biogeochemical processes in Arctic ecosystems.

The rewetting of formerly drained peatlands can help to counteract climate change through the reduction of CO2 emissions. However, this can lead to resuming CH4 emissions due to changes in the microbiome, favoring CH4-producing archaea. How plants, hydrology and microbiomes interact as ultimate determinants of CH4 dynamics is still poorly understood. Using a mesocosm approach, we studied peat microbiomes, below-ground root biomass and CH4 fluxes with three different water level regimes (stable high, stable low and fluctuating) and four different plant communities (bare peat, Carex rostrata, Juncus inflexus and their mixture) over the course of one growing season. A significant difference in microbiome composition was found between mesocosms with and without plants, while the difference between plant species identity or water regimes was rather weak. A significant difference was also found between the upper and lower peat, with the difference increasing as plants grew. By the end of the growing season, the methanogen relative abundance was higher in the sub-soil layer, as well as in the bare peat and C. rostrata pots, as compared to J. inflexus or mixture pots. This was inversely linked to the larger root area of J. inflexus. The root area also negatively correlated with CH4 fluxes which positively correlated with the relative abundance of methanogens. Despite the absence or low abundance of methanotrophs in many samples, the integration of methanotroph abundance improved the quality of the correlation with CH4 fluxes, and methanogens and methanotrophs together determined CH4 fluxes in a structural equation model. However, water regime showed no significant impact on plant roots and methanogens, and consequently, on CH4 fluxes. This study showed that plant roots determined the microbiome composition and, in particular, the relative abundance of methanogens and methanotrophs, which, in interaction, drove the CH4 fluxes.

The distribution of roots throughout the soil drives depth-dependent plant–soil interactions and ecosystem processes, particularly in arctic tundra where plant biomass, is predominantly belowground. Vegetation is usually classified from aboveground, but it is unclear whether such classifications are suitable to estimate belowground attributes and their consequences, such as rooting depth distribution and its influence on carbon cycling. We performed a meta-analysis of 55 published arctic rooting depth profiles, testing for differences both between distributions based on aboveground vegetation types (Graminoid, Wetland, Erect-shrub, and Prostrate-shrub tundra) and between ‘Root Profile Types’ for which we defined three representative and contrasting clusters. We further analyzed potential impacts of these different rooting depth distributions on rhizosphere priming-induced carbon losses from tundra soils. Rooting depth distribution hardly differed between aboveground vegetation types but varied between Root Profile Types. Accordingly, modelled priming-induced carbon emissions were similar between aboveground vegetation types when they were applied to the entire tundra, but ranged from 7.2 to 17.6 Pg C cumulative emissions until 2100 between individual Root Profile Types. Variations in rooting depth distribution are important for the circumpolar tundra carbon-climate feedback but can currently not be inferred adequately from aboveground vegetation type classifications.

Plant roots influence many ecological and biogeochemical processes, such as carbon, water and nutrient cycling. Because of difficult accessibility, knowledge on plant root growth dynamics in field conditions, however, is fragmentary at best. Minirhizotrons, i.e. transparent tubes placed in the substrate into which specialized cameras or circular scanners are inserted, facilitate the capture of high-resolution images of root dynamics at the soil-tube interface with little to no disturbance after the initial installation. Their use, especially in field studies with multiple species and heterogeneous substrates, though, is limited by the amount of work that subsequent manual tracing of roots in the images requires. Furthermore, the reproducibility and objectivity of manual root detection is questionable. Here, we use a Convolutional Neural Network (CNN) for the automatic detection of roots in minirhizotron images and compare the performance of our RootDetector with human analysts with different levels of expertise. Our minirhizotron data come from various wetlands on organic soils, i.e. highly heterogeneous substrates consisting of dead plant material, often times mainly roots, in various degrees of decomposition. This may be seen as one of the most challenging soil types for root segmentation in minirhizotron images. RootDetector showed a high capability to correctly segment root pixels in minirhizotron images from field observations (F1 = 0.6044; r2 compared to a human expert = 0.99). Reproducibility among humans, however, depended strongly on expertise level, with novices showing drastic variation among individual analysts and annotating on average more than 13-times higher root length/cm2 per image compared to expert analysts. CNNs such as RootDetector provide a reliable and efficient method for the detection of roots and root length in minirhizotron images even from challenging field conditions. Analyses with RootDetector thus save resources, are reproducible and objective, and are as accurate as manual analyses performed by human experts.