Arctic ecosystems are increasingly exposed to extreme climatic events throughout the year, which can affect species performance. Cryptogams (bryophytes and lichens) provide important ecosystem ...services in polar ecosystems but may be physiologically affected or killed by extreme events. Through field and laboratory manipulations, we compared physiological responses of seven dominant sub‐Arctic cryptogams (three bryophytes, four lichens) to single events and factorial combinations of mid‐winter heatwave (6°C for 7 days), re‐freezing, snow removal and summer nitrogen addition. We aimed to identify which mosses and lichens are vulnerable to these abiotic extremes and if combinations would exacerbate physiological responses. Combinations of extremes resulted in stronger species responses but included idiosyncratic species‐specific responses. Species that remained dormant during winter (March), irrespective of extremes, showed little physiological response during summer (August). However, winter physiological activity, and response to winter extremes, was not consistently associated with summer physiological impacts. Winter extremes affect cryptogam physiology, but summer responses appear mild, and lichens affect the photobiont more than the mycobiont. Accounting for Arctic cryptogam response to multiple climatic extremes in ecosystem functioning and modelling will require a better understanding of their winter eco‐physiology and repair capabilities.
Atmospheric nitrogen (N) deposition is a global and increasing threat to biodiversity and ecosystem function. Much of our current understanding of N deposition impacts comes from field manipulation ...studies, although interpretation may need caution where simulations of N deposition (in terms of dose, application rate and N form) have limited realism. Here, we review responses to simulated N deposition from the UKREATE network, a group of nine experimental sites across the UK in a diversity of heathland, grassland, bog and dune ecosystems which include studies with a high level of realism and where many are also the longest running globally on their ecosystem type. Clear responses were seen across the sites with the greatest sensitivity shown in cover and species richness of bryophytes and lichens. Productivity was also increased at sites where N was the limiting nutrient, while flowering also showed high sensitivity, with increases and declines seen in dominant shrub and forb species, respectively. Critically, these parameters were responsive to some of the lowest additional loadings of N (7.7–10 kg ha−1 yr−1) showing potential for impacts by deposition rates seen in even remote and ‘unpolluted’ regions of Europe. Other parameters were less sensitive, but nevertheless showed response to higher doses. These included increases in soil %N and ‘plant available’ KCl extractable N, N cycling rates and acid–base status. Furthermore, an analysis of accumulated dose that quantified response against the total N input over time suggested that N impacts can ‘build up’ within an ecosystem such that even relatively low N deposition rates can result in ecological responses if continued for long enough. Given the responses have important implications for ecosystem structure, function, and recovery from N loading, the clear evidence for impacts at relatively low N deposition rates across a wide range of habitats is of considerable concern.
Arctic tundra ecosystems are a major source of methane (CH4), the variability of which is affected by local environmental and climatic factors, such as water table depth, microtopography, and the ...spatial heterogeneity of the vegetation communities present. There is a disconnect between the measurement scales for CH4 fluxes, which can be measured with chambers at one-meter resolution and eddy covariance towers at 100–1000 m, whereas model estimates are typically made at the ~100 km scale. Therefore, it is critical to upscale site level measurements to the larger scale for model comparison. As vegetation has a critical role in explaining the variability of CH4 fluxes across the tundra landscape, we tested whether remotely-sensed maps of vegetation could be used to upscale fluxes to larger scales. The objectives of this study are to compare four different methods for mapping and two methods for upscaling plot-level CH4 emissions to the measurements from EC towers. We show that linear discriminant analysis (LDA) provides the most accurate representation of the tundra vegetation within the EC tower footprints (classification accuracies of between 65% and 88%). The upscaled CH4 emissions using the areal fraction of the vegetation communities showed a positive correlation (between 0.57 and 0.81) with EC tower measurements, irrespective of the mapping method. The area-weighted footprint model outperformed the simple area-weighted method, achieving a correlation of 0.88 when using the vegetation map produced with the LDA classifier. These results suggest that the high spatial heterogeneity of the tundra vegetation has a strong impact on the flux, and variation indicates the potential impact of environmental or climatic parameters on the fluxes. Nonetheless, assimilating remotely-sensed vegetation maps of tundra in a footprint model was successful in upscaling fluxes across scales.
Elevated CO
2
(eCO
2
) can stimulate plant productivity and increase carbon (C) input to soils, but nutrient limitation restricts productivity. Despite phosphorus (P)-limited ecosystems increasing ...globally, it is unknown how nutrient cycling, particularly soil microbial extra cellular enzyme activity (EEA), will respond to eCO
2
in such ecosystems. Long-term nutrient manipulation plots from adjacent P-limited acidic and limestone grasslands were exposed to eCO
2
(600 ppm) provided by a mini-Free Air CO
2
Enrichment system. P-limitation was alleviated (35 kg-P ha
−1
y
−1
(P35)), exacerbated (35 kg-N ha
−1
y
−1
(N35), 140 kg-N ha
−1
y
−1
(N140)), or maintained (control (P0N0)) for > 20 years. We measured EEAs of C-, N- and P-cycling enzymes (1,4-β-glucosidase, cellobiohydrolase, N-acetyl β-D-glucosaminidase, leucine aminopeptidase, and acid phosphatase) and compared C:N:P cycling enzyme ratios using a vector analysis. Potential acid phosphatase activity doubled under N additions relative to P0N0 and P35 treatments. Vector analysis revealed reduced C-cycling investment and increased P-cycling investment under eCO
2
. Vector angle significantly increased with P-limitation (P35 < P0N0 < N35 < N140) indicating relatively greater investment in P-cycling enzymes. The limestone grassland was more C limited than the acidic grassland, characterised by increased vector length, C:N and C:P enzyme ratios. The absence of interactions between grassland type and eCO
2
or nutrient treatment for all enzyme indicators signaled consistent responses to changing P-limitation and eCO
2
in both grasslands. Our findings suggest that eCO
2
reduces C limitation, allowing increased investment in P- and N-cycle enzymes with implications for rates of nutrient cycling, potentially alleviating nutrient limitation of ecosystem productivity under eCO
2
.
Graphic abstract
Interactions among species determine local‐scale diversity, but local interactions are thought to have minor effects at larger scales. However, quantitative comparisons of the importance of biotic ...interactions relative to other drivers are rarely made at larger scales. Using a data set spanning 78 sites and five continents, we assessed the relative importance of biotic interactions and climate in determining plant diversity in alpine ecosystems dominated by nurse‐plant cushion species. Climate variables related with water balance showed the highest correlation with richness at the global scale. Strikingly, although the effect of cushion species on diversity was lower than that of climate, its contribution was still substantial. In particular, cushion species enhanced species richness more in systems with inherently impoverished local diversity. Nurse species appear to act as a ‘safety net’ sustaining diversity under harsh conditions, demonstrating that climate and species interactions should be integrated when predicting future biodiversity effects of climate change.
The Arctic is already experiencing changes in plant community composition, so understanding the contribution of different vegetation components to carbon (C) cycling is essential in order to ...accurately quantify ecosystem C balance. Mosses contribute substantially to biomass, but their impact on carbon use efficiency (CUE) – the proportion of gross primary productivity (GPP) incorporated into growth – and aboveground versus belowground C partitioning is poorly known.
We used 13C pulse-labelling to trace assimilated C in mosses (Sphagnum sect. Acutifolia and Pleurozium schreberi) and in dwarf shrub–P. schreberi vegetation in sub-Arctic Finland. Based on 13C pools and fluxes, we quantified the contribution ofmosses to GPP, CUE and partitioning.
Mosses incorporated 20 ± 9% of total ecosystem GPP into biomass. CUE of Sphagnum was 68–71%, that of P. schreberi was 62–81% and that of dwarf shrub–P. schreberi vegetation was 58–74%. Incorporation of C belowground was 10 ± 2% of GPP, while vascular plants alone incorporated 15 ± 4% of their fixed C belowground.
We have demonstrated that mosses strongly influence C uptake and retention in Arctic dwarf shrub vegetation. They increase CUE, and the fraction of GPP partitioned above-ground. Arctic C models must include mosses to accurately represent ecosystem C dynamics.
Permafrost soils store huge amounts of organic carbon, which could be released if climate change promotes thaw. Currently, modelling studies predict that thaw in boreal regions is mainly sensitive to ...warming, rather than changes in precipitation or vegetation cover. We evaluate this conclusion for North American boreal forests using a detailed process-based model parameterised and validated on field measurements. We show that soil thermal regimes for dominant forest types are controlled strongly by soil moisture and thus the balance between evapotranspiration and precipitation. Under dense canopy cover, high evapotranspiration means a 30% increase in precipitation causes less thaw than a 1 °C increase in temperature. However, disturbance to vegetation promotes greater thaw through reduced evapotranspiration, which results in wetter, more thermally conductive soils. In such disturbed forests, increases in precipitation rival warming as a direct driver of thaw, with a 30% increase in precipitation at current temperatures causing more thaw than 2 °C of warming. We find striking non-linear interactive effects on thaw between rising precipitation and loss of leaf area, which are of concern given projections of greater precipitation and disturbance in boreal forests. Inclusion of robust vegetation-hydrological feedbacks in global models is therefore critical for accurately predicting permafrost dynamics; thaw cannot be considered to be controlled solely by rising temperatures.
The Arctic is currently undergoing intense changes in climate; vegetation composition and productivity are expected to respond to such changes. To understand the impacts of climate change on the ...function of Arctic tundra ecosystems within the global carbon cycle, it is crucial to improve the understanding of vegetation distribution and heterogeneity at multiple scales. Information detailing the fine-scale spatial distribution of tundra communities provided by high resolution vegetation mapping, is needed to understand the relative contributions of and relationships between single vegetation community measurements of greenhouse gas fluxes (e.g., ~1 m chamber flux) and those encompassing multiple vegetation communities (e.g., ~300 m eddy covariance measurements). The objectives of this study were: (1) to determine whether dominant Arctic tundra vegetation communities found in different locations are spectrally distinct and distinguishable using field spectroscopy methods; and (2) to test which combination of raw reflectance and vegetation indices retrieved from field and satellite data resulted in accurate vegetation maps and whether these were transferable across locations to develop a systematic method to map dominant vegetation communities within larger eddy covariance tower footprints distributed along a 300 km transect in northern Alaska. We showed vegetation community separability primarily in the 450-510 nm, 630-690 nm and 705-745 nm regions of the spectrum with the field spectroscopy data. This is line with the different traits of these arctic tundra communities, with the drier, often non-vascular plant dominated communities having much higher reflectance in the 450-510 nm and 630-690 nm regions due to the lack of photosynthetic material, whereas the low reflectance values of the vascular plant dominated communities highlight the strong light absorption found here. High classification accuracies of 92% to 96% were achieved using linear discriminant analysis with raw and rescaled spectroscopy reflectance data and derived vegetation indices. However, lower classification accuracies (~70%) resulted when using the coarser 2.0 m WorldView-2 data inputs. The results from this study suggest that tundra vegetation communities are separable using plot-level spectroscopy with hand-held sensors. These results also show that tundra vegetation mapping can be scaled from the plot level (<1 m) to patch level (<500 m) using spectroscopy data rescaled to match the wavebands of the multispectral satellite remote sensing. We find that developing a consistent method for classification of vegetation communities across the flux tower sites is a challenging process, given the spatial variability in vegetation communities and the need for detailed vegetation survey data for training and validating classification algorithms. This study highlights the benefits of using fine-scale field spectroscopy measurements to obtain tundra vegetation classifications for landscape analyses and use in carbon flux scaling studies. Improved understanding of tundra vegetation distributions will also provide necessary insight into the ecological processes driving plant community assemblages in Arctic environments.
Green roof substrate is arguably the most important element of a green roof, providing water, nutrients and physical support to plants. Despite this there has been a lack of research into the role ...that different substrate components have on green roof plant growth and physiological performance.
To address this, we assessed the importance of three green roof substrate components (organic matter type, brick particle size and water absorbent additive) for plant growth and plant physiological performance. Lolium perenne (Ryegrass) was grown in eight substrates in a controlled greenhouse environment with a factorial design in composition of (i) small or large brick, (ii) conifer bark or green waste compost organic matter, and (iii) presence/absence of polyacrylamide water absorbent gel (‘SwellGel™’).
We found that large brick substrates had a lower water holding capacity than small brick (−35%), which led to decreased shoot growth (−17%) and increased root:shoot ratio (+16%). Green waste compost increased shoot and root growth (+32% and +13%) shoot nitrogen concentration and chlorophyll content (20% and 57%), and decreased root:shoot ratio (−15%) compared to bark. The addition of swell gel increased substrate water holding capacity (+24%), which increased shoot growth (+8%). Total evapotranspiration (a proxy for potential cooling) was increased by greater shoot biomass and substrate water holding capacity. Overall, this study provides one of the first quantitative assessments of the relative importance of commonly used green roof substrate components. It is clear that substrate composition should be considered carefully when designing green roofs, and substrate composition can be tailored for green roof service provision.
Parasitic plants have major impacts on plant community structure through their direct negative influence on host productivity and competitive ability. However, the possibility that these parasites ...may also have indirect impacts on community structure (via the mechanism of nutrient-rich litter input) while long hypothesized, has remained unsupported until now.
Using the hemiparasite Rhinanthus minor, we established experimental grassland mesocosms to quantify the impacts of Rhinanthus litter and parasitism across two soil fertility levels. We measured the biomass and tissue nutrient concentration of three functional groups within these communities to determine their physiological response to resource abstraction and litter input by the parasite.
We show that Rhinanthus alters the biomass and nutrient status of co-occurring plants with contrasting effects on different functional groups via the mechanism of nutrient-rich litter input. Critically, in the case of grass and total community biomass, this partially negates biomass reductions caused directly by parasitism.
This demonstrates that the influence of parasitic plant litter on plant community structure can be of equal importance to the much-reported direct impacts of parasitism. We must consider both positive indirect (litter) and negative direct (parasitism) impacts of parasitic plants to understand their role in structuring plant communities.
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