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Background OSA is highly prevalent and characterised by abnormal respiration during sleep. This large, population-based study aimed to investigate the associations between OSA and lung function in subjects aged 50–64 years.Method The population-based Swedish CArdioPulmonary bioimage Study includes information on anthropometry, comorbidities and spirometry. The current analysis included data from three centres (Gothenburg, Umeå and Uppsala) on whole-night respiratory polygraphy as a meta-analysis examining the overall effect size of lung function on sleep apnoea severity, expressed as ß-coefficient after stratifying for sex and adjusting for age, waist circumference and smoking status.Results Data from 9016 participants (54% women, age 58±4 years, body mass index 27±4 kg/m2) with sleep recordings of good quality were included in the final analysis. Forced expiratory volume during 1 s (FEV1) (ß=−0.10 (95% CI −0.16 to −0.03)), forced vital capacity (FVC) (−0.15 (−0.21 to −0.10)) and diffusion capacity for carbon monoxide (DLCO) (−0.08 (−0.10 to −0.05)) were all negatively associated with the oxygen desaturation index (ODI) and also with per cent of registration with nocturnal oxygen saturation

Abstract Background Breathlessness is common in the population and can be related to a range of medical conditions. We aimed to evaluate the burden of breathlessness related to different medical conditions in a middle-aged population. Methods Cross-sectional analysis of the population-based Swedish CArdioPulmonary bioImage Study of adults aged 50–64 years. Breathlessness (modified Medical Research Council [mMRC] ≥ 2) was evaluated in relation to self-reported symptoms, stress, depression; physician-diagnosed conditions; measured body mass index (BMI), spirometry, venous haemoglobin concentration, coronary artery calcification and stenosis [computer tomography (CT) angiography], and pulmonary emphysema (high-resolution CT). For each condition, the prevalence and breathlessness population attributable fraction (PAF) were calculated, overall and by sex, smoking history, and presence/absence of self-reported cardiorespiratory disease. Results We included 25,948 people aged 57.5 ± [SD] 4.4; 51% women; 37% former and 12% current smokers; 43% overweight (BMI 25.0–29.9), 21% obese (BMI ≥ 30); 25% with respiratory disease, 14% depression, 9% cardiac disease, and 3% anemia. Breathlessness was present in 3.7%. Medical conditions most strongly related to the breathlessness prevalence were (PAF 95%CI): overweight and obesity (59.6–66.0%), stress (31.6–76.8%), respiratory disease (20.1–37.1%), depression (17.1–26.6%), cardiac disease (6.3–12.7%), anemia (0.8–3.3%), and peripheral arterial disease (0.3–0.8%). Stress was the main factor in women and current smokers. Conclusion Breathlessness mainly relates to overweight/obesity and stress and to a lesser extent to comorbidities like respiratory, depressive, and cardiac disorders among middle-aged people in a high-income setting—supporting the importance of lifestyle interventions to reduce the burden of breathlessness in the population.

Aim Heritability of cough has not yet been studied. We aimed to evaluate if individuals with cough are more likely to have offspring who develop cough, and if these associations differ by type of cough (productive/nonproductive). Methods The RHINESSA Generation Study (Respiratory Health In Northern Europe, Spain and Australia) includes 7155 parents (initially aged 30–54) answering detailed questionnaires in 2000 and 2010, and 8176 offspring ≥20 years answering similar questionnaires in 2012–2019. Chronic cough was categorised as productive or nonproductive (dry) cough. Associations between parental and offspring cough were analysed using mixed-effects logistic regression, adjusting for offspring age, sex, body mass index, smoking history, education level, current asthma, rhinitis, nocturnal gastroesophageal reflux; parent sex and smoking history; centre and family. Results Among parents with nonproductive cough, 11% of their offspring reported nonproductive cough, compared with 7% of offspring to parents without nonproductive cough, adjusted odds ratio (aOR) 1.59 (95% confidence interval 1.20–2.10). Among parents with productive cough, 14% of their offspring reported productive cough, compared with 11% of offspring to parents without productive cough, aOR 1.34 (1.07–1.67). No associations were found between parent productive cough–offspring nonproductive cough, nor between parent nonproductive cough–offspring productive cough. Conclusions Parents with chronic cough are more likely to have offspring with chronic cough independent of parental asthma, suggesting cough to be a separate heritable trait. The type of cough is important, as the nonproductive cough in parent associates only with nonproductive cough in offspring, and the same applied for productive cough.

Satellite-based inventories of bark beetle attacks are increasingly used for detecting and monitoring infested forest at the landscape scale. The Normalized Distance Red & SWIR index is one of few indices that have shown higher accuracies than commonly used vegetation indices. In this study, the temporal changes of the distance red swir (ΔDRS) index were analyzed, validated and applied to multi-temporal Sentinel-2 images covering one tile of 110 x 110 km2. The main purpose was to assess the applicability of a new ΔDRS vegetation index to detect spruce forest after bark beetle (Ips typographus) attacks. Harvester data from a private forest company were used to validate the method. The normalized DRS index has previously been developed and tested at test site level, while this study explored and demonstrated the use of ΔDRS in an applied context on a larger scale. Water and chlorophyll induced changes and different disturbances were effectively identified across the landscape. A linear-discriminant analysis was used to classify 274 clusters as attacked and healthy forest, with an overall accuracy of 78%. The largest ΔDRS values in our study (>0.06) corresponded well to clear-cuts, and all 172 clear-cuts were correctly classified. We conclude that the ΔDRS index has a potential to map vegetation changes related to water and chlorophyll changes in the Scandinavian forests and that it can be useful to identify bark beetle-infested forest within 1 year after the attacks and clear-cuts.

Objectives To explore the relationship between physical activity over a 10-year period and current symptoms of insomnia, daytime sleepiness and estimated sleep duration in adults aged 39–67.Design Population-based, multicentre cohort study.Setting 21 centres in nine European countries.Methods Included were 4339 participants in the third follow-up to the European Community Respiratory Health Survey (ECRHS III), who answered questions on physical activity at baseline (ECRHS II) and questions on physical activity, insomnia symptoms, sleep duration and daytime sleepiness at 10-year follow-up (ECRHS III). Participants who reported that they exercised with a frequency of at least two or more times a week, for 1 hour/week or more, were classified as being physically active. Changes in activity status were categorised into four groups: persistently non-active; became inactive; became active; and persistently active.Main outcome measures Insomnia, sleep time and daytime sleepiness in relation to physical activity.Results Altogether, 37% of participants were persistently non-active, 25% were persistently active, 20% became inactive and 18% became active from baseline to follow-up. Participants who were persistently active were less likely to report difficulties initiating sleep (OR 0.60, 95% CI 0.45–0.78), a short sleep duration of ≤6 hours/night (OR 0.71, 95% CI 0.59–0.85) and a long sleep of ≥9 hours/night (OR 0.53, 95% CI 0.33–0.84) than persistently non-active subjects after adjusting for age, sex, body mass index, smoking history and study centre. Daytime sleepiness and difficulties maintaining sleep were not related to physical activity status.Conclusion Physically active people have a lower risk of some insomnia symptoms and extreme sleep durations, both long and short.

Abstract Background Previous research suggests an association between road traffic noise and obesity, but current evidence is inconclusive. The aim of this study was to assess the association between nocturnal noise exposure and markers of obesity and to assess whether sleep disturbance might be a mediator in this association. Methods We applied data from the Respiratory Health in Northern Europe (RHINE) cohort. We used self-measured waist circumference (WC) and body mass index (BMI) as outcome values. Noise exposure was assessed as perceived traffic noise in the bedroom and/or the bedroom window’s location towards the street. We applied adjusted linear, and logistic regression models, evaluated effect modifications and conducted mediation analysis. Results Based on fully adjusted models we found that women, who reported very high traffic noise levels in bedroom, had 1.30 (95% CI 0.24–2.37) kg/m2 higher BMI and 3.30 (95% CI 0.39–6.20) cm higher WC compared to women, who reported no traffic noise in the bedroom. Women who reported higher exposure to road traffic noise had statistically significant higher odds of being overweight and have abdominal obesity with OR varying from 1.15 to 1.26 compared to women, who reported no traffic noise in the bedroom. For men, the associations were rather opposite, although mostly statistically insignificant. Furthermore, men, who reported much or very much traffic noise in the bedroom, had a statistically significantly lower risk of abdominal obesity. Sleep disturbance fully or partially mediated the association between noise in bedroom and obesity markers among women. Conclusion Our results suggest that self-reported traffic noise in the bedroom may be associated to being overweight or obese trough sleep disturbance among women, but associations were inconclusive among men.

Remotely sensed data are frequently used for predicting and mapping ecosystem characteristics, and spatially explicit wall-to-wall information is sometimes proposed as the best possible source of information for decision-making. However, wall-to-wall information typically relies on model-based prediction, and several features of model-based prediction should be understood before extensively relying on this type of information. One such feature is that model-based predictors can be considered both unbiased and biased at the same time, which has important implications in several areas of application. In this discussion paper, we first describe the conventional model-unbiasedness paradigm that underpins most prediction techniques using remotely sensed (or other) auxiliary data. From this point of view, model-based predictors are typically unbiased. Secondly, we show that for specific domains, identified based on their true values, the same model-based predictors can be considered biased, and sometimes severely so.We suggest distinguishing between conventional model-bias, defined in the statistical literature as the difference between the expected value of a predictor and the expected value of the quantity being predicted, and design-bias of model-based estimators, defined as the difference between the expected value of a model-based estimator and the true value of the quantity being predicted. We show that model-based estimators (or predictors) are typically design-biased, and that there is a trend in the design-bias from overestimating small true values to underestimating large true values. Further, we give examples of applications where this is important to acknowledge and to potentially make adjustments to correct for the design-bias trend. We argue that relying entirely on conventional model-unbiasedness may lead to mistakes in several areas of application that use predictions from remotely sensed data.

Background Interstitial lung abnormalities (ILA) are incidental findings on chest computed tomography (CT). These patterns can present at an early stage of fibrotic lung disease. Our aim was to estimate the prevalence of ILA in the Swedish population, in particular in never-smokers, and find out its association with demographics, comorbidities and symptoms. Methods Participants were recruited to the Swedish CArdioPulmonary BioImage Study (SCAPIS), a population-based survey including men and women aged 50–64 years performed at six university hospitals in Sweden. CT scan, spirometry and questionnaires were performed. ILA were defined as cysts, ground-glass opacities, reticular abnormality, bronchiectasis and honeycombing. Findings Out of 29 521 participants, 14 487 were never-smokers and 14 380 were men. In the whole population, 2870 (9.7%) had ILA of which 134 (0.5%) were fibrotic. In never-smokers, the prevalence was 7.9% of which 0.3% were fibrotic. In the whole population, age, smoking history, chronic bronchitis, cancer, coronary artery calcium score and high-sensitive C-reactive protein were associated with ILA. Both ILA and fibrotic ILA were associated with restrictive spirometric pattern and impaired diffusing capacity of the lung for carbon monoxide. However, individuals with ILA did not report more symptoms compared with individuals without ILA. Interpretation ILA are common in a middle-aged Swedish population including never-smokers. ILA may be at risk of being underdiagnosed among never-smokers since they are not a target for screening.

The estimation of species composition and species-specific stem volumes are critical components of many forest inventories. The use of airborne laser scanning with multiple spectral channels may prove instrumental for the cost-efficient retrieval of these forest variables. In this study, we scanned a boreal forest using two channels: 532 nm (green) and 1064 nm (near infrared). The data was used in a two-step methodology to (1) classify species, and (2) estimate species-specific stem volume at the level of individual tree crowns. The classification of pines, spruces and broadleaves involved linear discriminant analysis (LDA) and resulted in an overall accuracy of 91.1 % at the level of individual trees. For the estimation of stem volume, we employed species-specific k-nearest neighbors models and evaluated the performance at the plot level for 256 field plots located in central Sweden. This resulted in root-mean-square errors (RMSE) of 36 m3/ha (16 %) for total volume, 40 m3/ha (27 %) for pine volume, 32 m3/ha (48 %) for spruce volume, and 13 m3/ha (87 %) for broadleaf volume. We also simulated the use of a monospectral near infrared (NIR) scanner by excluding features based on the green channel. This resulted in lower overall accuracy for the species classification (86.8 %) and an RMSE of 41 m3/ha (18 %) for the estimation of total stem volume. The largest difference when only the NIR channel was used was the difficulty to accurately identify broadleaves and estimate broadleaf stem volume. When excluding the green channel, RMSE for broadleaved volume increased from 13 to 26 m3/ha. The study thus demonstrates the added benefit of the green channel for the estimation of both species composition and species-specific stem volumes. In addition, we investigated how tree height influences the results where shorter trees were found to be more difficult to classify correctly.

Background Epidemiological studies have shown that impaired lung function is common and associated with increased risk of cardiovascular disease. Increased levels of several inflammatory and cardiovascular disease-related plasma proteins have been associated with impaired lung function. The aim was to study the association between plasma proteomics and forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVC ratio. Methods We used a discovery and replication approach in two community-based cohorts, EpiHealth and the Malmö Offspring Study (total n=2874), to cross-sectionally study 242 cardiovascular disease- and metabolism-linked proteins in relation to FEV1, FVC (both % predicted) and FEV1/FVC ratio. A false discovery rate of 5% was used as the significance threshold in the discovery cohort. Results Plasma fatty acid-binding protein 4, interleukin-1 receptor antagonist, interleukin-6 and leptin were negatively associated with FEV1 and paraoxonase 3 was positively associated therewith. Fatty acid-binding protein 4, fibroblast growth factor 21, interleukin-1 receptor antagonist, interleukin-6 and leptin were negatively associated with FVC and agouti-related protein, insulin-like growth factor-binding protein 2, paraoxonase 3 and receptor for advanced glycation end products were positively associated therewith. No proteins were associated with FEV1/FVC ratio. A sensitivity analysis in EpiHealth revealed only minor changes after excluding individuals with known cardiovascular disease, diabetes or obesity. Conclusions Five proteins were associated with both FEV1 and FVC. Four proteins associated with only FVC and none with FEV1/FVC ratio, suggesting associations mainly through lung volume, not airway obstruction. However, additional studies are needed to investigate underlying mechanisms for these findings.

In sustainable forest resource management, establishing forest conservation areas is important to maintain forest biodiversity. However, assessing the conservation value of forests is challenging because the target areas are often both large and remote. We explored using dense airborne laser scanning (ALS) data to estimate conservation values. Field data were collected at sites in Sweden for standing deadwood (S trees), laying deadwood (L trees), and trees considered particularly important for conserving biodiversity (N trees), and forest conservation values were determined using a commonly employed method in the field. A template matching method was then used to detect L, S and N trees from ALS data. L trees were identified from linear features in the point cloud above the ground, with a 52 % detection error rate. S and N trees were identified from unusually small or large crown diameters, with 71 % and 83 % error rates, respectively. We also tested the relationships between the three types of indicator tree, their summed values and the field inventory-assessed conservation values. Regressions between the assessed conservation values and ALS indicators were most robust comparing the three test sites when using the summed number of L, S, and N trees. A wall-to-wall map covering a 3 km × 4 km area was generated using Kernel density estimation of the summed number of ALS-derived indicators, to represent relative conservation values. The map was validated using 10 1-ha plots, and yielded an R2 value of 0.6 for predicted conservation values at the plot level. We conclude that ALS data can be used to map forest conservation values and inform decisions about which forests should be used for timber production and which should be set aside as conservation areas. The maps could also be used as a data source for habitat analysis.

Objective: To investigate markers of premature menopause (

Abstract Preliminary findings suggest that pets may impact the owner’s sleep. By using data from the Swedish CArdioPulmonary bIoimage Study (SCAPIS) cohort, we aimed to investigate the association of pet ownership with the following self-reported sleep outcomes in 3788 to 4574 participants: (i) achieving the recommended daily sleep duration for adults (i.e., at least 7 h per day); (ii) sleep quality as measured by the Pittsburgh Sleep Quality Index (a score of > 5 indicating poor sleep quality); and (iii) difficulty falling or staying asleep. Sleep metrics were not associated with pet ownership, dog ownership, and dog walking when controlling the logistic regression for possible confounders (e.g., shift work, lack of social interaction, and chronic stress). In contrast, cat ownership was associated with a higher odds ratio of failing to achieve the recommended duration of 7 h of sleep per day (adjusted odds ratio [95% CI]:1.18 [1.02, 1.37] versus non-cat owners). Our findings suggest that certain pet groups might have a more significant impact on the owner’s sleep than others. As the observed association between cat ownership and short sleep duration might be a chance finding, this observation should be seen as hypothesis-generating only.

Abstract Background Congenital chloride diarrhea (CLD; OMIM 214700) is a rare autosomal recessive disorder caused by pathogenic variations in the solute carrier family 26 member A3 (SLC26A3) gene. Without salt substitution, this chronic diarrheal disorder causes severe dehydration and electrolyte disturbances. Homozygous variants in the nearby gene SLC26A4 disrupt anion exchange in the inner ear and the thyroid, causing Pendred syndrome (PDS; OMIM 274600), which is the most frequent form of syndromic deafness. Case presentation We report an unusual co-occurrence of two rare homozygous mutations in both the SLC26A3 and SLC26A4 genes, causing a rare combination of both CLD and PDS in two siblings. Although the clinical pictures were typical, the combined loss of these anion transporters might modulate the risk of renal injury associated with CLD. Conclusions Familial presentation of two rare autosomal recessive disorders with loss of function of different SLC26 anion transporters is described. Independent homozygous variants in the SLC26A3 and SLC26A4 genes cause CLD and PDS in siblings, shedding light on co-occurrence of rare recessive traits in the progeny of consanguineous couples.

Abstract Habitat suitability models (HSM) based on remotely sensed data are useful tools in conservation work. However, they typically use species occurrence data rather than robust demographic variables, and their predictive power is rarely evaluated. These shortcomings can result in misleading guidance for conservation. Here, we develop and evaluate a HSM based on correlates of long‐term breeding success of an open nest building boreal forest bird, the Siberian jay. In our study site in northern Sweden, nest failure of this permanent resident species is driven mainly by visually hunting corvids that are associated with human settlements. Parents rely on understory nesting cover as protection against these predators. Accordingly, our HSM includes a light detection and ranging (LiDAR) based metric of understory density around the nest and the distance of the nest to the closest human settlement to predict breeding success. It reveals that a high understory density 15–80 m around nests is associated with increased breeding success in territories close to settlements (

Background: The premenstrual syndrome (PMS) causes clinically relevant psychological and physical symptoms in up to 20% of women of reproductive age. To date, no studies have investigated the relationship between PMS and residential surrounding greenspace, although a green living environment has been reported to have beneficial associations with overall and reproductive health. Objective: To investigate whether lifelong exposure to residential surrounding greenspace is associated with PMS and whether such an association is mediated by BMI, air pollution or physical activity. Methods: This study used data collected in 2013–2015 from 1069 Scandinavian women aged 18–49 years, participating in RHINESSA, a European multi-centre and population-based cohort. Satellite-derived Normalised Difference Vegetation Index was used as a proxy of greenspace. Presence of eight common PMS symptoms and their sum (PMS symptom count) were used as outcomes. The associations were assessed by adjusted multilevel logistic and negative binomial regressions. Subsequently we carried out mediation analyses for physical activity, BMI and air pollution exposure. Results: Higher exposure to residential surrounding greenspace was associated with “Anxiety or tension” (Odds Ratio 0.82, 95% Confidence Interval (CI): 0.70 – 0.95), ”Depression or hopelessness” (0.84, 0.73 – 0.98), “Difficulty with sleeping” (0.82, 0.68 – 1.00) and “Breast tenderness and abdominal bloating” (0.84, 0.71 – 0.99) before or around the start of the menstrual period. There was also an association with a lower PMS symptom count (Risk Ratio: 0.94, 95% CI: 0.91 – 0.99). These associations were robust to sensitivity analyses and were not mediated by BMI, physical activity or air pollution. Conclusions: Living in greener areas may be beneficial against PMS symptoms. Further studies are needed to confirm these novel findings and to explore the underlying biological mechanisms.

BackgroundThe prevalence of obstructive sleep apnea is higher in women after menopause. This is suggested to be a result of an altered sex hormone balance but has so far not been confirmed in a population-based study.ObjectiveTo investigate whether serum concentration of estrogens and progesterone are associated with the prevalence of sleep apnea symptoms in middle-aged women of the general population.MethodsWe analyzed data from 774 women (40-67 years) from 15 study centers in seven countries participating in the second follow-up of the European Community Respiratory Health Survey (2010-2012). Multiple logistic regression models were fitted with self-reported symptoms of sleep apnea as outcomes and serum concentrations of various estrogens and progesterone as predictors. All analyses were adjusted for relevant covariates including age, BMI, education, study center, smoking habits, and reproductive age.ResultsAmong all included women, a doubling of serum concentrations of estrone and progesterone was associated with 19% respectively 9% decreased odds of snoring. Among snorers, a doubling of the concentrations of 17β-estradiol, estrone and estrone 3-sulfate was associated with 18%, 23% and 17% decreased odds of breathing irregularly, and a doubling of the progesterone concentration was further associated with 12% decreased odds of waking up suddenly with a chocking sensation. Other evaluated associations were not statistically significant.ConclusionsMiddle-aged women with low serum estrogen and progesterone levels are more likely to snore and report symptoms of obstructive sleep apnea.

Abstract Background Pneumonia is an important cause of morbidity and mortality. COPD patients using inhaled corticosteroids (ICS) have an increased risk of pneumonia, but less is known about whether ICS treatment in asthma also increases the risk of pneumonia. The aim of this analysis was to examine risk factors for hospitalisations with pneumonia in a general population sample with special emphasis on asthma and the use of ICS in asthmatics. Methods In 1999 to 2000, 7340 subjects aged 28 to 54 years from three Swedish centres completed a brief health questionnaire. This was linked to information on hospitalisations with pneumonia from 2000 to 2010 and treatment with ICS from 2005 to 2010 held within the Swedish National Patient Register and the Swedish Prescribed Drug Register. Results Participants with asthma (n = 587) were more likely to be hospitalised with pneumonia than participants without asthma (Hazard Ratio (HR 3.35 (1.97–5.02)). Other risk factors for pneumonia were smoking (HR 1.93 (1.22–3.06)), BMI 30 kg/m2 (HR 2.54 (1.39–4.67)). Asthmatics (n = 586) taking continuous treatment with fluticasone propionate were at an increased risk of being hospitalized with pneumonia (incidence risk ratio (IRR) 7.92 (2.32–27.0) compared to asthmatics that had not used fluticasone propionate, whereas no significant association was found with the use of budesonide (IRR 1.23 (0.36–4.20)). Conclusion Having asthma is associated with a three times higher risk of being hospitalised for pneumonia. This analysis also indicates that there are intraclass differences between ICS compounds with respect to pneumonia risk, with an increased risk of pneumonia related to fluticasone propionate.

The increased temporal frequency of optical satellite data acquisitions provides a data stream that has the potential to improve land cover mapping, including mapping of tree species. However, for large area operational mapping, partial cloud cover and different image extents can pose challenges. Therefore, methods are needed to assimilate new images in a straightforward way without requiring a total spatial coverage for each new image. This study shows that Bayesian inference applied sequentially has the potential to solve this problem. To test Bayesian inference for tree species classification in the boreo-nemoral zone of southern Sweden, field data from the study area of Remningstorp (58°27′18.35″ N, 13°39′8.03″ E) were used. By updating class likelihood with an increasing number of combined Sentinel-2 images, a higher and more stable cross-validated overall accuracy was achieved. Based on a Mahalanobis distance, 23 images were automatically chosen from the period of 2016 to 2018 (from 142 images total). An overall accuracy of 87% (a Cohen’s kappa of 78.5%) was obtained for four tree species classes: Betula spp., Picea abies, Pinus sylvestris, and Quercus robur. This application of Bayesian inference in a boreo-nemoral forest suggests that it is a practical way to provide a high and stable classification accuracy. The method could be applied where data are not always complete for all areas. Furthermore, the method requires less reference data than if all images were used for classification simultaneously.

Classification of tree species or species classes is still a challenge for remote sensing-based forest inventory. Operational use of Airborne Laser Scanning (ALS) data for prediction of forest variables has this far been dominated by area-based methods where laser scanning data have been used for estimation of forest variables within raster cells. Classification of tree species has however not been achieved with sufficient accuracy with area-based methods using only ALS data. Furthermore, analysis of tree species at the level of raster cells with typical size of 15 m × 15 m is not ideal in the case of mixed species stands. Most ALS systems for terrestrial mapping use only one wavelength of light. New multispectral ALS systems for terrestrial mapping have recently become operational, such as the Optech Titan system with wavelengths 1550 nm, 1064 nm, and 532 nm. This study presents an alternative type of area-based method for classification of tree species classes where multispectral ALS data are used in combination with small raster cells. In this “mini raster cell method” features for classification are derived from the intensity of the different wavelengths in small raster cells using a moving window average approach to allow for a heterogeneous tree species composition. The most common tree species in the Nordic countries are Pinus sylvestris and Picea abies, constituting about 80% of the growing stock volume. The remaining 20% consists of several deciduous species, mainly Betula pendula and Betula pubescens, and often grow in mixed forest stands. Classification was done for pine (Pinus sylvestris), spruce (Picea abies), deciduous species and mixed species in middle-aged and mature stands in a study area located in hemi-boreal forest in the southwest of Sweden (N 58°27’, E 13°39’). The results were validated at plot level with the tree species composition defined as proportion of basal area of the tree species classes. The mini raster cell classification method was slightly more accurate (75% overall accuracy) than classification with a plot level area-based method (68% overall accuracy). The explanation is most likely that the mini raster cell method is successful at classifying homogenous patches of tree species classes within a field plot, while classification based on plot level analysis requires one or several heterogeneous classes of mixed species forest. The mini raster cell method also results in a high-resolution tree species map. The small raster cells can be aggregated to estimate tree species composition for arbitrary areas, for example forest stands or area units corresponding to field plots.

Greatly simplified ecosystems are often neglected for biodiversity studies. However, these simplified systems dominate in many regions of the world, and a lack of understanding of what shapes species occurrence in these systems can have consequences for biodiversity and ecosystem services at a massive scale. In Fennoscandia, ~90% of the boreal forest (~21Mha) is structurally simplified with little knowledge of how forest structural elements shape the occurrence and diversity of for example epiphytic lichens in these managed forests. One form of structural simplification is the reduction of the number and frequency of different tree species. As many lichen species have host tree preferences, it is particularly likely that this simplification has a huge effect on the lichen community in managed forests. In a 40-70 years old boreal forest in Sweden, we therefore related the occurrence and richness of all observed epiphytic lichens to the host tree species and beta and gamma lichen diversity at the forest stand level to the stand's tree species composition and stem diameter. Picea abies hosted the highest lichen richness followed by Pinus sylvestris, Quercus robur, Alnus glutinosa, Betula spp., and Populus tremula. However, P. tremula hosted twice as many uncommon species as any of the other tree species. Stand level beta and gamma diversity was twice as high on stands with four compared to one tree species, and was highest when either coniferous or deciduous trees made up 40-50% of the trees. The stem diameter was positively related to lichen richness at the tree and stand level, but negatively to beta diversity. For biodiversity, these findings imply that leaving a few trees of a different species during forest thinning is unlikely as effective as combining life-boat trees for endangered species with an even tree species mixture.

ObjectiveTo evaluate how self-reported leisure-time physical activity (PA) changes during the adult life span, and to study how PA is related to cardiovascular risk factors using longitudinal studies.MethodsSeveral Swedish population-based longitudinal studies were used in the present study (PIVUS, ULSAM, SHE, and SHM, ranging from hundreds to 30,000 participants) to represent information across the adult life span in both sexes. Also, two cross-sectional studies were used as comparison (EpiHealth, LifeGene). PA was assessed by questionnaires on a four or five-level scale.ResultsTaking results from several samples into account, an increase in PA from middle-age up to 70 years was found in males, but not in females. Following age 70, a decline in PA was seen. Young adults reported both a higher proportion of sedentary behavior and a higher proportion high PA than the elderly. Females generally reported a lower PA at all ages. PA was mainly associated with serum triglycerides and HDL-cholesterol, but also weaker relationships with fasting glucose, blood pressure and BMI were found. These relationships were generally less strong in elderly subjects.ConclusionUsing data from multiple longitudinal samples the development of PA over the adult life span could be described in detail and the relationships between PA and cardiovascular risk factors were portrayed. In general, a higher or increased physical activity over time was associated with a more beneficial cardiovascular risk factor profile, especially lipid levels.

Study objectives Obesity is often associated with lower lung function; however, the interaction of lung function with central obesity and physical inactivity is less clear. As such, we investigated the effect on lung function of body size (body mass index (BMI)), central obesity (waist circumference (WC)) and self-reported physical activity. Methods Lung function, height, weight and WC were measured in 22 743 participants (12 791 women), aged 45–75 years, from the EpiHealth cohort study. Physical activity, gender and educational level were assessed using a questionnaire. Results Obesity, central obesity and physical inactivity were all associated with lower forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC). However, in participants without central obesity there was an increase in both FEV1 and FVC by BMI (% predicted FVC increasing from median 98%, interquartile range (IQR) 89–110% in underweight participants (BMI

Background The diagnosis of chronic obstructive pulmonary disease is based on the presence of persistent respiratory symptoms and chronic airflow limitation (CAL). CAL is based on the ratio of forced expiratory volume in 1 s to forced vital capacity (FEV1:FVC) after bronchodilation, and FEV1:FVC less than the fifth percentile is often used as a cut-off for CAL. The aim was to investigate if increasing percentiles of FEV1:FVC were associated with any respiratory symptom (cough with phlegm, dyspnoea or wheezing) in a general population sample of never-smokers and ever-smokers.Methods In a cross-sectional study comprising 15 128 adults (50–64 years), 7120 never-smokers and 8008 ever-smokers completed a respiratory questionnaire and performed FEV1 and FVC after bronchodilation. We calculated their z-scores for FEV1:FVC and defined the fifth percentile using the Global Lung Function Initiative (GLI) reference value, GLI5 and increasing percentiles up to GLI25. We analysed the associations between different strata of percentiles and prevalence of any respiratory symptom using multivariable logistic regression for estimation of OR.Results Among all subjects, regardless of smoking habits, the odds of any respiratory symptom were elevated up to the GLI15–20 strata. Among never-smokers, the odds of any respiratory symptom were elevated at GLI

ABSTRACT: Background: Emerging evidence suggests that androgens and estrogens have a role in respiratory health, but it is largely unknown whether levels of these hormones can affect lung function in adults from the general population. This study investigated whether serum dehydroepiandrosterone sulfate (DHEA-S), a key precursor of both androgens and estrogens in peripheral tissues, was related to lung function in adult women participating in the European Community Respiratory Health Survey (ECRHS). Methods: Lung function and serum DHEA-S concentrations were measured in n = 2,045 and n = 1,725 women in 1999–2002 and in 2010–2013, respectively. Cross-sectional associations of DHEA-S levels (expressed as age-adjusted z-score) with spirometric outcomes were investigated, adjusting for smoking habits, body mass index, menopausal status, and use of corticosteroids. Longitudinal associations of DHEA-S levels in 1999–2002 with incidence of restrictive pattern and airflow limitation in 2010–2013 were also assessed. Findings: Women with low DHEA-S (z-score

Aim: To investigate whether exposure to dampness and mold at home and at work induce sleep disturbances and daytime sleepiness among adults. Materials and methods: Associations between onset of sleep disturbances and dampness, mold and mold odor at home and at work were investigated in a cohort of 11,318 adults from the population in Iceland, Norway, Sweden, Denmark and Estonia. The participants answered a questionnaire at baseline and 10 years later, with questions on sleep disturbances, including difficulty initiating sleep (DIS), difficulty maintaining sleep (DMS), early morning awakening (EMA), insomnia symptoms, snoring and excessive daytime sleepiness (EDS). Multiple logistic regression models were applied to estimate associations adjusting for potential confounders including gender, age, smoking habit at baseline, change of smoking habit from baseline to follow up, BMI at baseline, change of BMI from baseline to follow up, education level at follow up, allergic rhinitis at baseline, doctor diagnosed asthma at baseline and chronic bronchitis at baseline. Results: Baseline floor dampness, visible mold and mold odor at home increased onset of DIS, DMS, EMA, insomnia symptoms and snoring during follow up (OR 1.29–1.87). Any sign of dampness at baseline increased onset of DIS (OR 1.28, 95%CI 1.06–1.55), DMS (OR 1.17, 95%CI 1.02–1.34) and insomnia symptoms (OR 1.18, 95%CI 1.03–1.36). Dampness at home during follow up increased onset of DIS, DMS, EMA, insomnia symptoms and EDS (OR 1.17–1.36). Dampness at work during follow up increased onset of DIS, EMA, insomnia symptoms and EDS (OR 1.16–1.34). Combined dampness at home and at work during follow up increased the risk of onset of DIS, DMS, EMA, insomnia symptoms and EDS (OR 1.29–1.74). Conclusions: Dampness and mold at home and at work can increase the development of insomnia symptoms, snoring and EDS among adults.

ObjectiveMost women live to experience menopause and will spend 4-8 years transitioning from fertile age to full menstrual stop. Biologically, reproductive ageing is a continuous process, but by convention, it is defined categorically as pre-, peri- and postmenopause; categories that are sometimes supported by measurements of sex hormones in blood samples. We aimed to develop and validate a new tool, a reproductive ageing score (RAS), that could give a simple and yet precise description of the status of reproductive ageing, without hormone measurements, to be used by health professionals and researchers.MethodsQuestionnaire data on age, menstrual regularity and menstrual frequency was provided by the large multicentre population-based RHINE cohort. A continuous reproductive ageing score was developed from these variables, using techniques of fuzzy mathematics, to generate a decimal number ranging from 0.00 (nonmenopausal) to 1.00 (postmenopausal). The RAS was then validated with sex hormone measurements (follicle stimulating hormone and 17β-estradiol) and interview-data provided by the large population-based ECRHS cohort, using receiver-operating characteristics (ROC).ResultsThe RAS, developed from questionnaire data of the RHINE cohort, defined with high precision and accuracy the menopausal status as confirmed by interview and hormone data in the ECRHS cohort. The area under the ROC curve was 0.91 (95% Confidence interval (CI): 0.90-0.93) to distinguish nonmenopausal women from peri- and postmenopausal women, and 0.85 (95% CI: 0.83-0.88) to distinguish postmenopausal women from nonmenopausal and perimenopausal women.ConclusionsThe RAS provides a useful and valid tool for describing the status of reproductive ageing accurately, on a continuous scale from 0.00 to 1.00, based on simple questions and without requiring blood sampling. The score allows for a more precise differentiation than the conventional categorisation in pre-, peri- and postmenopause. This is useful for epidemiological research and clinical trials.

Abstract Background The aim of this investigation was to study change in adults over a 20 year period in the prevalence of respiratory symptoms and disorders and its association to year of birth, life style and sleep related variables. Method Adults 20–44 years of age, 6085 women and 5184 men, were randomly selected from seven centres in Northern Europe and followed for 20 years. The number of participants in the first survey was 21,595 and 11,269 participated in all three surveys. The participants were divided into three birth cohorts: 1944–1955, 1956–1965 and 1966–1975. Results During the 20 year period the prevalence of wheeze decreased (− 2%) and the prevalence of asthma (+ 4%) and allergic rhinitis (+ 5%) increased, whereas the prevalence of nocturnal respiratory symptoms was relatively unchanged. The increase in allergic rhinitis was largest in those born 1966 to 1975 except in Estonia. There was large decrease in smoking (− 20%), increase in obesity (+ 7%) and snoring (+ 6%) during the study period. Smoking, obesity, snoring and nocturnal gastroesophageal reflux (nGER) were related to a higher risk of all symptoms. Obesity, snoring and nGER were also independently related to asthma. Conclusion We conclude that as our participants got older there was a decrease in wheeze, no change in nocturnal symptoms and an increase in reported asthma and allergic rhinitis. These changes in prevalence are probably related to a decrease in smoking being counteracted by an increase in allergy, obesity and sleep related disorders.

Abstract Background Mitochondrial diseases due to defective respiratory chain complex III (CIII) are relatively uncommon. The assembly of the eleven-subunit CIII is completed by the insertion of the Rieske iron-sulfur protein, a process for which BCS1L protein is indispensable. Mutations in the BCS1L gene constitute the most common diagnosed cause of CIII deficiency, and the phenotypic spectrum arising from mutations in this gene is wide. Results A case of CIII deficiency was investigated in depth to assess respiratory chain function and assembly, and brain, skeletal muscle and liver histology. Exome sequencing was performed to search for the causative mutation(s). The patient’s platelets and muscle mitochondria showed respiration defects and defective assembly of CIII was detected in fibroblast mitochondria. The patient was compound heterozygous for two novel mutations in BCS1L, c.306A > T and c.399delA. In the cerebral cortex a specific pattern of astrogliosis and widespread loss of microglia was observed. Further analysis showed loss of Kupffer cells in the liver. These changes were not found in infants suffering from GRACILE syndrome, the most severe BCS1L-related disorder causing early postnatal mortality, but were partially corroborated in a knock-in mouse model of BCS1L deficiency. Conclusions We describe two novel compound heterozygous mutations in BCS1L causing CIII deficiency. The pathogenicity of one of the mutations was unexpected and points to the importance of combining next generation sequencing with a biochemical approach when investigating these patients. We further show novel manifestations in brain, skeletal muscle and liver, including abnormality in specialized resident macrophages (microglia and Kupffer cells). These novel phenotypes forward our understanding of CIII deficiencies caused by BCS1L mutations.

Background: Menopause is associated with a number of adverse health effects and its timing has been reported to be influenced by several lifestyle factors. Whether greenspace exposure is associated with age at menopause has not yet been investigated. Objective: To investigate whether residential surrounding greenspace is associated with age at menopause and thus reproductive aging. Methods: This longitudinal study was based on the 20-year follow-up of 1955 aging women from a large, population-based European cohort (ECRHS). Residential surrounding greenspace was abstracted as the average of satellite-based Normalized Difference Vegetation Index (NDVI) across a circular buffer of 300 m around the residential addresses of each participant during the course of the study. We applied mixed effects Cox models with centre as random effect, menopause as the survival object, age as time indicator and residential surrounding greenspace as time-varying predictor. All models were adjusted for smoking habit, body mass index, parity, age at menarche, ever-use of contraception and age at completed full-time education as socio-economic proxy. Results: An increase of one interquartile range of residential surrounding greenspace was associated with a 13% lower risk of being menopausal (Hazard Ratio: 0.87, 95% Confidence Interval: 0.79–0.95). Correspondingly the predicted median age at menopause was 1.4 years older in the highest compared to the lowest NDVI quartile. Results remained stable after additional adjustment for air pollution and traffic related noise amongst others. Conclusions: Living in greener neighbourhoods is associated with older age at menopause and might slow reproductive aging. These are novel findings with broad implications. Further studies are needed to see whether our findings can be replicated in different populations and to explore the potential mechanisms underlying this association. Keywords: Greenspace, Menopause, NDVI, Reproductive aging, Sex hormones

Introduction The study aim was to examine the association of snoring and nocturnal gastro-oesophageal reflux (nGOR) with respiratory symptoms and lung function, and if snoring and/or nGOR associated with a steeper decline in lung function. Methods Data from the third visit of the European Community Respiratory Health Survey (ECRHS) was used for cross-sectional analysis. Pre- and post-bronchodilator spirometry was performed, and information on sleep, nGOR and respiratory symptoms was collected (n=5715). Habitual snoring and nGOR were assessed by questionnaire reports. Pre-bronchodilator spirometry from ECRHS I, II and III (20 years follow-up) were used to analyse lung function changes by multivariate regression analysis. Results Snoring and nGOR were independently associated with a higher prevalence of wheeze, chest tightness, breathlessness, cough and phlegm. The prevalence of any respiratory symptom was 79% in subjects with both snoring and nGOR versus 56% in those with neither (p

ObjectiveTo examine whether the relationship between the metabolic syndrome (MetS) and various sleep parameters [sleep duration, symptoms of sleep-disordered breathing (SDB), and sleep disturbances] varies by age.MethodsWaist circumference, blood pressure, triglycerides, high-density lipoprotein cholesterol, and fasting glucose were used to determine MetS status in a cohort (N = 19,691) of middle-aged (aged 45–64 years) and older (aged ≥65 years) subjects. Habitual sleep duration (short, ≤6 h/day; normal, 7–8 h/day; and long ≥9 h/day), sleep disturbances (such as problems with falling and staying asleep), and symptoms of sleep-disordered breathing (SDB, such as snoring and sleep apneas) were measured by questionnaires.ResultsAmong the participants, 4,941 subjects (25.1%) fulfilled the criteria for MetS. In the entire sample, both short and long sleep durations were associated with higher prevalence of MetS as compared to normal sleep duration. When stratified by age, a similar pattern was observed for middle-aged subjects ( 0.05 for sleep disturbance × age).ConclusionOur results suggest that age may modify the associations between some sleep parameters and the prevalence of MetS.

Breathlessness is associated with major adverse health outcomes and is twice as common in women as men in the general population. We evaluated whether this is related to their lower absolute lung volumes.Cross-sectional analysis of the population-based Swedish CardioPulmonarybioImage Study (SCAPIS) Pilot, including static spirometry and diffusing capacity (n = 1,013; 49% women). Breathlessness was measured using the modified Medical Research Council (mMRC) scale and analyzed using ordinal logistic regression adjusting for age, pack-years of smoking, body mass index, chronic airway limitation, asthma, chronic bronchitis, depression and anxiety in all models.Breathlessness was twice as common in women as in men; adjusted odds ratio (OR) 2.20 (95% confidence interval, 1.32-3.66). Lower absolute lung volumes were associated with increased breathlessness prevalence in both men and women. The sex difference in breathlessness was unchanged when adjusting for lung function in %predicted, but disappeared when controlling for absolute values of total lung capacity (OR 1.12; 0.59-2.15), inspiratory capacity (OR 1.26; 0.68-2.35), forced vital capacity (OR 0.84; 0.42-1.66), forced expiratory volume in one second (OR 0.70; 0.36-1.35) or lung diffusing capacity (OR 1.07; 0.58-1.97).In the general population, the markedly higher prevalence of breathlessness in women is related to their smaller absolute lung volumes.

The term Asthma and COPD Overlap (ACO) describes a condition where asthma and COPD overlap. We aimed to investigate associations between ACO and insomnia and respiratory symptoms, and to investigate the prevalence of ACO and the characteristics of subjects with ACO in two Northern European population studies.The study comprised 25 429 subjects aged ≥ 40 years who participated in one of two Northern European general population surveys. Both surveys included questions on asthma, COPD, respiratory and sleep-related symptoms, including difficulty initiating sleep, difficulty maintaining sleep, early-morning awakening, and excessive daytime sleepiness. ACO was defined as having both self-reported asthma and COPD.The prevalence of ACO was 1.0%. The group with ACO had a higher prevalence of both insomnia and respiratory symptoms than subjects with only asthma or COPD. Having ACO was independently associated with a 2-3 times higher probability of having sleep-related symptoms as compared with the group without asthma or COPD, after adjustment for age, sex, BMI, smoking history and educational level (adjusted odds ratio 2.14-3.36, 95% CI).Subjects with ACO have a high prevalence of insomnia and respiratory symptoms. To our knowledge, this is the first study to assess the association between sleep-related symptoms and ACO.

OBJECTIVES: This population-based cohort study was performed to assess the association between sleep disturbances and the risk of occupational accidents among women. METHODS: Data were collected by questionnaires on two different occasions (2000 and 2010) and data on work injuries were also collected from Swedish government records (ISA). Insomnia symptoms were defined as having severe or very severe problems with (i) difficulty initiating sleep, (ii) difficulty maintaining sleep, or (iii) early morning awakening. Symptom of obstructive sleep apnea syndrome (OSAS) was defined as reporting both snoring and daytime sleepiness. Working-age respondents (20–67 years of age) who responded to both baseline and follow-up questionnaires and had worked for part or all of the 10-year follow-up period (N=4320) were included in the study. RESULTS: Of the subjects responding to the questionnaire, 12.2% reported ≥1 accident and 6.3% reported an accident requiring sick leave in the government register. Blue-collar workers and night and shift work were more common in the group with occupational accidents. Subjects with insomnia symptoms both at baseline and follow-up (persistent insomnia symptoms) ran a higher risk of being involved in an self-reported occupational accident [adjusted OR (OR_adj) 1.5, 95% confidence interval (95% CI) 1.2–2.0] after adjusting for age, body mass index, smoking, alcohol dependency, white- or blue-collar worker, years at work, night work, and physical activity. Persistent insomnia symptoms did not reach statistical significance as an independent predictor of register-reported occupational accident with sick leave (OR_adj 1.4, 95% CI 0.99–2.1). No significant association was found between symptoms of OSAS and self-reported or register-based occupational accidents. CONCLUSIONS: Persistent insomnia symptoms were associated with an increased risk of self-reported occupational accidents, while no significant association was found with occupational accidents with sick leave reported to government register.

In managed landscapes, conservation planning requires effective methods to identify high-biodiversity areas. The objective of this study was to evaluate the potential of airborne laser scanning (ALS) and forest estimates derived from satellite images extracted at two spatial scales for predicting the stand-scale abundance and species richness of birds and beetles in a managed boreal forest landscape. Multiple regression models based on forest data from a 50-m radius (i.e., corresponding to a homogenous forest stand) had better explanatory power than those based on a 200-m radius (i.e., including also parts of adjacent stands). Bird abundance and species richness were best explained by the ALS variables “maximum vegetation height” and “vegetation cover between 0.5 and 3 m” (both positive). Flying beetle abundance and species richness, as well as epigaeic (i.e., ground-living) beetle richness were best explained by a model including the ALS variable “maximum vegetation height” (positive) and the satellite-derived variable “proportion of pine” (negative). Epigaeic beetle abundance was best explained by “maximum vegetation height” at 50 m (positive) and “stem volume” at 200 m (positive). Our results show that forest estimates derived from satellite images and ALS data provide complementary information for explaining forest biodiversity patterns. We conclude that these types of remote sensing data may provide an efficient tool for conservation planning in managed boreal landscapes.

Individual tree crowns may be delineated from airborne laser scanning (ALS) data by segmentation of surface models or by 3D analysis. Segmentation of surface models benefits from using a priori knowledge about the proportions of tree crowns, which has not yet been utilized for 3D analysis to any great extent. In this study, an existing surface segmentation method was used as a basis for a new tree model 3D clustering method applied to ALS returns in 104 circular field plots with 12 m radius in pine-dominated boreal forest (64°14'N, 19°50'E). For each cluster below the tallest canopy layer, a parabolic surface was fitted to model a tree crown. The tree model clustering identified more trees than segmentation of the surface model, especially smaller trees below the tallest canopy layer. Stem attributes were estimated with k-Most Similar Neighbours (k-MSN) imputation of the clusters based on field-measured trees. The accuracy at plot level from the k-MSN imputation (stem density root mean square error or RMSE 32.7%; stem volume RMSE 28.3%) was similar to the corresponding results from the surface model (stem density RMSE 33.6%; stem volume RMSE 26.1%) with leave-one-out cross-validation for one field plot at a time. Three-dimensional analysis of ALS data should also be evaluated in multi-layered forests since it identified a larger number of small trees below the tallest canopy layer.

There is little knowledge about how oral and respiratory health is interrelated even though the mucosa of the oral cavity and airways constitutes a continuum and the exposures to these are partly similar.To investigate whether gum bleeding is related to asthma, respiratory symptoms and self-reported COPD.A postal questionnaire including questions about respiratory and oral health was sent to general population samples in seven Northern European centres. In 13,409 responders, gum bleeding when brushing teeth was reported always/often by 4% and sometimes by 20%. Logistic regressions accounted for age, smoking, educational level, centre and gender. Effects of BMI, cardio-metabolic diseases, early life factors, gastro-oesophageal reflux, dental hygiene, nasal congestion, and asthma medication were addressed.Gum bleeding always/often was significantly associated with ≥ 3 asthma symptoms (OR 2.58, 95% CI 2.10-3.18), asthma (1.62 [1.23-2.14]) and self-reported COPD (2.02 [1.28-3.18]). There was a dose-response relationship between respiratory outcomes and gum bleeding frequency (≥ 3 symptoms: gum bleeding sometimes 1.42 [1.25-1.60], often/always 2.58 [2.10-3.18]), and there was no heterogeneity between centres (p(heterogeneity) = 0.49). None of the investigated risk factors explained the associations. The observed associations were significantly stronger among current smokers (p(interaction) = 0.004).A consistent link between gum bleeding and obstructive airways disease was observed, not explained by common risk factors or metabolic factors. We speculate that oral pathogens might have unfavourable impact on the airways, and that the direct continuity of the mucosa of the oral cavity and the airways reflects a pathway that might provide novel opportunities for interventions.

This study compares methods to estimate stem volume, stem number and basal area from Airborne Laser Scanning (ALS) data for 68 field plots in a hemi-boreal, spruce dominated forest (Lat. 58°N, Long. 13°E). The stem volume was estimated with five different regression models: one model based on height and density metrics from the ALS data derived from the whole field plot, two models based on similar combinations derived from 0.5 m raster cells, and two models based on canopy volumes from the ALS data. The best result was achieved with a model based on height and density metrics derived from 0.5 m raster cells (Root Mean Square Error or RMSE 37.3%) and the worst with a model based on height and density metrics derived from the whole field plot (RMSE 41.9%). The stem number and the basal area were estimated with: (i) area-based regression models using height and density metrics from the ALS data; and (ii) single tree-based information derived from local maxima in a normalized digital surface model (nDSM) mean filtered with different conditions. The estimates from the regression model were more accurate (RMSE 52.7% for stem number and 21.5% for basal area) than those derived from the nDSM (RMSE 63.4%–91.9% and 57.0%–175.5%, respectively). The accuracy of the estimates from the nDSM varied depending on the filter size and the conditions of the applied filter. This suggests that conditional filtering is useful but sensitive to the conditions.

The Sentinel-2 program provides the opportunity to monitor terrestrial ecosystems with a high temporal and spectral resolution. In this study, a multi-temporal Sentinel-2 data set was used to classify common tree species over a mature forest in central Sweden. The tree species to be classified were Norway spruce (Picea abies), Scots pine (Pinus silvestris), Hybrid larch (Larix × marschlinsii), Birch (Betula sp.) and Pedunculate oak (Quercus robur). Four Sentinel-2 images from spring (7 April and 27 May), summer (9 July) and fall (19 October) of 2017 were used along with the Random Forest (RF) classifier. A variable selection approach was implemented to find fewer and uncorrelated bands resulting in the best model for tree species identification. The final model resulting in the highest overall accuracy (88.2%) came from using all bands from the four image dates. The single image that gave the most accurate classification result (80.5%) was the late spring image (27 May); the 27 May image was always included in subsequent image combinations that gave the highest overall accuracy. The five tree species were classified with a user’s accuracy ranging from 70.9% to 95.6%. Thirteen of the 40 bands were selected in a variable selection procedure and resulted in a model with only slightly lower accuracy (86.3%) than that using all bands. Among the highest ranked bands were the red edge bands 2 and 3 as well as the narrow NIR (near-infrared) band 8a, all from the 27 May image, and SWIR (short-wave infrared) bands from all four image dates. This study shows that the red-edge bands and SWIR bands from Sentinel-2 are of importance, and confirms that spring and/or fall images capturing phenological differences between the species are most useful to tree species classification.

As part of the digitalization of the forest planning process, 3D remote sensing data is an important data source. However, the demand for more detailed information with high temporal resolution and yet still being cost efficient is a challenging combination for the systems used today. A new lidar technology based on single photon counting has the possibility to meet these needs. The aim of this paper is to evaluate the new single photon lidar sensor Leica SPL100 for area-based forest variable estimations. In this study, it was found that data from the new system, operated from 3800 m above ground level, could be used for raster cell estimates with similar or slightly better accuracy than a linear system, with similar point density, operated from 400 m above ground level. The new single photon counting lidar sensor shows great potential to meet the need for efficient collection of detailed information, due to high altitude, flight speed and pulse repetition rate. Further research is needed to improve the method for extraction of information and to investigate the limitations and drawbacks with the technology. The authors emphasize solar noise filtering in forest environments and the effect of different atmospheric conditions, as interesting subjects for further research.

Today, non-expensive remote sensing (RS) data from different sensors and platforms can be obtained at short intervals and be used for assessing several kinds of forest characteristics at the level of plots, stands and landscapes. Methods such as composite estimation and data assimilation can be used for combining the different sources of information to obtain up-to-date and precise estimates of the characteristics of interest. In composite estimation a standard procedure is to assign weights to the different individual estimates inversely proportional to their variance. However, in case the estimates are correlated, the correlations must be considered in assigning weights or otherwise a composite estimator may be inefficient and its variance be underestimated. In this study we assessed the correlation of plot level estimates of forest characteristics from different RS datasets, between assessments using the same type of sensor as well as across different sensors. The RS data evaluated were SPOT-5 multispectral data, 3D airborne laser scanning data, and TanDEM-X interferometric radar data. Studies were made for plot level mean diameter, mean height, and growing stock volume. All data were acquired from a test site dominated by coniferous forest in southern Sweden. We found that the correlation between plot level estimates based on the same type of RS data were positive and strong, whereas the correlations between estimates using different sources of RS data were not as strong, and weaker for mean height than for mean diameter and volume. The implications of such correlations in composite estimation are demonstrated and it is discussed how correlations may affect results from data assimilation procedures.

Multispectral Airborne Laser Scanning (ALS) is a new technology and its output data have not been fully explored for tree species classification purposes. The objective of this study was to investigate what type of features from multispectral ALS data (wavelengths of 1550 nm, 1064 nm and 532 nm) are best suited for tree species classification. Remote sensing data were gathered over hemi-boreal forest in southern Sweden (58°27′18.35″N, 13°39′8.03″E) on 21 July 2016. The field data consisted of 179 solitary trees from nine genera and ten species. Two new methods for feature extraction were tested and compared to features of height and intensity distributions. The features that were most important for tree species classification were intensity distribution features. Features from the upper part of the upper and outer parts of the crown were better for classification purposes than others. The best classification model was created using distribution features of both intensity and height in multispectral data, with a leave-one-out cross-validated accuracy of 76.5%. As a comparison, only structural features resulted in an highest accuracy of 43.0%. Picea abies and Pinus sylvestris had high user’s and producer’s accuracies and were not confused with any deciduous species. Tilia cordata was the deciduous species with a large sample that was most frequently confused with many other deciduous species. The results, although based on a small and special data set, suggest that multispectral ALS is a technology with great potential for tree species classification.