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Characterizing seedling stands with respect to their species proportions and co-occurring vegetation is important for monitoring the desired development of the forest stand. Related inventory information has traditionally been collected with costly field surveys and National Forest Inventory (NFI)-based models. Here, we present a novel fusion approach to combine remote sensing (RS)-based models and NFI-based models to predict seedling stand characteristics, i.e., height, density, and tending needs. We used the best linear unbiased predictor for the fusion of the NFI- and RS-based models. The NFI-based models were derived using NFI sample plots and stand features. The RS-based models were derived using airborne laser scanning and color–infrared images and separate field-measured data. NFI-based models were found to be rather unreliable (RMSE = 65%–115% for stem density and 59%–78% for height), but they were always available without the need for any additional RS data. RS-based models provided an RMSE of 41%–92% for stem density and 26%–45% for height. The fusion procedure used at the prediction stage consistently increased the accuracy of all variables of interest, but the improvements were minor. In addition, we classified the tending need in seedling stands if the height of the coniferous tree was less than 1 m compared to broadleaved trees. If we simulate the decision-making situation of tending needs, we can predict tending needs (91% user accuracy) fairly well for a stand.

The volume models that have been used in Finland for the last 40 years, while generally well thought-out, exhibit an illogical behaviour for small trees. In recent studies, tree stem form was observed to have changed in time and also involve spatial variation attributable to environmental factors. It is yet unclear how the stem taper has actually changed. To overcome these problems, we fitted a completely new set of volume and taper curve models and examined whether this change is attributable to the changes in management and environmental factors rather than to measurement errors in the previously used datasets. For the latter, we added a dataset into the analysis, which was smaller but of higher quality due to the destructive nature of the stem taper measurements. We aim at (1) developing a new non-linear variable form factor volume function that works with trees of all sizes, (2) improving the description of the variation of the stem form in time and space by including temperature sum and soil type as predictors, (3) understanding the changes in the stem form by fitting new taper curve models and (4) improving the statistical properties of the predictions by using mixed model techniques and by addressing the effect of parameter uncertainty. To assess the impact of renewing the models, we (5) predicted the mean volume and its confidence interval with each model for forest inventory data at country level. The results show that the tree stem form has a spatial trend that can be described with the temperature sum. Moreover, the changes in stem form also have a spatial trend, with largest changes in Lapland. The difference is mostly observable in the lowest part of the stem, and it is especially large in the largest pines. We conclude that environmental variables can help to improve national stem taper functions in countries with pronounced environmental gradients.

Horvitz–Thompson-like stand density estimation is a method for estimating the stand density from tree crown objects extracted from airborne laser scanning data through individual tree detection. The estimator is based on stochastic geometry and mathematical morphology of the (planar) set formed by the detected tree crowns. This set is used to approximate the detection probabilities of trees. These probabilities are then used to calculate the estimate. The method includes a tuning parameter, which needs to be known to apply the method. We present a refinement of the method to allow more general detection conditions than those of previous papers. We also present and discuss the methods for estimating the tuning parameter of the estimator using a functional k-nearest neighbors method. We test the model fitting and prediction in two spatially separate data sets and examine the plot-level accuracy of estimation. The estimator produced a 13% lower RMSE (root-mean-square error) than the benchmark method in an external validation data set. We also analyze the effects of similarity and dissimilarity of training and validation data on the results.

Climate change and the related increases in evapotranspiration threaten to make northern peatlands drier. The carbon sink function in peatlands is based on the delicate balance between the photosynthesis and decomposition. However, little is known about how existing and invading plant species will photosynthesize under drier conditions. The aim of this study is to quantify the long-term consequences of climate change-induced drying for peatland photosynthesis in the level of individual species and vegetation community. We measured the species-level photosynthesis of vascular plants and mosses characteristic for the three peatland types (rich fen, poor fen, bog) within a 16-year water level drawdown (WLD) experiment. Measurements were made in the laboratory from mesocosms collected from the field within the same day. We applied nonlinear mixed-effects models to test the impact of WLD on hyperbolic photosynthetic light response curve parameters. The model was then used to upscale photosynthesis to site-level. WLD impacted site-level photosynthesis through two mechanisms: species turnover and changes in species-level photosynthesis rate. The rich fen was the most sensitive and underwent major changes through both mechanisms; the vascular plant community shifted to woody plant dominance with higher rate of photosynthesis than the pre-treatment vegetation, and the rate of species-level photosynthesis increased significantly. The bog had a stable plant community with little change in photosynthesis, while the poor fen was an intermediate of the three peatland types. Our results suggest that vascular plants are the main drivers of site-level productivity changes, while mosses are more resistant to change. The change seems proportional to the availability of mineral nutrients, with higher nutrient status supporting vascular plant expansion.

Accumulation of secondary metabolites may exhibit developmentally regulated variation in different plant organs. Moreover, prevailing environmental conditions may interact with development-related variations in plant traits. In this study, we examined developmentally regulated variation in phenolic accumulation in the twigs of dioecious Populus tremula (L.) and how the effects of elevated temperature and ultraviolet B (UVB) radiation on growth and phenolics accumulation varied as the plants get older. In an open-field experiment, six female and six male genotypes were exposed to single and combined elevated temperature and UVB radiation treatments for three consecutive growing seasons. The concentrations of low molecular weight phenolics and condensed tannins did not show age-dependent variation in the twigs. In temperature-treated plants, diameter growth rate decreased, and concentration of condensed tannins increased as plants aged; there were no cumulative effects of elevated UVB radiation on growth and phenolic accumulation. Females maintained a higher concentration of low molecular weight phenolics throughout the experimental period; however, growth and phenolic concentration did not vary over time in females and males. Our results suggest that phenolic accumulation in perennial plants may not necessarily always exhibit age-dependent variation and the effects of elevated temperature on growth and phenolic may diminish as plants get older.

Forest management inventories assisted by airborne laser scanning (ALS) can be used to predict different forest attributes. These predictions are utilized in practical forestry, but in the case of timber assortment-specific volumes, the ALS-based predictions can be inaccurate. This causes uncertainty in harvest planning. However, ALS-based predictions can be calibrated to achieve greater accuracy with local measurements. In this study, we used ALS data and accurately positioned cut-to-length harvester measurements from Norway spruce (Picea abies (L.) Karst.) dominated clear-cuts. We fitted linear mixed-effects (LME) models with exponential correlation structure for merchantable volume and sawlog volume for 225 m2 cells. Our aim was to study the effect of local harvester measurements on the accuracy of stand level merchantable and sawlog volumes. LME-based predictions were calibrated repeatedly up to 40 times as the cutting progressed. ALS data and harvester measurements were used to predict both the random effects and residual errors for each validation unit. At best, relative root mean square error (RMSE%) of initial predictions of 15.4 per cent for merchantable volume and 22.1 per cent for sawlog volume were reduced to 4.1 and 5.3 per cent, respectively, when measurements from 40 harvested cells of size 225 m2 were used. These results suggest that spatially accurate harvester data could be utilized during harvesting to increase the accuracy of volume and timber assortment predictions.

One of the main rules of subtitling states that subtitles should be formatted and timed so that viewers have enough time to read and understand the text but also to follow the picture. In this paper we examine the factors that influence the time viewers spend looking at subtitles. We concentrate on the lexical and structural properties of subtitles. The participant group (N = 14) watched a television documentary with Russian narration and Finnish subtitles (the participants’ native language), while their eye movements were tracked. Using a linear mixed-effects model, we identified significant effects of subtitle duration and character count on the time participants spent looking at the subtitles. The model also revealed significant inter-individual differences, despite the fact that the participant group was seemingly homogeneous. The findings underline the complexity of subtitled audiovisual material as a stimulus of cognitive processing. We provide a starting point for more comprehensive modelling of the factors involved in gaze behaviour when watching subtitled content. Lay summary Subtitles have become a popular method for watching foreign series and films even in countries that have traditionally used dubbing in this regard. Because subtitles are visible to the viewer a short, limited time, they should be composed so that they are easy to read, and that the viewer has time to also follow the image. Nevertheless, the factors that have impact the time it takes to read a subtitle is not very well known. We wanted to find out what makes people who are watching subtitled television shows spend more time gazing at the subtitles? To answer this question, we recorded the eye movements of 14 participants when they were watching a short, subtitled television documentary. We created a statistical model of the gaze behavior from the eye movement data and found that both the length of the subtitle and the time the subtitle is visible are separate contributing factors. We also discovered large differences between individual viewers. Our conclusion is that people process subtitled content in very different ways, but there are some common tendencies. Our model can be seen as solid starting point for comprehensive modelling of gaze behavior of people watching subtitled audiovisual material.

Bush encroachment affects ~45 million ha of Namibia and, without appropriate restoration measures, it negatively affects rangeland productivity and biodiversity. Thinning is a common method to counteract bush encroachment. The thinning strategy applied in north-central Namibia was assessed to examine how effective it has been in reducing bush encroachment. Trees/shrubs were selectively thinned manually, targeting all height classes, except individuals with stem diameters ≥18 cm. We investigated the effects on the vegetation and soil properties using surveys on three freehold farms (in 2016 and 2017) in bush-encroached and previously thinned habitats. Our results revealed significant differences in the mean total nitrogen (TN) content between the treatments; thinned areas had higher TN content which would be beneficial for fast-growing grasses. In the thinned plots, the occurrence probability of red umbrella thorn (Vachellia reficiens Warwa) was significantly reduced, indicating that it was the most harvested species; and umbrella thorn (Vachellia tortilis (Burch.) Brenan spp. heteracantha) was increased, indicating that it favoured reduced densities of dominant species. Natural regeneration was rapid; the tree/shrub abundance in the 0–1-m height class in the thinned area surpassed those in the non-thinned by 34 per cent, ~7.2 years since thinning. Thinning significantly reduced tree/shrub abundances of the 1–3- and >3-m height classes, which was still evident 7.2 years since thinning. Based upon the generalized linear mixed-effects model, tree/shrub counts between treatments may equalize in ~14 and 15 years for the 1–3- and >3-m height classes, respectively. Thinning was effective in reducing tree/shrub abundances and can be used to restore wildlife habitat on the Namibian farmland: however, post-thinning management is required to maintain an open savannah vegetation structure as the 0–1-m height class cohort will eventually grow into mature trees/shrubs.

The behavior of organisms can be subject to human‐induced selection such as that arising from fishing. Angling is expected to induce mortality on fish with bold and explorative behavior, which are behaviors commonly linked to a high standard metabolic rate. We studied the transgenerational response of brown trout (Salmo trutta) to angling‐induced selection by examining the behavior and metabolism of 1‐year‐old parr between parents that were or were not captured by experimental fly fishing. We performed the angling selection experiment on both a wild and a captive population, and compared the offspring for standard metabolic rate and behavior under predation risk in common garden conditions. Angling had population‐specific effects on risk taking and exploration tendency, but no effects on standard metabolic rate. Our study adds to the evidence that angling can induce transgenerational responses on fish personality. However, understanding the mechanisms of divergent responses between the populations requires further study on the selectivity of angling in various conditions., Angling‐induced divergent responses on a wild and a hatchery population of brown trout, making hatchery population juveniles from low‐vulnerability parents more explorative than offspring from high‐vulnerability parents, but having no effect on juveniles from the wild population. Our results imply that angling selection may lead to accumulating behavioral changes across generations. Whether this will manifest as increased shyness, as has been predicted, can depend on the background of the population or the ecological conditions during angling.

Accumulation of certain phenolics is a well‐known response of plants to enhanced UVB radiation (280–315 nm), but few experiments have compared the relative importance of different phenolic groups for UVB resilience. To study how an altered phenolic profile affects the responses and resilience of silver birch (Betula pendula) to enhanced UVB, we used RNA interference (RNAi) targeting dihydroflavonol reductase (DFR), anthocyanidin synthase (ANS), or anthocyanidin reductase (ANR) to change the accumulation of phenolics. The unmodified control line and RNAi‐modified plants were grown for 51 days under ambient or +32% enhanced UVB dose in a greenhouse. RNAi greatly affected phenolic profile and plant growth. There were no interactive effects of RNAi and UVB on growth or photosynthesis, which indicates that the RNAi and unmodified control plants were equally resilient. UVB enhancement led to an accumulation of foliar flavonoids and condensed tannins, and an increase in the density of stem glands and glandular trichomes on upper leaf surfaces in both the control and RNAi‐modified plants. Our results do not indicate a photoprotective role for condensed tannins. However, decreased growth of high‐flavonoid low‐tannin DFRi and ANRi plants implies that the balance of flavonoids and condensed tannins might be important for normal plant growth.

In many countries, airborne laser scanning (ALS) inventories are implemented to produce predictions for stand-level forest attributes. Nevertheless, mature stands are usually field-visited prior to clear-cutting, so some measurements can be conducted on these stands to calibrate the ALS-based predictions. In this paper, we developed a seemingly unrelated multivariate mixed-effects model system that includes component models for basal area, merchantable volume, and sawlog volume for 225 m2 cells. We used ALS data and accurately positioned cut-to-length harvester observations from clear-cut stands dominated by Norway spruce (Picea abies (L.) Karst.). Our aim was to study the effect of 1–10 local angle-gauge basal area measurements on the accuracy of predicted merchantable and sawlog volumes. A seemingly unrelated mixed-effect model system was fitted to estimate cross-model correlations in residuals and random effects, which were then utilized to predict all the random effects of the system for calibrated stand-level predictions. The 10 angle-gauge plots decreased the relative root mean square error (RMSE%) of the basal area and merchantable volume predictions from 16.8% to 10.5% and from 15.8% to 11.9%, respectively. Cross-model correlations of the stand effects of sawlog volume with the other responses were low; therefore, the initial RMSE% of ∼22% was decreased only marginally by the calibration.

Bush encroachment affects much of the Namibian woodland landscape, causing significant loss of open savannah habitat and farm profits. Thinning of the trees/shrubs is recommended; however, research is required to identify the overall efficacy and effects of this method on the woodland habitat. We aimed to examine the effect of the thinning strategy applied on the vegetation structure of encroaching tree/shrub species, as well as the sighting lines of the habitat. Vegetation surveys were done on three freehold farms in north-central Namibia. The study utilised a combination of a blocked and split-plot study design: each block consisted of a pair of thinned and non-thinned plots with multiple subplots. Thinned plots had been manually thinned, with a post-thinning age of three years or more. Results revealed that tree/shrub abundance differed between species; thinned areas had the least abundance and overall species-treatment interactions were significant. Thinning caused a significant reduction in overall tree/shrub densities, settling within the recommended range for the area. Thinning also significantly reduced the average tree/shrub height, canopy area, medium-sized trees/shrubs, and increased sighting lines. This confirms a bush encroachment mitigation strategy that favours grass cover, and wildlife that rely on longer sighting lines for safety or when hunting.

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Despite active research, antiherbivore activity of specific plant phenolics remains largely unresolved. We constructed silver birch (Betula pendula) lines with modified phenolic metabolism to study the effects of foliar flavonoids and condensed tannins on consumption and growth of larvae of a generalist herbivore, the autumnal moth (Epirrita autumnata). We conducted a feeding experiment using birch lines in which expression of dihydroflavonol reductase (DFR), anthocyanidin synthase (ANS) or anthocyanidin reductase (ANR) had been decreased by RNA interference. Modification-specific effects on plant phenolics, nutrients and phenotype, and on larval consumption and growth were analyzed using uni- and multivariate methods. Inhibiting DFR expression increased the concentration of flavonoids at the expense of condensed tannins, and silencing DFR and ANR decreased leaf and plant size. E. autumnata larvae consumed on average 82% less of DFRi plants than of unmodified controls, suggesting that flavonoids or glandular trichomes deter larval feeding. However, larval growth efficiency was highest on low-tannin DFRi plants, indicating that condensed tannins (or their monomers) are physiologically more harmful than non-tannin flavonoids for E. autumnata larvae. Our results show that genetic manipulation of the flavonoid pathway in plants can effectively be used to produce altered phenolic profiles required for elucidating the roles of low-molecular weight phenolics and condensed tannins in plant–herbivore relationships, and suggest that phenolic secondary metabolites participate in regulation of plant growth.

Tree growth is expected to be responsive to climatic drivers across a spectrum of temporal scales, ranging from yearly growth to daily water use and photosynthesis. Automatic dendrometers offer the potential to provide continuous high-resolution measurements of tree radius changes. The signal recorded contains three components: (1) a long-term seasonal growth component, (2) a mid-term component representing swelling after rainfall and subsequent drying and (3) daily cycles of water-uptake related to tree transpiration. For 91 trees at 4 sites (Picea abies: 58, Pinus cembra: 17, Fagus sylvatica: 14, Pinus sylvestris: 2) monitored in Austria between 2012 and 2015, we simultaneously modelled these three processes using a hierarchical nonlinear mixed-effects model represented by two logistic growth curves. The focus was on the mid-term and daily component, and therefore long-term growth that is typically modelled by including tree size, competition or site variables was represented by random effects only. Both mid-term and short-term components were species-specific. In general, P. cembra and F. sylvatica were less sensitive to climate variables than P. abies. For all species, the mid-term component was best represented using a 14-day moving average difference between rainfall and potential evapotranspiration, a 24-h moving average of precipitation and its 1–3 days lags, a 24-h moving average temperature and its 1–3 days lags. The daily cycles of water uptake were best related to hourly humidity and its 3-h lag, and interactions with the 14-day moving average difference between rainfall and potential evapotranspiration accounted for attenuating cycles after rainy events and increasing cycles in dry periods.

We quantified the role of spatially varying vegetation composition in seasonal and interannual changes in a boreal bog’s CO2 uptake. We divided the spatially heterogeneous site into six microform classes based on plant species composition and measured their net ecosystem exchange (NEE) using chamber method over the growing seasons in 2012–2014. A nonlinear mixed-effects model was applied to assess how the contributions of microforms with different vegetation change temporally, and to upscale NEE to the ecosystem level to be compared with eddy covariance (EC) measurements. Both ecosystem respiration (R) and gross photosynthesis (PG) were the largest in high hummocks, 894–964 (R) and 969–1132 (PG) g CO2 m−2 growing season−1, and decreased toward the wetter microforms. NEE had a different spatial pattern than R and PG; the highest cumulative seasonal CO2 sink was found in lawns in all years (165–353 g CO2 m−2). Microforms with similar wetness but distinct vegetation had different NEE, highlighting the importance of vegetation composition in regulating CO2 sink. Chamber-based ecosystem-level NEE was smaller and varied less interannually than the EC-derived estimate, indicating a need for further research on the error sources of both methods. Lawns contributed more to ecosystem-level NEE (55–78%) than their areal cover within the site (21.5%). In spring and autumn, lawns had the highest NEE, whereas in midsummer differences among microforms were small. The contributions of all microforms to the ecosystem-level NEE varied seasonally and interannually, suggesting that spatially heterogeneous vegetation composition could make bog CO2 uptake temporally more stable.

Errors in individual tree detection and delineation affect diameter distribution predictions based on crown attributes extracted from the detected trees. We develop a methodology for circumventing these problems. The method is based on matching cumulative distribution functions of field measured tree diameter distributions and crown radii distributions extracted from airborne laser scanning data through individual tree detection presented by Vauhkonen and Mehtatalo (2015). In this study, empirical distribution functions and a monotonic, nonlinear model curve are introduced. Tree crown radius distribution produced by individual tree detection is corrected by a method taking into account that all trees cannot be detected. The evaluation is based on the ability of the developed model sequence to predict quadratic mean diameter and total basal area. The studied data consists of 36 field plots in a typical boreal managed forest area in eastern Finland. The suggested enhancements to the model sequence produce improved results in most of the test cases. Most notably, in leaveone-out cross-validation experiments the modified models improve RMSE of basal area 13% in the full data and RMSE of quadratic mean diameter and basal area 69% and 11%, respectively, in pure pine plots. Better modeling of the crown radius distribution and improved matching between crown radii and stem diameters add the operational premises of the full distribution matching.

Northern peatlands form a major soil carbon (C) stock. With climate change, peatland C mineralization is expected to increase, which in turn would accelerate climate change. A particularity of peatlands is the importance of soil aeration, which regulates peatland functioning and likely modulates the responses to warming climate. Our aim is to assess the impacts of warming on a southern boreal and a sub-arctic sedge fen carbon dioxide (CO2) exchange under two plausible water table regimes: wet and moderately dry. We focused this study on minerotrophic treeless sedge fens, as they are common peatland types at boreal and (sub)arctic areas, which are expected to face the highest rates of climate warming. In addition, fens are expected to respond to environmental changes faster than the nutrient poor bogs. Our study confirmed that CO2 exchange is more strongly affected by drying than warming. Experimental water level draw-down (WLD) significantly increased gross photosynthesis and ecosystem respiration. Warming alone had insignificant impacts on the CO2 exchange components, but when combined with WLD it further increased ecosystem respiration. In the southern fen, CO2 uptake decreased due to WLD, which was amplified by warming, while at northern fen it remained stable. As a conclusion, our results suggest that a very small difference in the WLD may be decisive, whether the C sink of a fen decreases, or whether the system is able to adapt within its regime and maintain its functions. Moreover, the water table has a role in determining how much the increased temperature impacts the CO2 exchange. This article is protected by copyright. All rights reserved.

In an Area Based Approach (ABA) to forest inventories using Airborne Laser Scanning (ALS) data, the sample plot size may vary or the cell size may differ from the plot size. Although this resolution mismatch may cause bias and increase in prediction error, it has not been thoroughly studied. The aim of this study was to clarify the meaning of resolution dependence in ABA, and to further identify its causal factors and quantify their effects. In general, a number of factors contribute to resolution dependence in ABA forest inventories, including the varying point density of the ALS data, the type of response variable, how the predictor variables are computed, and the properties of the prediction model. For quantification, we used field plots with mapped tree locations, which enabled the generation of different sized sample plots inside a larger plot. Plot level above ground biomass (AGB) was the response variable employed in all the models. The error rate seemed to increase when the prediction plots were larger than the fitting plots, and vice versa. The maximum BIAS was 1.50% and the maximum change of RMSE compared to its value in native resolution was 0.97% when there was a 4-fold difference in resolution. This indicates that the resolution effect is small in most real-world use cases, however, resolution effect should be carefully considered in ALS-assisted large area inventories that target unbiased estimates of forest parameters.

The increasing availability of wall-to-wall remote sensing datasets in combination with accurate field data enables the mapping of different ecosystem services more accurately and over larger areas than before. The provision of wild berries is an essential ecosystem service, and berries are the most used non-wood forest products in Nordic countries. The aim of the study was to 1) develop general prediction models for bilberry and cowberry yield based on metrics derived from airborne laser scanning (ALS) data and other existing wall-to-wall data and 2) to identify laser-based structural features of forests that can be linked to locations of the highest berry yields. We used the indirect approach where the correlation between forest structure described by the ALS data and the berry yields are utilized. Berry data collected in the Swedish National Forest Inventory (NFI) 2007–2016 were used for training the models and ALS data from 2009 to 2014 from the national ALS campaign of Sweden. Berry yields were modelled using generalised linear mixed models (GLMMs), and forest structural differences were demonstrated in histograms of presence/absence data. The ALS-based canopy cover was an important variable both in bilberry and cowberry models. Other significant variables were ALS-based height variance, shrub cover, height above sea level, slope, soil wetness and terrain ruggedness, satellite-based species-specific volume and percentage, seasonality of temperature and precipitation and annual precipitation, inventory year, soil type and land use class. In addition, the time difference between the inventory day and the Julian day when berries were expected to be ripe showed a 1.5% decrease for bilberry and a 1.1% decrease for cowberry yield per day during the season. The highest bilberry yield was identified in forests with a canopy cover of 50% and the highest cowberry yield in forests with a canopy cover close to zero. The canopy height of 15 m reflected the highest bilberry yield, whereas a canopy height close to 0 m resulted in the highest cowberry yield. The shrub cover was close to zero both with highest bilberry and cowberry yields. This is the first study combining ALS metrics with other wall-to-wall variables and NFI field data to model bilberry and cowberry yields. Prediction models can be used to produce maps showing the most potential locations for berry picking. Further, the models may, in the future, be imported into forest planning systems to obtain stand-level prognoses of berry yield development under different forest management strategies.

Objective. Heart rate (HR) monitoring provides a convenient and inexpensive way to predict energy expenditure (EE) during physical activity. However, there is a lot of variation among individuals in the EE-HR relationship, which should be taken into account in predictions. The objective is to develop a model that allows the prediction of EE based on HR as accurately as possible and allows an improvement of the prediction using calibration measurements from the target individual. Approach. We propose a nonlinear (logistic) mixed model for EE and HR measurements and an approach to calibrate the model for a new person who does not belong to the dataset used to estimate the model. The calibration utilizes the estimated model parameters and calibration measurements of HR and EE from the person in question. We compare the results of the logistic mixed model with a simpler linear mixed model for which the calibration is easier to perform. Main results. We show that the calibration is beneficial already with only one pair of measurements on HR and EE. This is an important benefit over an individual-level model fitting, which requires a larger number of measurements. Moreover, we present an algorithm for calculating the confidence and prediction intervals of the calibrated predictions. The analysis was based on up to 11 pairs of EE and HR measurements from each of 54 individuals of a heterogeneous group of people, who performed a maximal treadmill test. Significance. The proposed method allows accurate energy expenditure predictions based on only a few calibration measurements from a new individual without access to the original dataset, thus making the approach viable for example on wearable computers.