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.

Shrub expansion modulates belowground impacts of changing snow conditions in alpine grasslands.

Climate change is disproportionately impacting mountain ecosystems, leading to large reductions in winter snow cover, earlier spring snowmelt and widespread shrub expansion into alpine grasslands. Yet, the combined effects of shrub expansion and changing snow conditions on abiotic and biotic soil properties remains poorly understood. We used complementary field experiments to show that reduced snow cover and earlier snowmelt have effects on soil microbial communities and functioning that persist into summer. However, ericaceous shrub expansion modulates a number of these impacts and has stronger belowground effects than changing snow conditions. Ericaceous shrub expansion did not alter snow depth or snowmelt timing but did increase the abundance of ericoid mycorrhizal fungi and oligotrophic bacteria, which was linked to decreased soil respiration and nitrogen availability. Our findings suggest that changing winter snow conditions have cross-seasonal impacts on soil properties, but shifts in vegetation can modulate belowground effects of future alpine climate change.

Climate change alters temporal dynamics of alpine soil microbial functioning and biogeochemical cycling via earlier snowmelt.

Soil microbial communities regulate global biogeochemical cycles and respond rapidly to changing environmental conditions. However, understanding how soil microbial communities respond to climate change, and how this influences biogeochemical cycles, remains a major challenge. This is especially pertinent in alpine regions where climate change is taking place at double the rate of the global average, with large reductions in snow cover and earlier spring snowmelt expected as a consequence. Here, we show that spring snowmelt triggers an abrupt transition in the composition of soil microbial communities of alpine grassland that is closely linked to shifts in soil microbial functioning and biogeochemical pools and fluxes. Further, by experimentally manipulating snow cover we show that this abrupt seasonal transition in wide-ranging microbial and biogeochemical soil properties is advanced by earlier snowmelt. Preceding winter conditions did not change the processes that take place during snowmelt. Our findings emphasise the importance of seasonal dynamics for soil microbial communities and the biogeochemical cycles that they regulate. Moreover, our findings suggest that earlier spring snowmelt due to climate change will have far reaching consequences for microbial communities and nutrient cycling in these globally widespread alpine ecosystems.

Minimising methodological biases to improve the accuracy of partitioning soil respiration using natural abundance 13C.

RATIONALE: Microbial degradation of soil organic matter (heterotrophic respiration) is a key determinant of net ecosystem exchange of carbon, but it is difficult to measure because the CO2 efflux from the soil surface is derived not only from heterotrophic respiration, but also from plant root and rhizosphere respiration (autotrophic). Partitioning total CO2 efflux can be achieved using the different natural abundance stable isotope ratios (δ(13)C) of root and soil CO2. Successful partitioning requires very accurate measurements of total soil efflux δ(13)CO2 and the δ(13)CO2 of the autotrophic and heterotrophic sources, which typically differ by just 2-8‰. METHODS: In Scottish moorland and grass mesocosm studies we systematically tested some of the most commonly used techniques in order to identify and minimise methodological errors. Typical partitioning methods are to sample the total soil-surface CO2 efflux using a chamber, then to sample CO2 from incubated soil-free roots and root-free soil. We investigated the effect of collar depth on chamber measurements of surface efflux δ(13)CO2 and the effect of incubation time on estimates of end-member δ(13)CO2. RESULTS: (1) a 5 cm increase in collar depth affects the measurement of surface efflux δ(13)CO2 by -1.5‰ and there are fundamental inconsistencies between modelled and measured biases; (2) the heterotrophic δ(13)CO2 changes by up to -4‰ within minutes of sampling; we recommend using regression to estimate the in situ δ(13)CO2 values; (3) autotrophic δ(13)CO2 measurements are reliable if root CO2 is sampled within an hour of excavation; (4) correction factors should be used to account for instrument drift of up to 3‰ and concentration-dependent non-linearity of CRDS (cavity ringdown spectroscopy) analysis. CONCLUSIONS: Methodological biases can lead to large inaccuracies in partitioning estimates. The utility of stable isotope partitioning of soil CO2 efflux will be enhanced by consensus on the optimum measurement protocols and by minimising disturbance, particularly during chamber measurements.