Root trait variation along a sub-arctic tundra elevational gradient

Elevational gradients are useful for predicting how plant communities respond to global warming, because communities at lower elevations experience warmer temperatures. Fine root traits and root trait variation could play an important role in determining plant community responses to warming in cold-climate ecosystems where a large proportion of plant biomass is allocated belowground. Here, we investigated the effects of elevation-associated temperature change on twelve chemical and morphological fine root traits of plant species and plant communities in a Swedish subarctic tundra. We also assessed the relative contributions of plant species turnover and intraspecific variation to the total amount of community-level root trait variation explained by elevation. Several root traits, both at the species and whole community levels, had significant linear or quadratic relationships with elevation, but the direction and strength of these relationships varied among traits and plant species. Further, we found no support for a unidirectional change from more acquisitive root trait values at the lower elevations towards trait values associated with greater nutrient conservation at the higher elevations, either at the species or community level. On the other hand, root trait coefficients of variation at the community level increased with elevation for several root traits. Further, for a large proportion of the community-level traits we found that intraspecific variation was relatively more important than species turnover, meaning that trait plasticity is important for driving community-level trait responses to environmental factors in this tundra system. Our findings indicate that with progressing global warming, intraspecific trait variation may drive plant community composition but this may not necessarily lead to shifts in root resource-acquisition strategy for all species

Root traits and soil micro-organisms as drivers of plant-soil feedbacks within the sub-arctic tundra meadow

Plant-soil feedback (PSF) results from the influence of plants on the composition and abundance of various taxa and functional groups of soil micro-organisms, and their reciprocal effects on the plants. However, little is understood about the importance of fine root traits and root economic strategies in moderating microbial-driven PSF. We examined the relationships between PSF and 11 chemical and morphological root traits from 18 sub-arctic meadow plant species, as well as the soil microbial community composition which we characterized using phospholipid fatty acids (PLFAs) and high-throughput sequencing. We also investigated the importance of the root economics spectrum in influencing PSF, because it indicates plant below-ground economic strategies via trade-offs between resource acquisition and conservation. When we considered the entire root economics spectrum, we found that PSFs were more negative when root trait values were more acquisitive across the 18 species. In addition, PSF was more negative when values of root nitrogen content and root forks per root length were higher, and more positive when root dry matter content was higher. We additionally identified two fungal orders that were negatively related to PSF. However, we found no evidence that root traits influenced PSF through its relationship with these fungal orders. Synthesis. Our results provide evidence that for some fine root traits, the root economics spectrum and some fungal orders have an important role in influencing PSF. By investigating the roles of soil micro-organisms and fine root traits in driving PSF, this study enables us to better understand root trait-microbial linkages across species and therefore offers new insights about the mechanisms that underpin PSFs and ultimately plant community assembly

Root trait-microbial relationships across tundra plant species

Fine roots, and their functional traits, influence associated rhizosphere microorganisms via root exudation and root litter quality. However, little information is known about their relationship with rhizosphere microbial taxa and functional guilds.We investigated the relationships of 11 fine root traits of 20 sub-arctic tundra meadow plant species and soil microbial community composition, using phospholipid fatty acids (PLFAs) and high-throughput sequencing. We primarily focused on the root economics spectrum, as it provides a useful framework to examine plant strategies by integrating the co-ordination of belowground root traits along a resource acquisition-conservation trade-off axis.We found that the chemical axis of the fine root economics spectrum was positively related to fungal to bacterial ratios, but negatively to Gram-positive to Gram-negative bacterial ratios. However, this spectrum was unrelated to the relative abundance of functional guilds of soil fungi. Nevertheless, the relative abundance of arbuscular mycorrhizal fungi was positively correlated to root carbon content, but negatively to the numbers of root forks per root length.Our results suggest that the fine root economics spectrum is important for predicting broader groups of soil microorganisms (i.e. fungi and bacteria), while individual root traits may be more important for predicting soil microbial taxa and functional guilds

Plant-microbial linkages underpin carbon sequestration in contrasting mountain tundra vegetation types

Tundra ecosystems hold large stocks of soil organic matter (SOM), likely due to low temperatures limiting rates of microbial SOM decomposition more than those of SOM accumulation from plant primary productivity and microbial necromass inputs. Here we test the hypotheses that distinct tundra vegetation types and their carbon supply to characteristic rhizosphere microbes determine SOM cycling independent of temperature. In the subarctic Scandes, we used a three-way factorial design with paired heath and meadow vegetation at each of two elevations, and with each combination of vegetation type and elevation subjected during one growing season to either ambient light (i.e., ambient plant productivity), or 95% shading (i.e., reduced plant productivity). We assessed potential above-and belowground ecosystem linkages by uni-and multivariate analyses of variance, and structural equation modelling. We observed direct coupling between tundra vegetation type and microbial community composition and function, which underpinned the ecosystem's potential for SOM storage. Greater primary productivity at low elevation and ambient light supported higher microbial biomass and nitrogen immobilisation, with lower microbial mass-specific enzymatic activity and SOM humification. Congruently, larger SOM at lower elevation and in heath sustained fungal-dominated microbial communities, which were less substrate-limited, and invested less into enzymatic SOM mineralisation, owing to a greater carbon-use efficiency (CUE). Our results highlight the importance of tundra plant community characteristics (i.e., productivity and vegetation type), via their effects on soil microbial community size, structure and physiology, as essential drivers of SOM turnover. The here documented concerted patterns in above-and belowground ecosystem functioning is strongly supportive of using plant community characteristics as surrogates for assessing tundra carbon storage potential and its evolution under climate and vegetation changes

The biological controls of soil carbon accumulation following wildfire and harvest in boreal forests: A review

Boreal forests are frequently subjected to disturbances, including wildfire and clear-cutting. While these disturbances can cause soil carbon (C) losses, the long-term accumulation dynamics of soil C stocks during subsequent stand development is controlled by biological processes related to the balance of net primary production (NPP) and outputs via heterotrophic respiration and leaching, many of which remain poorly understood. We review the biological processes suggested to influence soil C accumulation in boreal forests. Our review indicates that median C accumulation rates following wildfire and clear-cutting are similar (0.15 and 0.20 Mg ha(-1) year(-1), respectively), however, variation between studies is extremely high. Further, while many individual studies show linear increases in soil C stocks through time after disturbance, there are indications that C stock recovery is fastest early to mid-succession (e.g. 15-80 years) and then slows as forests mature (e.g. >100 years). We indicate that the rapid build-up of soil C in younger stands appears not only driven by higher plant production, but also by a high rate of mycorrhizal hyphal production, and mycorrhizal suppression of saprotrophs. As stands mature, the balance between reductions in plant and mycorrhizal production, increasing plant litter recalcitrance, and ectomycorrhizal decomposers and saprotrophs have been highlighted as key controls on soil C accumulation rates. While some of these controls appear well understood (e.g. temporal patterns in NPP, changes in aboveground litter quality), many others remain research frontiers. Notably, very little data exists describing and comparing successional patterns of root production, mycorrhizal functional traits, mycorrhizal-saprotroph interactions, or C outputs via heterotrophic respiration and dissolved organic C following different disturbances. We argue that these less frequently described controls require attention, as they will be key not only for understanding ecosystem C balances, but also for representing these dynamics more accurately in soil organic C and Earth system models

Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network

A growing body of work examines the direct and indirect effects of climate change on ecosystems, typically by using manipulative experiments at a single site or performing meta-analyses across many independent experiments. However, results from single-site studies tend to have limited generality. Although meta-analytic approaches can help overcome this by exploring trends across sites, the inherent limitations in combining disparate datasets from independent approaches remain a major challenge. In this paper, we present a globally distributed experimental network that can be used to disentangle the direct and indirect effects of climate change. We discuss how natural gradients, experimental approaches, and statistical techniques can be combined to best inform predictions about responses to climate change, and we present a globally distributed experiment that utilizes natural environmental gradients to better understand long-term community and ecosystem responses to environmental change. The warming and (species) removal in mountains (WaRM) network employs experimental warming and plant species removals at high- and low-elevation sites in a factorial design to examine the combined and relative effects of climatic warming and the loss of dominant species on community structure and ecosystem function, both above- and belowground. The experimental design of the network allows for increasingly common statistical approaches to further elucidate the direct and indirect effects of warming. We argue that combining ecological observations and experiments along gradients is a powerful approach to make stronger predictions of how ecosystems will function in a warming world as species are lost, or gained, in local communities

Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network

A growing body of work examines the direct and indirect effects of climate change on ecosystems, typically by using manipulative experiments at a single site or performing meta-analyses across many independent experiments. However, results from single-site studies tend to have limited generality. Although meta-analytic approaches can help overcome this by exploring trends across sites, the inherent limitations in combining disparate datasets from independent approaches remain a major challenge. In this paper, we present a globally distributed experimental network that can be used to disentangle the direct and indirect effects of climate change. We discuss how natural gradients, experimental approaches, and statistical techniques can be combined to best inform predictions about responses to climate change, and we present a globally distributed experiment that utilizes natural environmental gradients to better understand long-term community and ecosystem responses to environmental change. The warming and (species) removal in mountains (WaRM) network employs experimental warming and plant species removals at high- and low-elevation sites in a factorial design to examine the combined and relative effects of climatic warming and the loss of dominant species on community structure and ecosystem function, both above- and belowground. The experimental design of the network allows for increasingly common statistical approaches to further elucidate the direct and indirect effects of warming. We argue that combining ecological observations and experiments along gradients is a powerful approach to make stronger predictions of how ecosystems will function in a warming world as species are lost, or gained, in local communities

Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis.

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis

Circum-Arctic distribution of chemical anti-herbivore compounds suggests biome-wide trade-off in defence strategies in Arctic shrubs

Spatial variation in plant chemical defence towards herbivores can help us understand variation in herbivore top-down control of shrubs in the Arctic and possibly also shrub responses to global warming. Less defended, non-resinous shrubs could be more influenced by herbivores than more defended, resinous shrubs. However, sparse field measurements limit our current understanding of how much of the circum-Arctic variation in defence compounds is explained by taxa or defence functional groups (resinous/non-resinous). We measured circum-Arctic chemical defence and leaf digestibility in resinous (Betula glandulosa, B. nana ssp. exilis) and non-resinous (B. nana ssp. nana, B. pumila) shrub birches to see how they vary among and within taxa and functional groups. Using liquid chromatography-mass spectrometry (LC-MS) metabolomic analyses and in vitro leaf digestibility via incubation in cattle rumen fluid, we analysed defence composition and leaf digestibility in 128 samples from 44 tundra locations. We found biogeographical patterns in anti-herbivore defence where mean leaf triterpene concentrations and twig resin gland density were greater in resinous taxa and mean concentrations of condensing tannins were greater in non-resinous taxa. This indicates a biome-wide trade-off between triterpene- or tannin-dominated defences. However, we also found variations in chemical defence composition and resin gland density both within and among functional groups (resinous/non-resinous) and taxa, suggesting these categorisations only partly predict chemical herbivore defence. Complex tannins were the only defence compounds negatively related to in vitro digestibility, identifying this previously neglected tannin group as having a potential key role in birch anti-herbivore defence. We conclude that circum-Arctic variation in birch anti-herbivore defence can be partly derived from biogeographical distributions of birch taxa, although our detailed mapping of plant defence provides more information on this variation and can be used for better predictions of herbivore effects on Arctic vegetation

Circum-Arctic distribution of chemical anti-herbivore compounds suggests biome-wide trade-off in defence strategies in Arctic shrubs

Spatial variation in plant chemical defence towards herbivores can help us understand variation in herbivore top-down control of shrubs in the Arctic and possibly also shrub responses to global warming. Less defended, non-resinous shrubs could be more influenced by herbivores than more defended, resinous shrubs. However, sparse field measurements limit our current understanding of how much of the circum-Arctic variation in defence compounds is explained by taxa or defence functional groups (resinous/non-resinous). We measured circum-Arctic chemical defence and leaf digestibility in resinous (Betula glandulosa, B. nana ssp. exilis) and non-resinous (B. nana ssp. nana, B. pumila) shrub birches to see how they vary among and within taxa and functional groups. Using liquid chromatography-mass spectrometry (LC-MS) metabolomic analyses and in vitro leaf digestibility via incubation in cattle rumen fluid, we analysed defence composition and leaf digestibility in 128 samples from 44 tundra locations. We found biogeographical patterns in anti-herbivore defence where mean leaf triterpene concentrations and twig resin gland density were greater in resinous taxa and mean concentrations of condensing tannins were greater in non-resinous taxa. This indicates a biome-wide trade-off between triterpene- or tannin-dominated defences. However, we also found variations in chemical defence composition and resin gland density both within and among functional groups (resinous/non-resinous) and taxa, suggesting these categorisations only partly predict chemical herbivore defence. Complex tannins were the only defence compounds negatively related to in vitro digestibility, identifying this previously neglected tannin group as having a potential key role in birch anti-herbivore defence. We conclude that circum-Arctic variation in birch anti-herbivore defence can be partly derived from biogeographical distributions of birch taxa, although our detailed mapping of plant defence provides more information on this variation and can be used for better predictions of herbivore effects on Arctic vegetation.Peer reviewe