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.

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.

Hydropower is expanding globally and is regarded a key measure for mitigating climate change, but it also results in major environmental degradation, both at local scale and more widely. We can learn lessons about how restoration can be used to alleviate these problems from failures and successes in countries with a long history of hydropower development, such as Norway. Here, hydropower projects grew larger over time, and in the 1960s, the emerging environmentalist movement started to challenge hydropower developments because of their negative impacts on the environment. The Norwegian Water Resources and Energy Directorate then appointed a landscape architect who became very influential, particularly due to his skills in aesthetics and photo documentation. He developed principles for designing self-sustaining environments which he called “living nature”, and in particular proposed methods of restoring barren, unattractive, alpine spoil heaps. Later, restoration methods and goals have changed in response to new insights and the changing goals of ecological restoration. Here, we present current best practice for the alpine biome and sum up general lessons in three points: restoration can represent a sustainable, ‘third way’ in the conflict between conservation and development; including a wider group of professionals may improve restoration goals and methods, and effective use of visual communication can be a good way of gaining support for new restoration principles.

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.

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.