Bryophytes dominate plant regulation of soil microclimate in alpine grasslands

publishedVersio

Explicitly modelling microtopography in permafrost landscapes in a land surface model (JULES vn5.4_microtopography)

Microtopography can be a key driver of heterogeneity in the ground thermal and hydrological regime of permafrost landscapes. In turn, this heterogeneity can influence plant communities, methane fluxes, and the initiation of abrupt thaw processes. Here we have implemented a two-tile representation of microtopography in JULES (the Joint UK Land Environment Simulator), where tiles are representative of repeating patterns of elevation difference. Tiles are coupled by lateral flows of water, heat, and redistribution of snow, and a surface water store is added to represent ponding. Simulations are performed of two Siberian polygon sites, (Samoylov and Kytalyk) and two Scandinavian palsa sites (Stordalen and Iškoras). The model represents the observed differences between greater snow depth in hollows vs. raised areas well. The model also improves soil moisture for hollows vs. the non-tiled configuration (“standard JULES”) though the raised tile remains drier than observed. The modelled differences in snow depths and soil moisture between tiles result in the lower tile soil temperatures being warmer for palsa sites, as in reality. However, when comparing the soil temperatures for July at 20 cm depth, the difference in temperature between tiles, or “temperature splitting”, is smaller than observed (3.2 vs. 5.5 ∘C). Polygons display small (0.2 ∘C) to zero temperature splitting, in agreement with observations. Consequently, methane fluxes are near identical (+0 % to 9 %) to those for standard JULES for polygons, although they can be greater than standard JULES for palsa sites (+10 % to 49 %). Through a sensitivity analysis we quantify the relative importance of model processes with respect to soil moisture and temperatures, identifying which parameters result in the greatest uncertainty in modelled temperature. Varying the palsa elevation between 0.5 and 3 m has little effect on modelled soil temperatures, showing that using only two tiles can still be a valid representation of sites with a range of palsa elevations. Mire saturation is heavily dependent on landscape-scale drainage. Lateral conductive fluxes, while small, reduce the temperature splitting by ∼ 1 ∘C and correspond to the order of observed lateral degradation rates in peat plateau regions, indicating possible application in an area-based thaw model

Intraspecific trait variability is a key feature underlying high Arctic plant community resistance to climate warming

In the high Arctic, plant community species composition generally responds slowly to climate warming, whereas less is known about the community functional trait responses and consequences for ecosystem functioning. The slow species turnover and large distribution ranges of many Arctic plant species suggest a significant role of intraspecific trait variability in functional responses to climate change. Here we compare taxonomic and functional community compositional responses to a long-term (17-year) warming experiment in Svalbard, Norway, replicated across three major high Arctic habitats shaped by topography and contrasting snow regimes. We observed taxonomic compositional changes in all plant communities over time. Still, responses to experimental warming were minor and most pronounced in the drier habitats with relatively early snowmelt timing and long growing seasons (Cassiope and Dryas heaths). The habitats were clearly separated in functional trait space, defined by 12 size- and leaf economics-related traits, primarily due to interspecific trait variation. Functional traits also responded to experimental warming, most prominently in the Dryas heath and mostly due to intraspecific trait variation. Leaf area and mass increased and leaf δ15N decreased in response to the warming treatment. Intraspecific trait variability ranged between 30% and 71% of the total trait variation, reflecting the functional resilience of those communities, dominated by long-lived plants, due to either phenotypic plasticity or genotypic variation, which most likely underlies the observed resistance of high Arctic vegetation to climate warming. We further explored the consequences of trait variability for ecosystem functioning by measuring peak season CO2 fluxes. Together, environmental, taxonomic, and functional trait variables explained a large proportion of the variation in net ecosystem exchange (NEE), which increased when intraspecific trait variation was accounted for. In contrast, even though ecosystem respiration and gross ecosystem production both increased in response to warming across habitats, they were mainly driven by the direct kinetic impacts of temperature on plant physiology and biochemical processes. Our study shows that long-term experimental warming has a modest but significant effect on plant community functional trait composition and suggests that intraspecific trait variability is a key feature underlying high Arctic ecosystem resistance to climate warming.publishedVersio

Multiscale mapping of plant functional groups and plant traits in the High Arctic using field spectroscopy, UAV imagery and Sentinel-2A data

The Arctic is warming twice as fast as the rest of the planet, leading to rapid changes in species composition and plant functional trait variation. Landscape-level maps of vegetation composition and trait distributions are required to expand spatially-limited plot studies, overcome sampling biases associated with the most accessible research areas, and create baselines from which to monitor environmental change. Unmanned aerial vehicles (UAVs) have emerged as a low-cost method to generate high-resolution imagery and bridge the gap between fine-scale field studies and lower resolution satellite analyses. Here we used field spectroscopy data (400-2500 nm) and UAV multispectral imagery to test spectral methods of species identification and plant water and chemistry retrieval near Longyearbyen, Svalbard. Using the field spectroscopy data and Random Forest analysis, we were able to distinguish eight common High Arctic plant tundra species with 74% accuracy. Using partial least squares regression (PLSR), we were able to predict corresponding water, nitrogen, phosphorus and C:N values (r (2) = 0.61-0.88, RMSEmean = 12%-64%). We developed analogous models using UAV imagery (five bands: Blue, Green, Red, Red Edge and Near-Infrared) and scaled up the results across a 450 m long nutrient gradient located underneath a seabird colony. At the UAV level, we were able to map three plant functional groups (mosses, graminoids and dwarf shrubs) at 72% accuracy and generate maps of plant chemistry. Our maps show a clear marine-derived fertility gradient, mediated by geomorphology. We used the UAV results to explore two methods of upscaling plant water content to the wider landscape using Sentinel-2A imagery. Our results are pertinent for high resolution, low-cost mapping of the Arctic.Peer reviewe

Climate–ecosystem modelling made easy: The Land Sites Platform

Dynamic Global Vegetation Models (DGVMs) provide a state-of-the-art process-based approach to study the complex interplay between vegetation and its physical environment. For example, they help to predict how terrestrial plants interact with climate, soils, disturbance and competition for resources. We argue that there is untapped potential for the use of DGVMs in ecological and ecophysiological research. One fundamental barrier to realize this potential is that many researchers with relevant expertize (ecology, plant physiology, soil science, etc.) lack access to the technical resources or awareness of the research potential of DGVMs. Here we present the Land Sites Platform (LSP): new software that facilitates single-site simulations with the Functionally Assembled Terrestrial Ecosystem Simulator, an advanced DGVM coupled with the Community Land Model. The LSP includes a Graphical User Interface and an Application Programming Interface, which improve the user experience and lower the technical thresholds for installing these model architectures and setting up model experiments. The software is distributed via version-controlled containers; researchers and students can run simulations directly on their personal computers or servers, with relatively low hardware requirements, and on different operating systems. Version 1.0 of the LSP supports site-level simulations. We provide input data for 20 established geo-ecological observation sites in Norway and workflows to add generic sites from public global datasets. The LSP makes standard model experiments with default data easily achievable (e.g., for educational or introductory purposes) while retaining flexibility for more advanced scientific uses. We further provide tools to visualize the model input and output, including simple examples to relate predictions to local observations. The LSP improves access to land surface and DGVM modelling as a building block of community cyberinfrastructure that may inspire new avenues for mechanistic ecosystem research across disciplines.publishedVersio

Reading tea leaves worldwide: Decoupled drivers of initial litter decomposition mass-loss rate and stabilization

The breakdown of plant material fuels soil functioning and biodiversity. Currently, process understanding of global decomposition patterns and the drivers of such patterns are hampered by the lack of coherent large-scale datasets. We buried 36,000 individual litterbags (tea bags) worldwide and found an overall negative correlation between initial mass-loss rates and stabilization factors of plant-derived carbon, using the Tea Bag Index (TBI). The stabilization factor quantifies the degree to which easy-to-degrade components accumulate during early-stage decomposition (e.g. by environmental limitations). However, agriculture and an interaction between moisture and temperature led to a decoupling between initial mass-loss rates and stabilization, notably in colder locations. Using TBI improved mass-loss estimates of natural litter compared to models that ignored stabilization. Ignoring the transformation of dead plant material to more recalcitrant substances during early-stage decomposition, and the environmental control of this transformation, could overestimate carbon losses during early decomposition in carbon cycle models

Reading tea leaves worldwide: decoupled drivers of initial litter decomposition mass‐loss rate and stabilization

The breakdown of plant material fuels soil functioning and biodiversity. Currently, process understanding of global decomposition patterns and the drivers of such patterns are hampered by the lack of coherent large‐scale datasets. We buried 36,000 individual litterbags (tea bags) worldwide and found an overall negative correlation between initial mass‐loss rates and stabilization factors of plant‐derived carbon, using the Tea Bag Index (TBI). The stabilization factor quantifies the degree to which easy‐to‐degrade components accumulate during early‐stage decomposition (e.g. by environmental limitations). However, agriculture and an interaction between moisture and temperature led to a decoupling between initial mass‐loss rates and stabilization, notably in colder locations. Using TBI improved mass‐loss estimates of natural litter compared to models that ignored stabilization. Ignoring the transformation of dead plant material to more recalcitrant substances during early‐stage decomposition, and the environmental control of this transformation, could overestimate carbon losses during early decomposition in carbon cycle models

The handbook for standardized field and laboratory measurements in terrestrial climate change experiments and observational studies (ClimEx)

1. Climate change is a world‐wide threat to biodiversity and ecosystem structure, functioning and services. To understand the underlying drivers and mechanisms, and to predict the consequences for nature and people, we urgently need better understanding of the direction and magnitude of climate change impacts across the soil–plant–atmosphere continuum. An increasing number of climate change studies are creating new opportunities for meaningful and high‐quality generalizations and improved process understanding. However, significant challenges exist related to data availability and/or compatibility across studies, compromising opportunities for data re‐use, synthesis and upscaling. Many of these challenges relate to a lack of an established ‘best practice’ for measuring key impacts and responses. This restrains our current understanding of complex processes and mechanisms in terrestrial ecosystems related to climate change. 2. To overcome these challenges, we collected best‐practice methods emerging from major ecological research networks and experiments, as synthesized by 115 experts from across a wide range of scientific disciplines. Our handbook contains guidance on the selection of response variables for different purposes, protocols for standardized measurements of 66 such response variables and advice on data management. Specifically, we recommend a minimum subset of variables that should be collected in all climate change studies to allow data re‐use and synthesis, and give guidance on additional variables critical for different types of synthesis and upscaling. The goal of this community effort is to facilitate awareness of the importance and broader application of standardized methods to promote data re‐use, availability, compatibility and transparency. We envision improved research practices that will increase returns on investments in individual research projects, facilitate second‐order research outputs and create opportunities for collaboration across scientific communities. Ultimately, this should significantly improve the quality and impact of the science, which is required to fulfil society's needs in a changing world

The importance of vegetation functional composition in mediating climate change impacts on ecosystem carbon dynamics in alpine grasslands

Climate is changing around the world, and because temperature and water are key drivers of many ecosystem processes this is expected to have significant effects on ecosystem processes and functioning, including ecosystem carbon cycling. In addition to the direct effects of increased temperature and changes is precipitation, indirect effects of climate-induced shifts in plant dominance can affect ecosystems and their functioning through a complex series of biotic cascades, couplings, and feedbacks (Wookey et al 2009). Alpine ecosystems in particular are expected to be strongly impacted by global warming because of the high temperature-sensitivity of biological and chemical processes and their vulnerability to vegetation shifts. In this thesis, I investigate the direct and indirect effects of climate change on ecosystem carbon dynamics in semi-natural alpine grasslands. The study design makes use of a systematic climate grid in Western Norway that consists of twelve semi-natural grassland selected along natural climate gradients, where temperature and precipitation vary independently. At each site we performed a fully factorial removal experiment, removing different plant functional groups (graminoids, forbs, bryophytes), to determine their effect on ecosystem carbon cycling and soil physical conditions. In addition, several plant functional traits were measured at each site to assess their contribution in determining ecosystem carbon exchange compared to climate and vegetation structure characteristics. I used a static chamber method to measure ecosystem carbon flux and estimate net ecosystem exchange (NEE), gross primary production (GPP) and ecosystem respiration (Reco) across the climatic gradients and removal experiment. Furthermore, I performed a standardized litter bag experiment to investigate the short-term direct effect of annual variability in temperature and precipitation and long-term indirect effect of climate variability along the natural climatic gradients on litter decomposition. The presence and functional composition of vegetation regulated soil temperature and to an extent soil moisture, which are key controls of ecosystem processes. Vegetation cover reduced maximum soil temperature due to the vegetation’s insulating capacity or shading. The strength of this effect depended on vegetation structure, plant functional group cover and vascular and non-vascular vegetation height. Bryophytes had a larger effect on soil temperature than forbs or graminoids, and increased depth of bryophyte mat strengthened the insulating effect of bryophytes. Soil moisture was primarily determined by the amount of precipitation received by a research site. Functional attributes of vegetation will therefore influence ecosystem processes like plant growth and decomposition through their regulating effect on soil temperature and thus influence ecosystem carbon cycling. Gross primary production was largely determined by vascular plant biomass, while respiration was primarily controlled by temperature and was little influenced by biomass of vascular plants. Bryophytes did not have a significant effect on either gross primary production or ecosystem respiration. Compensation of gross primary production after plant functional group loss was dependent on remaining plant functional groups and their interaction, which again was dependent on climate. In alpine sites, compensation capacity of forbs was stimulated when bryophytes were present, while in boreal sites compensation capacity of gramininoids seemed to be limited by bryophytes. For ecosystem respiration there was no difference in compensation capacity between plant functional groups nor effects of climate. We assessed the value of using plant functional traits for predictions of ecosystem C flux in relation to climate change. Climatic effects on gross primary production were related to changes in vegetation structure and plant functional traits, particularly a shift in traits of plant communities from tall, fast-growing species with big, thin leaves and low C:N in warmer drier sites to communities with lower growth, small and thicker leaves and higher leaf C:N cold sites. Plant functional traits were also able to capture additional between-site variation in ecosystem carbon exchange not related to climate, and could even account for appreciable amounts of variability at the within-site scale, which is likely related to smaller-scale driver of vegetation community composition such as topography and soil characteristics. The decomposition experiment revealed that direct effect of annual variation in temperature and precipitation on decomposition processes are modulated by environmental conditions, including plant diversity. Increasing temperature enhanced decomposition rate k and litter stabilization factor S within each climate regime, while this effect was not found across the different climate regimes for k and even had the reverse effect on S, as S decreased with temperature across climate regimes. Increased precipitation reduced k within and across climatic regimes, while increased precipitation decreased S in sub-alpine and alpine sites, but not boreal sites. We speculate that the differences in decomposition between climate regimes can related to differences in microbial community composition and soil structure. Altogether, this thesis highlight the importance of local environmental conditions and the functional composition of vegetation as modulators of climate change impacts on ecosystem carbon dynamics. This knowledge improves our understanding of how climate-induced changes in the functional composition of vegetation can affect ecosystem carbon cycling, and can possibly help improve predictability of ecosystem carbon exchange under global warming

PFTCourses, Elevational Gradient, Bird Cliff and ITEX Experiment, Longyearbyen, Svalbard

This project reports on plant functional traits, vegetation, ecosystem, and climate data in response to climate change experiments and along a 300 m elevational gradient and a bird cliff near Longyearbyen, Svalbard. The data was recorded in 3 different locations. Across 7 sites along the elevational gradient, 5 sites along a bird cliff gradient, and an ITEX warming experiments with Open Top chamber (OTC). The data were collected between 2003 and 2018 as part of Norwegian research projects and the international Plant Functional Traits Courses 4 (PFTC4)