Browsing by Subject "VASCULAR PLANTS"

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  • Watts, J. D.; Kimball, J. S.; Parmentier, F. J. W.; Sachs, T.; Rinne, J.; Zona, D.; Oechel, W.; Tagesson, T.; Jackowicz-Korczynski, M.; Aurela, M. (2014)
  • Susiluoto, Jouni; Raivonen, Maarit; Backman, Leif; Laine, Marko; Makela, Jarmo; Peltola, Olli; Vesala, Timo; Aalto, Tuula (2018)
    Estimating methane (CH4) emissions from natural wetlands is complex, and the estimates contain large uncertainties. The models used for the task are typically heavily parameterized and the parameter values are not well known. In this study, we perform a Bayesian model calibration for a new wetland CH4 emission model to improve the quality of the predictions and to understand the limitations of such models. The detailed process model that we analyze contains descriptions for CH4 production from anaerobic respiration, CH4 oxidation, and gas transportation by diffusion, ebullition, and the aerenchyma cells of vascular plants. The processes are controlled by several tunable parameters. We use a hierarchical statistical model to describe the parameters and obtain the posterior distributions of the parameters and uncertainties in the processes with adaptive Markov chain Monte Carlo (MCMC), importance resampling, and time series analysis techniques. For the estimation, the analysis utilizes measurement data from the Siikaneva flux measurement site in southern Finland. The uncertainties related to the parameters and the modeled processes are described quantitatively. At the process level, the flux measurement data are able to constrain the CH4 production processes, methane oxidation, and the different gas transport processes. The posterior covariance structures explain how the parameters and the processes are related. Additionally, the flux and flux component uncertain-ties are analyzed both at the annual and daily levels. The parameter posterior densities obtained provide information regarding importance of the different processes, which is also useful for development of wetland methane emission models other than the square root HelsinkI Model of MEthane buiLd- up and emIssion for peatlands (sqHIMMELI). The hierarchical modeling allows us to assess the effects of some of the parameters on an annual basis. The results of the calibration and the cross validation suggest that the early spring net primary production could be used to predict parameters affecting the annual methane production. Even though the calibration is specific to the Siikaneva site, the hierarchical modeling approach is well suited for larger-scale studies and the results of the estimation pave way for a regional or global- scale Bayesian calibration of wetland emission models.
  • Wetzel, Carlos E.; Bicudo, Denise de C.; Ector, Luc; Lobo, Eduardo A.; Soininen, Janne; Landeiro, Victor L.; Bini, Luis M. (2012)
    Background The regression of similarity against distance unites several ecological phenomena, and thus provides a highly useful approach for illustrating the spatial turnover across sites. Our aim was to test whether the rates of decay in community similarity differ between diatom growth forms suggested to show different dispersal ability. We hypothesized that the diatom group with lower dispersal ability (i.e. periphyton) would show higher distance decay rates than a group with higher dispersal ability (i.e. plankton). Methods/Principal findings Periphyton and phytoplankton samples were gathered at sites distributed over an area of approximately 800 km length in the Negro River, Amazon basin, Brazil, South America (3°08′00″S; 59°54′30″W). Distance decay relationships were then estimated using distance-based regressions, and the coefficients of these regressions were compared among the groups with different dispersal abilities to assess our predictions. We found evidence that different tributaries and reaches of the Negro River harbor different diatom communities. As expected, the rates of distance decay in community similarity were higher for periphyton than for phytoplankton indicating the lower dispersal ability of periphytic taxa. Conclusions/Significance Our study demonstrates that the comparison of distance decay relationships among taxa with similar ecological requirements, but with different growth form and thus dispersal ability provides a sound approach to evaluate the effects of dispersal ability on beta diversity patterns. Our results are also in line with the growing body of evidence indicating that microorganisms exhibit biogeographic patterns. Finally, we underscore that clumbing all microbial taxa into one group may be a flawed approach to test whether microbes exhibit biogeographic patterns.
  • Riutta, Terhi; Korrensalo, Aino; Laine, Anna M.; Laine, Jukka; Tuittila, Eeva-Stiina (2020)
    Vegetation and hydrology are important controlling factors in peatland methane dynamics. This study aimed at investigating the role of vegetation components, sedges, dwarf shrubs, and Sphagnum mosses, in methane fluxes of a boreal fen under natural and experimental water level draw-down conditions. We measured the fluxes during growing seasons 2001-2004 using the static chamber technique in a field experiment where the role of the ecosystem components was assessed via plant removal treatments. The first year was a calibration year after which the water level draw-down and vegetation removal treatments were applied. Under natural water level conditions, plant-mediated fluxes comprised 68%-78% of the mean growing season flux (1:73 +/- 0:17 gCH(4) m(-2) month 1 from June to September), of which Sphagnum mosses and sedges accounted for one-fourth and three-fourths, respectively. The presence of dwarf shrubs, on the other hand, had a slightly attenuating effect on the fluxes. In water level drawdown conditions, the mean flux was close to zero (0:03 +/- 0:03 gCH(4) m(-2) month(-1)) and the presence and absence of the plant groups had a negligible effect. In conclusion, water level acted as a switch; only in natural water level conditions did vegetation regulate the net fluxes. The results are relevant for assessing the response of fen peatland fluxes to changing climatic conditions, as water level drawdown and the consequent vegetation succession are the major projected impacts of climate change on northern peatlands.
  • Aikio, Sami; Ramula, Satu; Muola, Anne; von Numers, Mikael (2020)
    The extrinsic determinants hypothesis emphasizes the essential role of environmental heterogeneity in species' colonization. Consequently, high resident species diversity can increase community susceptibility to colonizations because good habitats may support more species that are functionally similar to colonizers. On the other hand, colonization success is also likely to depend on species traits. We tested the relative importance of environmental characteristics and species traits in determining colonization success using census data of 587 vascular plant species collected about 70 yr apart from 471 islands in the archipelago of SW Finland. More specifically, we explored potential new colonization as a function of island properties (e.g. location, area, habitat diversity, number of resident species per unit area), species traits (e.g. plant height, life-form, dispersal vector, Ellenberg indicator values, association with human impact), and species' historical distributions (number of inhabited islands, nearest occurrence). Island properties and species' historical distributions were more effective than plant traits in explaining colonization outcomes. Contrary to the extrinsic determinants hypothesis, colonization success was neither associated with resident species diversity nor habitat diversity per se, although colonization was lowest on sparsely vegetated islands. Our findings lead us to propose that while plant traits related to dispersal and establishment may enhance colonization, predictions of plant colonizations primarily require understanding of habitat properties and species' historical distributions.
  • Peltola, Olli; Vesala, Timo; Gao, Yao; Raty, Olle; Alekseychik, Pavel; Aurela, Mika; Chojnicki, Bogdan; Desai, Ankur R.; Dolman, Albertus J.; Euskirchen, Eugenie S.; Friborg, Thomas; Goeckede, Mathias; Helbig, Manuel; Humphreys, Elyn; Jackson, Robert B.; Jocher, Georg; Joos, Fortunat; Klatt, Janina; Knox, Sara H.; Kowalska, Natalia; Kutzbach, Lars; Lienert, Sebastian; Lohila, Annalea; Mammarella, Ivan; Nadeau, Daniel F.; Nilsson, Mats B.; Oechel, Walter C.; Peichl, Matthias; Pypker, Thomas; Quinton, William; Rinne, Janne; Sachs, Torsten; Samson, Mateusz; Schmid, Hans Peter; Sonnentag, Oliver; Wille, Christian; Zona, Donatella; Aalto, Tuula (2019)
    Natural wetlands constitute the largest and most uncertain source of methane (CH4) to the atmosphere and a large fraction of them are found in the northern latitudes. These emissions are typically estimated using process ("bottom-up") or inversion ("top-down") models. However, estimates from these two types of models are not independent of each other since the top-down estimates usually rely on the a priori estimation of these emissions obtained with process models. Hence, independent spatially explicit validation data are needed. Here we utilize a random forest (RF) machine-learning technique to upscale CH4 eddy covariance flux measurements from 25 sites to estimate CH4 wetland emissions from the northern latitudes (north of 45 degrees N). Eddy covariance data from 2005 to 2016 are used for model development. The model is then used to predict emissions during 2013 and 2014. The predictive performance of the RF model is evaluated using a leave-one-site-out cross-validation scheme. The performance (Nash-Sutcliffe model efficiency = 0.47) is comparable to previous studies upscaling net ecosystem exchange of carbon dioxide and studies comparing process model output against site-level CH4 emission data. The global distribution of wetlands is one major source of uncertainty for upscaling CH4. Thus, three wetland distribution maps are utilized in the upscaling. Depending on the wetland distribution map, the annual emissions for the northern wetlands yield 32 (22.3-41.2, 95% confidence interval calculated from a RF model ensemble), 31 (21.4-39.9) or 38 (25.9-49.5) Tg(CH4) yr(-1). To further evaluate the uncertainties of the upscaled CH4 flux data products we also compared them against output from two process models (LPX-Bern and WetCHARTs), and methodological issues related to CH4 flux upscaling are discussed. The monthly upscaled CH4 flux data products are available at https://doi.org/10.5281/zenodo.2560163.
  • Opedal, Øystein H.; von Numers, Mikael; Tikhonov, Gleb; Ovaskainen, Otso (2020)
    Abstract Predicting the dynamics of biotic communities is difficult because species? environmental responses are not independent, but covary due to shared or contrasting ecological strategies and the influence of species interactions. We used latent-variable joint species distribution models to analyse paired historical and contemporary inventories of 585 vascular plant species on 471 islands in the south-west Finnish archipelago. Larger, more heterogeneous islands were characterized by higher colonisation rates and lower extinction rates. Ecological and taxonomical species groups explained small but detectable proportions of variance in species? environmental responses. To assess the potential influence of species interactions on community dynamics, we estimated species associations as species-to-species residual correlations for historical occurrences, for colonisations, and for extinctions. Historical species associations could to some extent predict joint colonisation patterns, but the overall estimated influence of species associations on community dynamics was weak. These results illustrate the benefits of considering metacommunity dynamics within a joint framework, but also suggest that any influence of species interactions on community dynamics may be hard to detect from observational data.
  • Korrensalo, Aino; Mannisto, Elisa; Alekseychik, Pavel; Mammarella, Ivan; Rinne, Janne; Vesala, Timo; Tuittila, Eeva-Stiina (2018)
    We measured methane fluxes of a patterned bog situated in Siikaneva in southern Finland from six different plant community types in three growing seasons (2012-2014) using the static chamber method with chamber exposure of 35 min. A mixed-effects model was applied to quantify the effect of the controlling factors on the methane flux. The plant community types differed from each other in their water level, species composition, total leaf area (LAI(TOT)) and leaf area of aerenchymatous plant species (LAI(AER)). Methane emissions ranged from -309 to 1254 mg m(-2) d(-1). Although methane fluxes increased with increasing peat temperature, LAI(TOT) and LAI(AER), they had no correlation with water table or with plant community type. The only exception was higher fluxes from hummocks and high lawns than from high hummocks and bare peat surfaces in 2013 and from bare peat surfaces than from high hummocks in 2014. Chamber fluxes upscaled to ecosystem level for the peak season were of the same magnitude as the fluxes measured with the eddy covariance (EC) technique. In 2012 and in August 2014 there was a good agreement between the two methods; in 2013 and in July 2014, the chamber fluxes were higher than the EC fluxes. Net fluxes to soil, indicating higher methane oxidation than production, were detected every year and in all community types. Our results underline the importance of both LAI(AER) and LAI(TOT) in controlling methane fluxes and indicate the need for automatized chambers to reliably capture localized events to support the more robust EC method.
  • Rissanen, Tuuli Katariina; Niittynen, Pekka; Soininen, Janne; Luoto, Miska (2021)
    Aim To examine how snow cover and permafrost affect plant species distributions at a subcontinental extent. Location Mountain realm of Fennoscandia, northern Europe. Time period Species data from 1 January 1990-25 February 2019. Major taxa studied Arctic-alpine and boreal vascular plants. Methods We examined the effect of snow persistence and permafrost occurrence on the distributions of arctic-alpine and boreal plant species while controlling for climate, topography and geological factors. Data comprised 475,811 observations from 671 species in the Fennoscandian mountains. We investigated the relationships between species distributions and environmental variables using four modelling methods and ensemble modelling building on both non-spatial and spatial models. Results Snow persistence was the most important driver of plant species distributions, with the greatest variable importance for both arctic-alpine (38.2%) and boreal (49.9%) species. Permafrost had a consistent minor effect on the predicted distributions. Arctic-alpine plants occur in areas with long snow persistence and permafrost, whereas boreal species showed the opposite habitat preferences. Main conclusions Our results highlight the importance of snow persistence in driving the distribution of vascular plant species in cold environments at a subcontinental scale. The notable contribution of the cryosphere to plant species distribution models indicates that the inclusion of snow information in particular may improve our understanding and model predictions of biogeographical patterns in cold regions.
  • Mikola, Juha; Virtanen, Tarmo; Linkosalmi, Maiju; Vähä, Emmi; Nyman, Johanna; Postanogova, Olga; Räsänen, Aleksi; Kotze, D. Johan; Laurila, Tuomas; Juutinen, Sari; Kondratyev, Vladimir; Aurela, Mika (2018)
    Arctic tundra ecosystems will play a key role in future climate change due to intensifying permafrost thawing, plant growth and ecosystem carbon exchange, but monitoring these changes may be challenging due to the heterogeneity of Arctic landscapes. We examined spatial variation and linkages of soil and plant attributes in a site of Siberian Arctic tundra in Tiksi, northeast Russia, and evaluated possibilities to capture this variation by remote sensing for the benefit of carbon exchange measurements and landscape extrapolation. We distinguished nine land cover types (LCTs) and to characterize them, sampled 92 study plots for plant and soil attributes in 2014. Moreover, to test if variation in plant and soil attributes can be detected using remote sensing, we produced a normalized difference vegetation index (NDVI) and topographical parameters for each study plot using three very high spatial resolution multispectral satellite images. We found that soils ranged from mineral soils in bare soil and lichen tundra LCTs to soils of high percentage of organic matter (OM) in graminoid tundra, bog, dry fen and wet fen. OM content of the top soil was on average 14 g dm(-3) in bare soil and lichen tundra and 89 g dm(-3) in other LCTs. Total moss biomass varied from 0 to 820 gm(-2), total vascular shoot mass from 7 to 112 gm(-2) and vascular leaf area index (LAI) from 0.04 to 0.95 among LCTs. In late summer, soil temperatures at 15 cm depth were on average 14 degrees C in bare soil and lichen tundra, and varied from 5 to 9 degrees C in other LCTs. On average, depth of the biologically active, unfrozen soil layer doubled from early July to mid-August. When contrasted across study plots, moss biomass was positively associated with soil OM % and OM content and negatively associated with soil temperature, explaining 14-34% of variation. Vascular shoot mass and LAI were also positively associated with soil OM content, and LAI with active layer depth, but only explained 6-15% of variation. NDVI captured variation in vascular LAI better than in moss biomass, but while this difference was significant with late season NDVI, it was minimal with early season NDVI. For this reason, soil attributes associated with moss mass were better captured by early season NDVI. Topographic attributes were related to LAI and many soil attributes, but not to moss biomass and could not increase the amount of spatial variation explained in plant and soil attributes above that achieved by NDVI. The LCT map we produced had low to moderate uncertainty in predictions for plant and soil properties except for moss biomass and bare soil and lichen tundra LCTs. Our results illustrate a typical tundra ecosystem with great fine-scale spatial variation in both plant and soil attributes. Mosses dominate plant biomass and control many soil attributes, including OM % and temperature, but variation in moss biomass is difficult to capture by remote sensing reflectance, topography or a LCT map. Despite the general accuracy of landscape level predictions in our LCT approach, this indicates challenges in the spatial extrapolation of some of those vegetation and soil attributes that are relevant for the regional ecosystem and global climate models.
  • Usmonov, Mansur; Tojibaev, Komiljon; Jang, Chang-Gee; Sennikov, Alexander N. (2021)
    Background Cousinia knorringiae Bornm. (Asteraceae) belongs to C. sect. Subappendiculatae Tscherneva, a group of the species-rich and taxonomically difficult genus Cousinia Cass. This species is narrowly distributed in the Western Tian-Shan and has been known as endemic to Kyrgyzstan. It inhabits bare rocks and screes at elevations of 1200-1500 m above sea level. This species is of conservation interest because of its small population size and limited distribution. New information Cousinia knorringiae is reported for the first time from eastern Uzbekistan on the basis of specimens collected on Ungur-Tepa Mt., a south-western outlier of the Bozbu-Too Mts. (Western Tian-Shan). The conservation status of the species is assessed as Endangered (EN), based on criterion D (estimated population size 200-250 mature individuals), according to the IUCN Red List Categories and Criteria (version 3.1). A new distribution map and a line drawing for C. knorringiae are provided and its type locality is clarified. The new knowledge suggests that the species is endemic to the East Fergana botanical hotspot, which includes a transborder territory shared between Kyrgyzstan and Uzbekistan and should, therefore, be subjected to international conservation measures. The southern extension of Ungur-Tepa Mt. harbours important plant species, which cannot be found elsewhere in Uzbekistan and may, therefore, be proposed for legal protection.
  • Ranta, Pertti; Jokinen, Ari; Laaka-Lindberg, Sanna (2016)
    Building strategies for continental-scale conservation is challenging due to evolutionary and geopolitical problems. How do policy choices arise from this setting? In this study, we integrate ecological research with policy analysis to examine the problem field with a case study research. We use a violet species endemic to Europe, Viola uliginosa, as a proxy for a significant European Union (EU)-Russian biodiversity pattern and its conservation. The violet's core populations locate in Belarus, Ukraine, and Russia, and all populations in the EU are peripheral. The species is endangered in 12 EU member states and in decline in many places elsewhere. To analyze the choices of conservation, we gathered data on its ecology, distribution, and conservation mechanisms across Europe, putting additional emphasis on the EU enlargement and long-term site histories in Finland. We found that the survival of the species in the EU depends on the enlargement negotiations, conflicts between the EU biodiversity and agricultural policies, selection of the species to national Red Lists and the Habitats Directive, and contingent site histories depending on the conservation activities by civic actors and the member states. While the evolutionary aspect emphasizes the genetic differentiation potential of peripheral populations, the geopolitical aspect characterizes the EU as simultaneous spaces of a monotopia, borderlands, and polycentric development. We conclude that intersections between these geopolitical spaces can be used with evolutionary perspectives to identify local, European, and network-driven policy choices of conservation.
  • Rinne, Janne; Tuittila, Eeva-Stiina; Peltola, Olli; Li, Xuefei; Raivonen, Maarit; Alekseychik, Pavel; Haapanala, Sami; Pihlatie, Mari; Aurela, Mika; Mammarella, Ivan; Vesala, Timo (2018)
    We have analyzed decade-long methane flux data set from a boreal fen, Siikaneva, together with data on environmental parameters and carbon dioxide exchange. The methane flux showed seasonal cycle but no systematic diel cycle. The highest fluxes were observed in July-August with average value of 73 nmol m(-2) s(-1). Wintertime fluxes were small but positive, with January-March average of 6.7 nmol m(-2) s(-1). Daily average methane emission correlated best with peat temperatures at 20-35 cm depths. The second highest correlation was with gross primary production (GPP). The best correspondence between emission algorithm and measured fluxes was found for a variable-slope generalized linear model (r(2) = 0.89) with peat temperature at 35 cm depth and GPP as explanatory variables, slopes varying between years. The homogeneity of slope approach indicated that seasonal variation explained 79% of the sum of squares variation of daily average methane emission, the interannual variation in explanatory factors 7.0%, functional change 5.3%, and random variation 9.1%. Significant correlation between interannual variability of growing season methane emission and that of GPP indicates that on interannual time scales GPP controls methane emission variability, crucially for development of process-based methane emission models. Annual methane emission ranged from 6.0 to 14 gC m(-2) and was 2.7 +/- 0.4% of annual GPP. Over 10-year period methane emission was 18% of net ecosystem exchange as carbon. The weak relation of methane emission to water table position indicates that space-to-time analogy, used to extrapolate spatial chamber data in time, may not be applicable in seasonal time scales.
  • Zhang, Hui; Tuittila, Eeva-Stiina; Korrensalo, Aino; Rasänen, Aleksi; Virtanen, Tarmo; Aurela, Mika; Penttilä, Timo; Laurila, Tuomas; Gerin, Stephanie; Lindholm, Viivi; Lohila, Annalea (2020)
    Northern peatlands are projected to be crucial in future atmospheric methane (CH4) budgets and have a positive feedback on global warming. Fens receive nutrients from catchments via inflowing water and are more sensitive than bogs to variations in their ecohydrology. Yet, due to a lack of data detailing the impacts of moving water on microhabitats and CH4 fluxes in fens, large uncertainties remain with respect to predicting CH4 emissions from these sites under climate changes. We measured CH4 fluxes with manual chambers over three growing seasons (2017-2019) at a northern boreal fen. To address the spatial variation at the site where a stream flows through the long and narrow valley fen, we established sample plots at varying distances from the stream. To link the variations in CH4 emissions to environmental controls, we quantified water levels, peat temperature, dissolved oxygen concentration, vegetation composition, and leaf area index in combination with flux measurements during the growing season in 2019. We found that due to the flowing water, there was a higher water level, cooler peat temperatures, and more oxygen in the peat close to the stream, which also had the highest total leaf area and gross primary production (GPP) values but the lowest CH4 emissions. CH4 emissions were highest at an intermediate distance from the stream where the oxygen concentration in the surface peat was low but GPP was still high. Further from the stream, the conditions were drier and produced low CH4 emissions. Our results emphasize the key role of ecohydrology in CH4 dynamics in fens and, for the first time, show how a stream controls CH4 emissions in a flow-through fen. As valley fens are common peatland ecosystems from the Arctic to the temperate zones, future projections of global CH4 budgets need to take flowing water features into account.
  • Ovaskainen, Otso; Rybicki, Joel; Abrego, Nerea (2019)
    A key challenge for community ecology is to understand to what extent observational data can be used to infer the underlying community assembly processes. As different processes can lead to similar or even identical patterns, statistical analyses of non-manipulative observational data never yield undisputable causal inference on the underlying processes. Still, most empirical studies in community ecology are based on observational data, and hence understanding under which circumstances such data can shed light on assembly processes is a central concern for community ecologists. We simulated a spatial agent-based model that generates variation in metacommunity dynamics across multiple axes, including the four classic metacommunity paradigms as special cases. We further simulated a virtual ecologist who analysed snapshot data sampled from the simulations using eighteen output metrics derived from beta-diversity and habitat variation indices, variation partitioning and joint species distribution modelling. Our results indicated two main axes of variation in the output metrics. The first axis of variation described whether the landscape has patchy or continuous variation, and thus was essentially independent of the properties of the species community. The second axis of variation related to the level of predictability of the metacommunity. The most predictable communities were niche-based metacommunities inhabiting static landscapes with marked environmental heterogeneity, such as metacommunities following the species sorting paradigm or the mass effects paradigm. The most unpredictable communities were neutral-based metacommunities inhabiting dynamics landscapes with little spatial heterogeneity, such as metacommunities following the neutral or patch sorting paradigms. The output metrics from joint species distribution modelling yielded generally the highest resolution to disentangle among the simulated scenarios. Yet, the different types of statistical approaches utilized in this study carried complementary information, and thus our results suggest that the most comprehensive evaluation of metacommunity structure can be obtained by combining them.
  • Fernández-Marín, Beatriz; Atherton, Jon; Olascoaga, Beñat; Kolari, Pasi; Porcar Castell, Albert; García-Plazaola, José I. (2018)
    Subarctic plants in summer (subjected to continuous light) showed photosynthetic pigment contents mainly driven by PPFD (unrelated to day/night cycles) and a xanthophyll cycle responsiveness to PPFD exacerbated during night-times. Composition and content of photosynthetic pigments is finely tuned by plants according to a subtle equilibrium between the absorbed and used energy by the photosynthetic apparatus. Subarctic and Arctic plants are subjected to extended periods of continuous light during summer. This condition represents a unique natural scenario to study the influence of light on pigment regulation and the presence of diurnal patterns potentially governed by circadian rhythms. Here, we examined the modulation of the photosynthetic apparatus in three naturally co-occurring woody species: mountain birch (Betula pubescens ssp. czerepanovii), alpine bearberry (Arctostaphylos alpina) and Scots pine (Pinus sylvestris) around the summer solstice, at 67 A degrees N latitude. Plants were continuously exposed to solar radiation during the 3-day study period, although PPFD fluctuated, being lower during night-times. Photochemical efficiencies for a given PPFD were similar during daytime and night-time for the three species. In Scots pine, for a given PPFD, net assimilation was slightly higher during daytime than during night-time. Overall, the dynamism in pigment content was mainly driven by PPFD, and was generally unrelated to day/night cycles. Weak indications of potential circadian regulation were found over a few pigments only. Interestingly, the xanthophyll cycle was active at any time of the day in the three species but its responsiveness to PPFD was exacerbated during night-times. This was particularly evident for bearberry, which maintained a highly de-epoxidised state even at night-times. The results could indicate an incomplete acclimation to a 24-h photoperiod for these species, which have colonised subarctic latitudes only recently.