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Many ecosystems are defined and shaped by one or a few common, foundation species. Even though such species hold a key role in the restoration of these ecosystems, the demographic processes involved in their re‐establishment have rarely been studied. Foundation species' population dynamics, re‐establishment history, and the abiotic and biotic factors that affect individual establishment at restored sites can be studied by addressing population spatial patterns and age structure. Such an approach to studying population dynamics is particularly relevant for long‐lived species with low mortality, such as shrubs in alpine areas. We studied a population of the foundation species Empetrum nigrum ssp. hermaphroditum at an alpine spoil heap site and found evidence of population re‐establishment starting within a decade after construction. High Empetrum densities close to the spoil heap edges indicated that short distances to seed sources in the surroundings had a strong positive effect on establishment of individuals. Empetrum individuals were significantly clustered, which indicated intraspecific facilitation. As revealed by spatial analyses of recruits and older, established individuals, clustering developed gradually over time, which indicated a shift from no interaction to increased facilitation. We conclude that intraspecific facilitation promotes Empetrum reestablishment at the studied alpine spoil heap. Synthesis: We show that population spatial patterns and age structure can be successfully used to unveil the re‐establishment history of a foundation species in a restoration context. Efficient seed dispersal and intraspecific facilitation seem to be important factors behind Empetrum's successful re‐establishment at alpine spoil heaps. Identification of abiotic and biotic factors determining foundation species' establishment success at restored sites can support planning and improve success of restoration. [ABSTRACT FROM AUTHOR]

An urgent aim of ecology is to understand how key species relate to climatic and environmental variation, to better predict their prospects under future climate change. The abundant dwarf shrub bilberry (Vaccinium myrtillus L.) has caught particular interest due to its uphill expansion into alpine areas. Species' performance under changing climate has been widely studied using the climatic space‐for‐time approach along elevation gradients, but potentially confounding, local environmental variables that vary along elevation gradients have rarely been considered. In this study, performed in 10 sites along an elevation gradient (200–875 m) in W Norway, we recorded species composition and bilberry performance, both vegetative (ramet size and cover) and reproductive (berry and seed production) properties, over one to 4 years. We disentangled effects of local environmental variables and between‐year, climatic variation (precipitation and temperature), and identified shared and unique contributions of these variables by variation partitioning. We found bilberry ramet size, cover and berry production to peak at intermediate elevations, whereas seed production increased upwards. The peaks were less pronounced in extreme (dry or cold) summers than in normal summers. Local environmental variables explained much variation in ramet size and cover, less in berry production, and showed no relation to seed production. Climatic variables explained more of the variation in berry and seed production than in ramet size and cover, with temperature relating to vegetative performance, and precipitation to reproductive performance. Bilberry's clonal growth and effective reproduction probably explain why the species persists in the forest and at the same time invades alpine areas. Our findings raise concerns of the appropriateness of the climatic space‐for‐time approach. We recommend including both climatic and local environmental variables in studies of variation along elevation gradients and conclude that variation partitioning can be a useful supplement to other methods for analysing variation in plant performance. [ABSTRACT FROM AUTHOR]

Functional traits are linked to ecosystem processes and services and therefore relevant in recovery assessment. However, traits of bryophytes and lichens, important components of many ecosystems, have received less attention than those of vascular plants. We explored the use of functional traits of multiple important organism groups in recovery assessment. We combined data on traits and species composition for vascular plants, bryophytes, and lichens from four alpine spoil heaps and their undisturbed surroundings in western Norway, collected at three time‐points spanning more than two decades. We studied changes in community‐weighted mean (CWM) trait values and distribution of trait‐category optima over time. We analyzed temporal variation in joint functional trait composition using the ordination regression‐based approach (ORBA) to predict time to recovery. We observed functional shifts along the successional gradient for all organism groups, e.g. from wind‐dispersed propagules shortly after disturbance to vegetative reproduction at later successional stages. Over time, the similarity between dispersal‐related traits of vascular plants and bryophytes on the spoil heaps and in their surroundings increased, indicating that propagule influx is important in alpine restoration. The joint functional trait composition of all spoil heaps converged towards that of their surroundings: one spoil heap had recovered 34 years after construction, while the predicted time to recovery for the other three was 59–74 years. Our results indicate that inclusion of multiple organism groups improves trait‐based recovery assessments and time‐to‐recovery predictions. Further development of trait databases is essential for future use of joint functional trait composition in recovery assessment. [ABSTRACT FROM AUTHOR]

Restoration of degraded ecosystems may take decades or even centuries. Accordingly, information about the current direction and speed of recovery provided by methods for predicting time to recovery may give important feedback to restoration schemes. While predictions of time to recovery have so far been based mostly upon change in species richness and other univariate predictors, the novel ordination‐regression based approach (ORBA) affords a multivariate approach based upon species compositional change.We used species composition data from four alpine spoil heaps in western Norway, recorded at three time points, to predict time to recovery using ORBA. This approach uses distances between restored plots and reference plots along a successional gradient, represented by a vector in ordination space, to model linear or asymptotic relationships of compositional change as a function of time. Results from ORBA were compared with results from models of more generic univariate attributes, that is total cover, species richness and properties of the physical environment as functions of time.ORBA predictions of time to species compositional recovery varied from less than 60 years with linear models to 115–212 years with asymptotic models. The long estimated time to recovery suggests that the restoration schemes adopted for these spoil heaps are likely to be suboptimal.Much shorter time to recovery was predicted from some of the more generic univariate attributes, that is species richness and total cover, than from species composition. Given the current rates of recovery, most spoil heaps will reach reference levels for total cover and species richness within 50 years, whereas predictions indicate that 67–111 years are needed to restore levels of soil organic matter and pH.Synthesis and applications. Species composition and soil conditions provide information of generally higher relevance for evaluation of ecosystem recovery processes than the most commonly used metric to assess restoration success, species richness. Species richness is decoupled from species compositional recovery, and likely to be a generally poor measure of restoration success. We therefore encourage further improvement of methods like the ordination‐regression based approach that use species compositional data to predict time to recovery. [ABSTRACT FROM AUTHOR]

The present loss of species-rich grasslands makes it vital to restore these valuable habitat types, including novel habitat variants such as road verges. Due to the lack of knowledge on long-term outcomes of restoration initiatives, well-designed studies comparing different restoration methods are needed. In this study, we examined fine-scale vegetation recovery patterns over 9 years in a field experiment with several near-natural restoration methods (adding local seed mixtures, transferring hay from local grasslands using hard or light raking, and natural regeneration) in a road verge. We compared this to standard revegetation (hydroseeding species-poor commercial seed mixtures). We found major temporal changes in vegetation restored by local seed or hay transfer, before it gradually became more similar to the donor grasslands and seed mixtures, which served as references for the experiment. Natural (spontaneous) regeneration with seed dispersal from surroundings gave similar results, whereas areas revegetated using standard methods became more dissimilar to the reference sites during the study period. The main variation in species composition reflected the contrast between local donor grasslands and seed mixtures and the species-poor early successional grasslands. We conclude that near-natural methods (hay transfer and seeding) successfully restored species-rich grassland, including road verges. This study underlines the importance of comparing several treatments over a sufficiently long period to assess their success in restoring species-rich grassland. [ABSTRACT FROM AUTHOR]

Questions How do various grassland restoration methods (hay transfer from local or distant donors, seed sowing or natural regeneration) perform in restoration of species-rich, semi-natural grasslands? Are any of the donors particularly well suited as reference vegetation? Do bare soil treatments give better results than treatments where the soil is covered? What are the probabilities of steering vegetation development towards donor vegetation under the various restoration treatments? Location Sunnfjord open-air museum in rural, Western Norway. Methods In a replicated field trial we tested four restoration methods: transferring fresh hay from a local or a distant donor (hay transfer), seeding with a regional species mix, and allowing natural regeneration. We evaluated outcomes by comparing species richness, transfer rates and vegetation dynamics in donor and trial vegetation over four successive years. Results Our study revealed considerable changes in species composition under all restoration treatments, which decreased over time, indicating decelerating succession rates. Many non-trial grassland species became established, especially after seeding and natural regeneration (bare soil treatments). All trajectories became synchronized from the second year, and by trial end, the restoration treatments converged with respect to species richness and species composition. Conclusion All restoration treatments gave high resemblance to a specific donor: the local one. Distant hay transfer resulted in larger temporal changes and exemplified a climatic donor-receiver mismatch, while the failure of several seeded species to germinate indicated an ecological mismatch under the seeding treatment. Vigorous germination of non-trial seeds in the two bare soil treatments evened out the initial treatment-related differences. Dispersal from the surrounding area and between treatments may be utilized for restoration purposes, but also limits the potential for restoring a specific species composition. Although we apparently failed to tailor donor species composition to the recipient, we note that the slow dynamics of long-lived grassland species may lead to a different long-term restoration outcome. [ABSTRACT FROM AUTHOR]

Abstract: Road verges have been proposed as refuges for vulnerable grassland species in the modern, changing landscape, but little comparative knowledge exists on how management regimes affect population dynamics of such species. We compared the effects of various management regimes on the population dynamics of Pimpinella saxifraga in road verges and pastures, using elasticities and LTRE analyses with underlying vital rates as model components in three road verges and three pastures in an agricultural landscape in W Norway. Under present management regimes, we observed slightly higher population growth rates in pastures than in road verges. The pasture populations had comparatively lower survival but higher reproduction than the road verge populations, thus demonstrating a management-induced negative correlation. Such negative correlations may reflect species’ adaptability to environment changes, thereby reducing the extinction risk. We generally observed small changes in P. saxifraga demography to management but considerable variation along environmental gradients, underlining the importance of studying multiple populations. The linear form of the road verges enabled a fine-scale mosaic application of different management regimes. Individuals growing in zones receiving survival-lowering management produced seeds that compensated the lack of seeds in zones receiving fertility-lowering management. The observation of ‘mosaic’ management that allows road verge metapopulations to complement each others life-history characteristics exemplifies the unique potential of road verge ecosystems to maintain semi-natural grassland species like P. saxifraga, as well as providing habitats for different species exhibiting various life histories. [Copyright &y& Elsevier]

Questions: Which environmental and management factors determine plant species composition in semi-natural grasslands within a local study area? Are vegetation and explanatory factors scale-dependent? Location: Semi-natural grasslands in Lærdal, Sogn og Fjordane County, western Norway. Methods: We recorded plant species composition and explanatory variables in six grassland sites using a hierarchically nested sampling design with three levels: plots randomly placed within blocks selected within sites. We evaluated vegetation-environment relationships at all three levels by means of DCA ordination and split-plot GLM analyses. Results: The most important complex gradient determining variation in grassland species composition showed a broadscale relationship with management. Soil moisture conditions were related to vegetation variation on block scale, whereas element concentrations in the soil were significantly related to variation in species composition on all spatial scales. Our results show that vegetation-environment relationships are dependent on the scale of observation. We suggest that scalerelated (and therefore methodological) issues may explain the wide range of vegetation-environment relationships reported in the literature, for semi-natural grassland in particular but also for other ecosystems. Conclusions: Interpretation of the variation in species composition of semi-natural grasslands requires consideration of the spatial scales on which important environmental variables vary. [ABSTRACT FROM AUTHOR]

The globally increasing pace of ecosystem degradation makes it necessary to develop efficient restoration programmes. A reliable tool for estimation of the remaining time to recovery is an important component of such a programme. In this study, we explore the performance of the novel, ordination regression-based approach (ORBA) for prediction of time to recovery. We applied ORBA to a dataset of plant species composition data from ten spoil heap sites in S Norway, resulting from hydropower development. Five study sites were situated in the alpine and five in the boreal bioclimatic zone, the latter group showing large between-site variability of climate, time since disturbance (age) and restoration treatments. The vegetation of spoil heaps was recorded at two time-points, while that of the surroundings of each spoil heap was recorded once, to serve as a reference. We obtained time-to-recovery predictions based on ordination of the full dataset and of two data subsets that represented alpine and boreal sites, respectively. The vegetation of all spoil heaps became more similar to the vegetation of their surroundings over time. In many cases, linear models described the temporal pattern less well than asymptotic models. The latter models predicted slow recovery for all sites, but showed large variation in time to recovery among the boreal sites. In some of the boreal sites, we observed extremely species-poor plots and many infrequent species. Moreover, in one site we observed apparent mismatch between observed vegetation development and the underlying model of increasing similarity to surroundings. We ascribed these cases to suboptimal restoration practises, and for them, non-significant ORBA models resulted. Our findings support the conclusions of previous studies; that ORBA is a robust method for predicting time to recovery over a wide range of restoration projects. Its output – predicted time (years) to recovery – is easily communicated and may be useful in evaluating the speed and direction of restoration programmes. However, our results also demonstrate the importance of carefully assessing the properties of datasets (e.g. plotwise species richness) subjected to ORBA analyses. Unlabelled Image • Predictions of restoration success are useful in restoration of degraded habitats. • ORBA (ordination regression-based approach) offers time-to-recovery predictions. • Times to recovery were predicted for alpine and boreal hydropower spoil heaps. • Dataset properties and adequacy of underlying models affect time-to-recovery predictions. • ORBA appears robust and promising but further exploration is encouraged. [ABSTRACT FROM AUTHOR]

Aim: Climate and land use are key determinants of biodiversity, with past and ongoing changes posing serious threats to global ecosystems. Unlike most other organism groups, plant species can possess dormant life‐history stages such as soil seed banks, which may help plant communities to resist or at least postpone the detrimental impact of global changes. This study investigates the potential for soil seed banks to achieve this. Location: Europe. Time period: 1978–2014. Major taxa studied: Flowering plants. Methods: Using a space‐for‐time/warming approach, we study plant species richness and composition in the herb layer and the soil seed bank in 2,796 community plots from 54 datasets in managed grasslands, forests and intermediate, successional habitats across a climate gradient. Results: Soil seed banks held more species than the herb layer, being compositionally similar across habitats. Species richness was lower in forests and successional habitats compared to grasslands, with annual temperature range more important than mean annual temperature for determining richness. Climate and land‐use effects were generally less pronounced when plant community richness included seed bank species richness, while there was no clear effect of land use and climate on compositional similarity between the seed bank and the herb layer. Main conclusions: High seed bank diversity and compositional similarity between the herb layer and seed bank plant communities may provide a potentially important functional buffer against the impact of ongoing environmental changes on plant communities. This capacity could, however, be threatened by climate warming. Dormant life‐history stages can therefore be important sources of diversity in changing environments, potentially underpinning already observed time‐lags in plant community responses to global change. However, as soil seed banks themselves appear, albeit less, vulnerable to the same changes, their potential to buffer change can only be temporary, and major community shifts may still be expected. [ABSTRACT FROM AUTHOR]

Sets of presence records used to model species' distributions typically consist of observations collected opportunistically rather than systematically. As a result, sampling probability is geographically uneven, which may confound the model's characterization of the species' distribution. Modelers frequently address sampling bias by manipulating training data: either subsampling presence data or creating a similar spatial bias in non‐presence background data. We tested a new method, which we call 'background thickening', in the latter category. Background thickening entails concentrating background locations around presence locations in proportion to presence location density. We compared background thickening to two established sampling bias correction methods – target group background selection and presence thinning – using simulated data and data from a case study. In the case study, background thickening and presence thinning performed similarly well, both producing better model discrimination than target group background selection, and better model calibration than models without correction. In the simulation, background thickening performed better than presence thinning when the number of simulated presence locations was low, and vice versa. We discuss drawbacks to target group background selection, why background thickening and presence thinning are conservative but robust sampling bias correction methods, and why background thickening is better than presence thinning for small sample sizes. Particularly, background thickening is advantageous for treating sampling bias when data are scarce because it avoids discarding presence records. [ABSTRACT FROM AUTHOR]

Responses to climate change have often been found to lag behind the rate of warming that has occurred. In addition to dispersal limitation potentially restricting spread at leading range margins, the persistence of species in new and unsuitable conditions is thought to be responsible for apparent time‐lags.Soil seed banks can allow plant communities to temporarily buffer unsuitable environmental conditions, but their potential to slow responses to long‐term climate change is largely unknown. As local forest cover can also buffer the effects of a warming climate, it is important to understand how seed banks might interact with land cover to mediate community responses to climate change.We first related species‐level seed bank persistence and distribution‐derived climatic niches for 840 plant species. We then used a database of plant community data from grasslands, forests and intermediate successional habitats from across Europe to investigate relationships between seed banks and their corresponding herb layers in 2763 plots in the context of climate and land cover.We found that species from warmer climates and with broader distributions are more likely to have a higher seed bank persistence, resulting in seed banks that are composed of species with warmer and broader climatic distributions than their corresponding herb layers. This was consistent across our climatic extent, with larger differences (seed banks from even warmer climates relative to vegetation) found in grasslands.Synthesis. Seed banks have been shown to buffer plant communities through periods of environmental variability, and in a period of climate change might be expected to contain species reflecting past, cooler conditions. Here, we show that persistent seed banks often contain species with relatively warm climatic niches and those with wide climatic ranges. Although these patterns may not be primarily driven by species' climatic adaptations, the prominence of such species in seed banks might still facilitate climate‐driven community shifts. Additionally, seed banks may be related to ongoing trends regarding the spread of widespread generalist species into natural habitats, while cool‐associated species may be at risk from both short‐ and long‐term climatic variability and change. [ABSTRACT FROM AUTHOR]

Spoil heaps of surplus rock from hydropower tunnel construction negatively impact alpine landscapes unless restored. Such spoil heaps have been created for more than 100 years, but we still lack knowledge about the relative importance of compensatory mitigation (seeding and fer-tilization), spoil-heap construction method, local environ-mental factors, and regional climatic factors for restoration success. We studied the species composition of 19 alpine spoil heaps in Western Norway and their undisturbed surroundings using ordination and statistical modeling. Substrate grain size was the principal factor explaining differences in species composition between spoil heaps and their surroundings. Soil characteristics, that is, organic matter content and pH, and reutilization of topsoil were also important. Seeding and fertilization had negligible effects on restoration success. Slow recovery was observed for total vegetation cover and species richness of vascu-lar plants and lichens while bryophyte cover recovered rapidly. Lower bryophyte cover and bryophyte and vas-cular plant species richness on older than on younger spoil heaps indicated recent changes in spoil-heap construction practices that favor plant colonization. Our results indi-cate that spoil-heap design is more important for restora-tion success than compensatory mitigation. We therefore suggest spoil heaps designed with a fine-grained top sub-strate preferably from stockpiled local topsoil, with uneven surface topography that mimics natural topographic vari-ation, and recommend discontinuation of seeding and fertilization. [ABSTRACT FROM AUTHOR]

Species composition is a vital attribute of any ecosystem. Accordingly, ecological restoration often has the original, or "natural," species composition as its target. However, we still lack adequate methods for predicting the expected time to compositional recovery in restoration studies.We describe and explore a new, ordination regression‐based approach (ORBA) for predicting time to recovery that allows both linear and asymptotic (logarithmic) relationships of compositional change with time. The approach uses distances between restored plots and reference plots along the successional gradient, represented by a vector in ordination space, to predict time to recovery. Thus, the approach rests on three requirements: (a) the general form of the relationship between compositional change and time must be known; (b) a sufficiently strong successional gradient must be present and adequately represented in a species compositional dataset; and (c) a restoration target must be specified. We tested the approach using data from a boreal old‐growth forest that was followed for 18 years after experimental disturbance. Data from the first 9 years after disturbance were used to develop models, the subsequent 9 years for validation.Rates of compositional recovery in the example dataset followed the general pattern of decrease with time since disturbance. Accordingly, linear models were too optimistic about the time to recovery, whereas the asymptotic models provided more precise predictions.Synthesis and applications. Our results demonstrate that the new approach opens for reliable prediction of recovery rates and time to recovery using species compositional data. Moreover, it allows us to assess whether recovery proceeds in the desired direction and to quantitatively compare restoration speed, and hence effectiveness, between alternative management options. Our results demonstrate that the new approach opens for reliable prediction of recovery rates and time to recovery using species compositional data. Moreover, it allows us to assess whether recovery proceeds in the desired direction and to quantitatively compare restoration speed, and hence effectiveness, between alternative management options. [ABSTRACT FROM AUTHOR]