Firm size and growth opportunities: a survey

The qualifying aspect of the ongoing changes in firm growth processes seems to be the increased heterogeneity of size and a trend towards a broader fluctuation in average size. Exogenous factors (market size, demand trends, technological innovations, higher competition) determine a different impact on firms will to increase their own size, while endogenous variables play a greater role than in the past. The outcome is represented by a growth pattern that characterises some firms, but not all of them. Growth appear to be an asymmetric phenomenon, involving selectively but not casually a subgroup of firms. In the present paper it is hypothesized that growth stems from the asymmetric distribution of internalized resources (both material and immaterial), allowing some firms (regardless of the original size) to enter evolutionary paths that others don’t want or simply can’t enter.Firm Growth, Size Distribution, Gibrat’s Law, Industrial Dynamics, Human Capital, Intangible Assets, Industrial Policy

Begging and parental care in relation to offspring need and condition in the barn swallow (Hirundo rustica)

Parents are selected to maximize their fitness by allocating care among their progeny in relation to the differential reproductive value of offspring. Nestlings have been hypothesized to signal need for parental care reliably through their begging behavior, but offspring condition as reflected by their reproductive value may likewise affect begging and hence provisioning. We assessed the relative importance of need and condition in determining begging behavior and feeding rate of nestling barn swallows (Hirundo rustica) through short-term starvation, a challenge to their immune system with a foreign antigen negatively affecting condition, and brood size manipulation. Food deprivation but not condition or brood size manipulation increased nestling begging rate. Parents fed offspring depending on both need and condition but only when feeding broods that were reduced or of normal size. In enlarged broods, offspring received less food per capita than in reduced broods, and parents did not discriminate among nestlings relative to their need or condition. Thus, nestlings signal their need by increased solicitation. Parents allocate food to offspring dependent on both need and condition, with these effects depending on parental workload as determined by experimental brood size

Il microcarcinoma papillare della tiroide. Implicazioni cliniche e strategia terapeutica

Gli Autori riportano la propria esperienza sulle implicazioni cli - niche e le strategie terapeutiche del microcarcinoma papillare della tiroide, valutando 412 pazienti sottoposti ad intervento chirurgico per patologia tiroidea. Essi sottolineano l’attuale problematica della diagnosi “incidentale” postoperatoria, la relativa strategia terapeutica adiuvante, il frequente riscontro di una patologia tiroidea benigna associata, fattori che giustificano, oltre le note motivazioni oncologi - che, la scelta della tiroidectomia totale di principio

Assessing Precision in Conventional Field Measurements of Individual Tree Attributes

Forest resource information has a hierarchical structure: individual tree attributes are summed at the plot level and then in turn, plot-level estimates are used to derive stand or large-area estimates of forest resources. Due to this hierarchy, it is imperative that individual tree attributes are measured with accuracy and precision. With the widespread use of different measurement tools, it is also important to understand the expected degree of precision associated with these measurements. The most prevalent tree attributes measured in the field are tree species, stem diameter-at-breast-height (dbh), and tree height. For dbh and height, the most commonly used measuring devices are calipers and clinometers, respectively. The aim of our study was to characterize the precision of individual tree dbh and height measurements in boreal forest conditions when using calipers and clinometers. The data consisted of 319 sample trees at a study area in Evo, southern Finland. The sample trees were measured independently by four trained mensurationists. The standard deviation in tree dbh and height measurements was 0.3 cm (1.5%) and 0.5 m (2.9%), respectively. Precision was also assessed by tree species and tree size classes; however, there were no statistically significant differences between the mensurationists for dbh or height measurements. Our study offers insights into the expected precision of tree dbh and height as measured with the most commonly used devices. These results are important when using sample plot data in forest inventory applications, especially now, at a time when new tree attribute measurement techniques based on remote sensing are being developed and compared to the conventional caliper and clinometer measurements.Peer reviewe

Assessing the Effects of Sample Size on Parametrizing a Taper Curve Equation and the Resultant Stem-Volume Estimates

Large and comprehensive datasets, traditionally based on destructive stem analysis or other labor-intensive approaches, are commonly considered as a necessity in developing stem-volume equations. The aim here was to investigate how a decreasing number of sample trees affects parametrizing an existing taper curve equation and resultant stem-volume estimates. Furthermore, the potential of terrestrial laser scanning (TLS) in producing taper curves was examined. A TLS-based taper curve was derived for 246 Scots pines (Pinus sylvestris L.) from southern Finland to parametrize an existing taper curve equation. To assess sensitivity of the parametrization regarding sample size, the number of Scots pines included in the parametrization varied between full census and 1 Scots pine at a time. Root mean square error of stem-volume estimates remained ≤20.9% and the mean absolute difference was relatively constant (≤9.0%) between stem-volume estimates when the sample size included ≥46 Scots pines. Thus, it can be concluded that, with a rather small sample size, a taper curve equation can be re-parametrized for local conditions using point clouds from TLS to produce consistent stem-volume estimates

Assessing the Effects of Sample Size on Parametrizing a Taper Curve Equation and the Resultant Stem-Volume Estimates

Large and comprehensive datasets, traditionally based on destructive stem analysis or other labor-intensive approaches, are commonly considered as a necessity in developing stem-volume equations. The aim here was to investigate how a decreasing number of sample trees affects parametrizing an existing taper curve equation and resultant stem-volume estimates. Furthermore, the potential of terrestrial laser scanning (TLS) in producing taper curves was examined. A TLS-based taper curve was derived for 246 Scots pines (Pinus sylvestris L.) from southern Finland to parametrize an existing taper curve equation. To assess sensitivity of the parametrization regarding sample size, the number of Scots pines included in the parametrization varied between full census and 1 Scots pine at a time. Root mean square error of stem-volume estimates remained ≤20.9% and the mean absolute difference was relatively constant (≤9.0%) between stem-volume estimates when the sample size included ≥46 Scots pines. Thus, it can be concluded that, with a rather small sample size, a taper curve equation can be re-parametrized for local conditions using point clouds from TLS to produce consistent stem-volume estimates

Landsat archive holdings for Finland : opportunities for forest monitoring

There is growing interest in the use of Landsat data to enable forest monitoring over large areas. Free and open data access combined with high performance computing have enabled new approaches to Landsat data analysis that use the best observation for any given pixel to generate an annual, cloud-free, gap-free, surface reflectance image composite. Finland has a long history of incorporating Landsat data into its National Forest Inventory to produce forest information in the form of thematic maps and small area statistics on a variety of forest attributes. Herein we explore the spatial and temporal characteristics of the Landsat archive in the context of forest monitoring in Finland. The United States Geological Survey Landsat archive holds a total of 30 076 images (1972-2017) for 66 scenes (each 185 km by 185 km in size) representing the terrestrial area of Finland, of which 93.6% were acquired since 1984 with a spatial resolution of 30 m. Approximately 16.3% of the archived images have desired compositing characteristics (acquired within August 1 +/- 30 days,Peer reviewe

Assessing spectral measures of post-harvest forest recovery with field plot data

Information regarding the nature and rate of forest recovery is required to inform forest management, monitoring, and reporting activities. Delayed establishment or return of forests has implications to harvest rotations and carbon uptake, among others, creating a need for spatially-explicit, large-area, characterizations of forest recovery. Landsat time series (LTS) has been demonstrated as a means to quantitatively relate forest recovery, noting that there are gaps in our understanding of the linkage between spectral measures of forest recovery and manifestations of forest structure and composition. Field plots provide a means to better understand the linkage between forest characteristics and spectral recovery indices. As such, from a large set of existing field plots, we considered the conditions present for the year in which the co-located pixel was considered spectrally recovered using the Years to Recovery (Y2R) metric. Y2R is a long-term metric of spectral recovery that indicates the number of years required for a pixel to return to 80% of its pre-disturbance Normalized Burn Ratio value. Absolute and relative metrics of recovery at 5 years post-disturbance were also considered. We used these three spectral recovery metrics to predict the stand development class assigned by the field crew for 284 seedling plots with an overall accuracy of 73.59%, with advanced seedling stands more accurately discriminated (omission error, OE = 15.74%) than young seedling stands (OE = 49.84%). We then used field-measured attributes (e.g. height, stem density, dominant species) from the seedling plots to classify the plots into three spectral recovery groups, which were defined using the Y2R metric: spectral recovery in (1) 1–5 years, (2) 6–10 years, or (3) 11–15 years. Overall accuracy for spectral recovery groups was 61.06%. Recovery groups 1 and 3 were discriminated with greater accuracy (producer’s and user’s accuracies > 66%) than recovery group 2 ( 66%) than recovery group 2 ( 66%) than recovery group 2 (<50%). The top field-measured predictors of spectral recovery were mean height, dominant species, and percentage of stems in the plot that were deciduous. Variability in stand establishment and condition make it challenging to accurately discriminate among recovery rates within 10 years post-harvest. Our results indicate that the long-term metric Y2R relates to forest structure and composition attributes measured in the field and that spectral development post-disturbance corresponds with expectations of structural development, particularly height, for different species, site types, and deciduous abundance. These results confirm the utility of spectral recovery measures derived from LTS data to augment landscape-level assessments of post-disturbance recovery.Peer reviewe

Aboveground forest biomass derived using multiple dates of WorldView-2 stereo-imagery : quantifying the improvement in estimation accuracy

The aim of this study was to investigate the capabilities of two date satellite-derived image-based point clouds (IPCs) to estimate forest aboveground biomass (AGB). The data sets used include panchromatic WorldView-2 stereo-imagery with 0.46 m spatial resolution representing 2014 and 2016 and a detailed digital elevation model derived from airborne laser scanning data. Altogether, 332 field sample plots with an area of 256 m(2) were used for model development and validation. Predictors describing forest height, density, and variation in height were extracted from the IPC 2014 and 2016 and used in k-nearest neighbour imputation models developed with sample plot data for predicting AGB. AGB predictions for 2014 (AGB(2014)) were projected to 2016 using growth models (AGB(Projected_2016)) and combined with the AGB estimates derived from the 2016 data (AGB(2016)). AGB prediction model developed with 2014 data was also applied to 2016 data (AGB(2016_pred2014)). Based on our results, the change in the 90(th) percentile of height derived from the WorldView-2 IPC was able to characterize forest height growth between 2014 and 2016 with an average growth of 0.9 m. Features describing canopy cover and variation in height derived from the IPC were not as consistent. The AGB(2016) had a bias of -7.5% (-10.6 Mg ha(-1)) and root mean square error (RMSE) of 26.0% (36.7 Mg ha(-1)) as the respective values for AGB(Projected_2016) were 7.0% (9.9 Mg ha(-1)) and 21.5% (30.8 Mg ha(-1)). AGB(2016_pred2014) had a bias of -19.6% (-27.7 Mg ha(-1)) and RMSE of 33.2% (46.9 Mg ha(-1)). By combining predictions of AGB(2016) and AGB(Projected_2016) at sample plot level as a weighted average, we were able to decrease the bias notably compared to estimates made on any single date. The lowest bias of -0.25% (-0.4 Mg ha(-1)) was obtained when equal weights of 0.5 were given to the AGB(Projected_2016) and AGB(2016) estimates. Respectively, RMSE of 20.9% (29.5 Mg ha(-1)) was obtained using equal weights. Thus, we conclude that combination of two date WorldView-2 stereo-imagery improved the reliability of AGB estimates on sample plots where forest growth was the only change between the two dates.Peer reviewe

Whole mitochondrial genome sequencing provides new insights into the phylogeography of loggerhead turtles (Caretta caretta) in the Mediterranean Sea

Population structure and phylogeography of the loggerhead sea turtle (Caretta caretta) have so far been assessed mainly by mitochondrial DNA (mtDNA) single-gene sequencing studies. However, phylogenetic relationships amongst matrilines, genetic characterisation of rookeries and mixed-stock analyses have suffered from the limited resolution obtained by comparison of relatively short sequences such as from the mtDNA control region. Whole mitogenome sequencing can significantly improve population genetics, particularly in marine organisms showing female natal philopatry. Despite mitogenomics becoming increasingly common in biodiversity monitoring and conservation, only a few complete mitogenomes are available for C. caretta. In this study, we sequenced the complete mtDNA of 61 loggerhead turtles sampled between 2008 and 2021 along the Italian coastline and central Mediterranean Sea. We assigned complete mtDNA haplotypes to dead embryos and bycatch samples, and introduced a first nomenclature for loggerhead mitogenomes. Analysis of mtDNA diversity, Maximum Parsimony and Bayesian phylogenetic reconstruction allowed improved resolution of lineages with respect to studies reporting on partial mtDNA control region sequence comparisons, and we were able to further inform previous analyses on loggerhead ancestry based on control region haplogroups. Overall, whole mitogenome analysis has potential for considerable improvement of evolutionary history and phylogeographic investigations as well as mixed-stock surveys of loggerhead turtles