Prediction of Site Index and Age Using Time Series of TanDEM-X Phase Heights

Site index and stand age are important variables in forestry. Site index describes the growing potential at a given location, expressed as the height that trees can attain at a given age under favorable growing conditions. It is traditionally used to classify forests in terms of future timber yield potential. Stand age is used for the planning of management activities such as thinning and harvest. SI has previously been predicted using remote sensing, but usually relying on either very short time series or repeated ALS acquisitions. In this study, site index and forest stand age were predicted from time series of interferometric TanDEM-X data spanning seven growth seasons in a hemi-boreal forest in Remningstorp, a test site located in southern Sweden. The goal of the study was to see how satellite-based radar time series could be used to estimate site index and stand age. Compared to previous studies, we used a longer time series and applied a penetration depth correction to the phase heights, thereby avoiding the need for calibration using ancillary field or ALS data. The time series consisted of 30 TanDEM-X strip map scenes acquired between 2011 and 2018. Established height development curves were fitted to the time series of TanDEM-X-based top heights. This enabled simultaneous estimation of both age and site index on 91 field plots with a 10 m radius. The RMSE of predicted SI and age were 6.9 m and 38 years for untreated plots when both SI and age were predicted. When predicting SI and the age was known, the RMSE of the predicted SI was 4.0 m. No significant prediction bias was observed for untreated plots, while underestimation of SI and overestimation of age increased with the intensity of treatment

Predictions of Biomass Change in a Hemi-Boreal Forest Based on Multi-Polarization L- and P-Band SAR Backscatter

Above-ground biomass change accumulated during four growth seasons in a hemi-boreal forest was predicted using airborne L- and P-band synthetic aperture radar (SAR) backscatter. The radar data were collected in the BioSAR 2007 and BioSAR 2010 campaigns over the Remningstorp test site in southern Sweden. Regression models for biomass change were developed from biomass maps created using airborne LiDAR data and field measurements. To facilitate training and prediction on image pairs acquired at different dates, a backscatter offset correction method for L-band data was developed and evaluated. The correction, based on the HV/VV backscatter ratio, facilitated predictions across image pairs almost identical to those obtained using data from the same image pair for both training and prediction. For P-band, previous positive results using an offset correction based on the HH/VV ratio were validated. The best L-band model achieved a root mean square error (RMSE) of 21 t/ha, and the best P-band model achieved an RMSE of 19 t/ha. Those accuracies are similar to that of the LiDAR-based biomass change of 18 t/ha. The limitation of using LiDAR-based data for training was considered. The findings demonstrate potential for improved biomass change predictions from L-band backscatter despite varying environmental conditions and calibration uncertainties

BIOSAR 2010 - A SAR campaign in support to the BIOMASS mission

The ESA funded campaign BioSAR 2010 was carried out at the forestry test site Remningstorp in southern Sweden, in support to the BIOMASS satellite mission under study. Fully polarimetric SAR data were successfully acquired at L- and P-band using ONERA's multi-frequency system SETHI. In addition with other data types gathered, e.g. LiDAR and in-situ measurements, the compiled data set will be used for analyses and comparisons with biomass estimation results obtained at the same test site in the campaign BioSAR 2007, in which DLR's E-SAR made the SAR imaging. Detection of forest changes, robustness of biomass retrieval algorithms and long-term P-band coherence will be in focus as well as cross-validations between the two SAR sensors

The effect of leisure-time physical activity on the risk of acute myocardial infarction depending on Body Mass Index: a population-based case-control study

BACKGROUND: High body mass index (BMI) and lack of physical activity have been recognized as important risk factors for coronary heart disease. The aim of the present study was to evaluate whether leisure-time physical activity compensates for the increased risk of acute myocardial infarction associated with overweight and obesity. METHODS: Data from the SHEEP (Stockholm Heart Epidemiology Program) study were used. The SHEEP study is a large Swedish population-based case-control study, comprising 1204 male and 550 female cases, and 1538 male and 777 female controls, conducted in Stockholm County, Sweden, during the period 1992–1994. Odds ratios (OR), together with 95 % confidence intervals (95% CI), were calculated using unconditional logistic regression, as estimates of the relative risks. RESULTS: Regular leisure-time physical activity was associated with a decreased risk of myocardial infarction among lean, normal-weight and overweight subjects, but not among obese subjects. Obese (BMI ≥ 30) and physically active persons had an almost twofold risk of myocardial infarction, compared with normal-weight and sedentary persons (OR 1.85, 95% CI 1.07–3.18). The results were similar for men and women. CONCLUSION: While regular leisure-time physical activity seems to provide protection against myocardial infarction among lean, normal-weight and overweight subjects, this does not appear to be the case in obese subjects

Disease Dynamics and Bird Migration—Linking Mallards Anas platyrhynchos and Subtype Diversity of the Influenza A Virus in Time and Space

The mallard Anas platyrhynchos is a reservoir species for influenza A virus in the northern hemisphere, with particularly high prevalence rates prior to as well as during its prolonged autumn migration. It has been proposed that the virus is brought from the breeding grounds and transmitted to conspecifics during subsequent staging during migration, and so a better understanding of the natal origin of staging ducks is vital to deciphering the dynamics of viral movement pathways. Ottenby is an important stopover site in southeast Sweden almost halfway downstream in the major Northwest European flyway, and is used by millions of waterfowl each year. Here, mallards were captured and sampled for influenza A virus infection, and positive samples were subtyped in order to study possible links to the natal area, which were determined by a novel approach combining banding recovery data and isotopic measurements (δ2H) of feathers grown on breeding grounds. Geographic assignments showed that the core natal areas of studied mallards were in Estonia, southern and central Finland, and northwestern Russia. This study demonstrates a clear temporal succession of latitudes of natal origin during the course of autumn migration. We also demonstrate a corresponding and concomitant shift in virus subtypes. Acknowledging that these two different patterns were based in part upon different data, a likely interpretation worth further testing is that the early arriving birds with more proximate origins have different influenza A subtypes than the more distantly originating late autumn birds. If true, this knowledge would allow novel insight into the origins and transmission of the influenza A virus among migratory hosts previously unavailable through conventional approaches

Outcomes of Brood Parasite–Host Interactions Mediated by Egg Matching: Common Cuckoos Cuculus canorus versus Fringilla Finches

Antagonistic species often interact via matching of phenotypes, and interactions between brood parasitic common cuckoos (Cuculus canorus) and their hosts constitute classic examples. The outcome of a parasitic event is often determined by the match between host and cuckoo eggs, giving rise to potentially strong associations between fitness and egg phenotype. Yet, empirical efforts aiming to document and understand the resulting evolutionary outcomes are in short supply.We used avian color space models to analyze patterns of egg color variation within and between the cuckoo and two closely related hosts, the nomadic brambling (Fringilla montifringilla) and the site fidelic chaffinch (F. coelebs). We found that there is pronounced opportunity for disruptive selection on brambling egg coloration. The corresponding cuckoo host race has evolved egg colors that maximize fitness in both sympatric and allopatric brambling populations. By contrast, the chaffinch has a more bimodal egg color distribution consistent with the evolutionary direction predicted for the brambling. Whereas the brambling and its cuckoo host race show little geographical variation in their egg color distributions, the chaffinch's distribution becomes increasingly dissimilar to the brambling's distribution towards the core area of the brambling cuckoo host race.High rates of brambling gene flow is likely to cool down coevolutionary hot spots by cancelling out the selection imposed by a patchily distributed cuckoo host race, thereby promoting a matching equilibrium. By contrast, the site fidelic chaffinch is more likely to respond to selection from adapting cuckoos, resulting in a markedly more bimodal egg color distribution. The geographic variation in the chaffinch's egg color distribution could reflect a historical gradient in parasitism pressure. Finally, marked cuckoo egg polymorphisms are unlikely to evolve in these systems unless the hosts evolve even more exquisite egg recognition capabilities than currently possessed

Nation-wide clear-cut mapping in Sweden using ALOS PALSAR strip images

Advanced Land Observing Satellite (ALOS) Phased Array L-band type Synthetic Aperture Radar (PALSAR) backscatter images with 50 m pixel size (strip images) at HV-polarization were used to map clear-cuts at a regional and national level in Sweden. For a set of 31 clear-cuts, on average 59.9% of the pixels within each clear-cut were correctly detected. When compared with a one-pixel edge-eroded version of the reference dataset, the accuracy increased to 88.9%. With respect to statistics from the Swedish Forest Agency, county-wise clear-felled areas were underestimated by the ALOS PALSAR dataset (between 25% and 60%) due to the coarse resolution. When compared with statistics from the Swedish National Forest Inventory, the discrepancies were larger, partly due to the estimation errors from the plot-wise forest inventory data. In Sweden, for the time frame of 2008–2010, the total area felled was estimated to be 140,618 ha, 172,532 ha and 194,586 ha using data from ALOS PALSAR, the Swedish Forest Agency and the Swedish National Forest Inventory, respectively. ALOS PALSAR strip images at HV-polarization appear suitable for detection of clear-felled areas at a national level; nonetheless, the pixel size of 50 m is a limiting factor for accurate delineation of clear-felled areas

Extraction of Spectral Information from Airborne 3D Data for Assessment of Tree Species Proportions

With the rapid development of photogrammetric software and accessible camera technology, land surveys and other mapping organizations now provide various point cloud and digital surface model products from aerial images, often including spectral information. In this study, methods for colouring the point cloud and the importance of different metrics were compared for tree species-specific estimates at a coniferous hemi-boreal test site in southern Sweden. A total of three different data sets of aerial image-based products and one multi-spectral lidar data set were used to estimate tree species-specific proportion and stem volume using an area-based approach. Metrics were calculated for 156 field plots (10 m radius) from point cloud data and used in a Random Forest analysis. Plot level accuracy was evaluated using leave-one-out cross-validation. The results showed small differences in estimation accuracy of species-specific variables between the colouring methods. Simple averages of the spectral metrics had the highest importance and using spectral data from two seasons improved species prediction, especially deciduous proportion. Best tree species-specific proportion was estimated using multi-spectral lidar with 0.22 root mean square error (RMSE) for pine, 0.22 for spruce and 0.16 for deciduous. Corresponding RMSE for aerial images was 0.24, 0.23 and 0.20 for pine, spruce and deciduous, respectively. For the species-specific stem volume at plot level using image data, the RMSE in percent of surveyed mean was 129% for pine, 60% for spruce and 118% for deciduous

Overstory dynamics regulate the spatial variability in forest-floor CO2 fluxes across a managed boreal forest landscape

The forest-floor represents an important interface for various carbon dioxide (CO2) fluxes, however, our knowledge of their variability and drivers across a managed boreal forest landscape is limited. Here, we used a three-year (2016-2018) data set of biometric- and chamber-based flux measurements to investigate the net forest-floor CO2 exchange (NEff) and its component fluxes across 50 forest stands spanning different soil types, tree species, and age classes within a 68 km2 boreal catchment in Sweden. We found that the forest-floor acted as a net CO2 source with the 10th-90th percentile (used hereafter for describing reported variations) ranging from 149 to 399 g C m- 2 yr-1. Among the key landscape attributes, stand age strongly affected most NEff component fluxes, whereas tree species and soil type effects were weak and absent, respectively. Specifically, forest-floor net CO2 emissions increased with stand age due to declining understory gross and net primary production, ranging between 77-275 and 49-163 g C m- 2 yr- 1, respectively. Furthermore, we observed higher understory production rates in pine than in spruce stands. Across the 50 stands, the total forest-floor respiration ranged between 340 and 549 g C m- 2 yr-1 and its spatial variation was primarily regulated by its autotrophic components, i.e., understory and tree root respiration, which displayed divergent increasing and decreasing age-related trends, respectively. Furthermore, heterotrophic soil respiration remained within a relatively narrow range (154-290 g C m- 2 yr- 1), possibly owing to compensating gradients in forest-floor properties. We further identified tree biomass as the major driver of the landscape-scale variations of CO2 fluxes, likely attributable to modulating effects on forest-floor resource availability and growing conditions. This implies that tree growth responses to forest management and global change will be particularly important for regulating magnitudes and spatial variations of forest-floor CO2 fluxes in boreal forests