The dynamics of structure across scale in a primaeval European beech stand

We explored the spatial dynamics of structural complexity in the living tree stratum in a 10-ha stem-mapped portion of an unmanaged nearly monospecific primaeval European beech (Fagus sylvatica L.) stand in Western Ukraine. Development dynamics were assessed through patterns of change in association across scales (from 156.25 m2 to 1 ha) among stand basal area (BA), tree density, average and standard deviation (STD) of tree diameters, Gini coefficient (GC), the index of spatial aggregation (R), diameter differentiation index (T) and structural complexity index (SCI). At the smallest scales, STD, GC and T contrasted patches of differing structure (i.e. large between-patch structural differences). As subplot area increased and incorporated more heterogeneity, structural differences between subplots became more subtle and measures of tree-to-tree size variation (STD, T) lost sensitivity whereas it was gained for measures of overall within-patch heterogeneity (GC). At small scales, differences in STD largely explained variation in the SCI (between-plot variability); at intermediate scales, size differences among neighbours (T) explained most of the variability; and at large scales, plot-level differences in BA and its allocation to trees of different sizes (GC; within-plot variability) overrode size differences among nearest neighbours. The characterization of a fine-scale shifting mosaic of patches in different development stages appears to hold for primaeval beech forests in this spatially contiguous area of relatively large extent. The coalescence of small-scale processes into neighbourhoods, and then into patches at larger scales, may be best captured by the change in associations among structural measures across scales because the structural imprint of gap dynamics extends considerably beyond the scale of individual gap

Topographic and forest-stand variables determining epiphytic lichen diversity in the primeval beech forest in the Ukrainian Carpathians

The Uholka-Shyrokyi Luh area of the Carpathian Biosphere Reserve is considered the largest and the most valuable primeval beech forest in Europe for biodiversity conservation. To study the impact of different topographic and forest-stand variables on epiphytic lichen diversity a total of 294 systematically distributed sampling plots were surveyed and 198 epiphytic lichen species recorded in this forest landscape, which has an uneven-aged structure. The obtained data were analysed using a non-metric multidimensional ordination and a generalized linear model. The epiphytic lichen species density at the plot level was mainly influenced by altitude and forest-stand variables. These variables are related to both the light availability i.e. canopy closure, and the habitat diversity, i.e. the developmental stage of the forest stands and the mean stem diameter. We found that lichen species density on plots with a relatively open canopy was significantly higher than on plots with a fairly loose or closed canopy structure. The late developmental stage of forest stands, which is characterized by a large number of old trees with rough and creviced bark, had a strong positive effect on lichen species density. In the Uholka-Shyrokyi Luh primeval forest the mean stem diameter of beech trees significantly correlated with lichen species density per plot. Similar trends in the species diversity of nationally red-listed lichens were revealed. Epiphytic lichens with a high conservation value nationally and internationally were found to be rather abundant in the Uholka-Shyrokyi Luh area, which shows its international importance for the conservation of forest-bound lichens

Towards connecting biodiversity and geodiversity across scales with satellite remote sensing

Issue Geodiversity (i.e., the variation in Earth\u27s abiotic processes and features) has strong effects on biodiversity patterns. However, major gaps remain in our understanding of how relationships between biodiversity and geodiversity vary over space and time. Biodiversity data are globally sparse and concentrated in particular regions. In contrast, many forms of geodiversity can be measured continuously across the globe with satellite remote sensing. Satellite remote sensing directly measures environmental variables with grain sizes as small as tens of metres and can therefore elucidate biodiversity–geodiversity relationships across scales. Evidence We show how one important geodiversity variable, elevation, relates to alpha, beta and gamma taxonomic diversity of trees across spatial scales. We use elevation from NASA\u27s Shuttle Radar Topography Mission (SRTM) and c. 16,000 Forest Inventory and Analysis plots to quantify spatial scaling relationships between biodiversity and geodiversity with generalized linear models (for alpha and gamma diversity) and beta regression (for beta diversity) across five spatial grains ranging from 5 to 100 km. We illustrate different relationships depending on the form of diversity; beta and gamma diversity show the strongest relationship with variation in elevation. Conclusion With the onset of climate change, it is more important than ever to examine geodiversity for its potential to foster biodiversity. Widely available satellite remotely sensed geodiversity data offer an important and expanding suite of measurements for understanding and predicting changes in different forms of biodiversity across scales. Interdisciplinary research teams spanning biodiversity, geoscience and remote sensing are well poised to advance understanding of biodiversity–geodiversity relationships across scales and guide the conservation of nature

Importance of tree species size dominance and heterogeneity on the productivity of spruce-fir-beech mountain forest stands in Europe

12 Pág.There is concern in the scientific community and among forest managers about potential reductions in the provisioning of forest ecosystem services due to the loss of tree species diversity. Many studies have shown how species diversity influences forest functioning, especially productivity, but the influence of structural diversity, such as tree size heterogeneity, has received much less attention. This study focused on understanding the relationship between stand productivity and several structural characteristics of spruce-fir-beech mountain forest stands in Europe. We used a dataset of 89 long-term plots in spruce-fir-beech forests distributed along the European mountains where the three species, Norway spruce (Picea abies (L.) Karst.), silver fir (Abies alba Mill.) and European beech (Fagus sylvatica L.), represent at least 75% of the basal area. Site-dependent conditions were accounted for in a linear mixed-effect basic model, which related the stand productivity with the morphological, climatic and pedological characteristics. The influence of tree species diversity, tree size heterogeneity, species size dominance, and species overlapping in the size distribution on stand productivity was analysed by adding variables to the basic model one by one and evaluating the change in the Akaike's Information Criterion (AIC). The variables that resulted in significant reductions in the AIC, and that were not correlated with each other, were used to build a model to estimate stand productivity. The model showed that in spruce-fir-beech mixed mountain forests (i) when Norway spruce, silver fir and European beech are evenly present within the size distribution (high evenness) the productivity decreases, (ii) the stand productivity increases when the diameter distribution is skewed to the right (higher numbers of smaller individuals), (iii) the stand productivity increases as the proportion of basal area that is spruce increases, and (iv) stand productivity increases with the variability in diameter. We discuss the implications of our results for the management of spruce-fir-beech mountain forest in Europe and for preserving and increasing the stand productivity of these mixed forests.This study was finalized in the frame of the COST (European Cooperation in Science and Technology) Action CLIMO (Climate-Smart Forestry in Mountain Regions - CA15226) financially supported by the EU Framework Programme for Research and Innovation HORIZON 2020. Additionally, Michal Bosela was supported by the Slovak Research and Development Agency (Slovakia) via the project No. APVV-15-0265. Thomas A. Nagel received support from the Slovenian Research Agency (Slovenia) via the project No. J4-1765. Sitkova Zuzana received support by the Slovak Research and Development Agency (Slovakia) via the project No. APVV-16-0325.Peer reviewe

The productivity of mixed mountain forests comprised of Fagus sylvatica, Picea abies, and Abies alba across Europe

11 Pág.Mixed mountain forests of European beech (Fagus sylvatica L.), Norway spruce (Picea abies (L.) Karst), and silver fir (Abies alba Mill.) cover a total area of more than 10 million hectares in Europe. Due to altitudinal zoning, these forests are particularly vulnerable to climate change. However, as little is known about the long-term development of the productivity and the adaptation and mitigation potential of these forest systems in Europe, reliable information on productivity is required for sustainable forest management. Using generalized additive mixed models this study investigated 60 long-term experimental plots and provides information about the productivity of mixed mountain forests across a variety of European mountain areas in a standardized way for the first time. The average periodic annual volume increment (PAI) of these forests amounts to 9.3 m3ha-1y-1. Despite a significant increase in annual mean temperature the PAI has not changed significantly over the last 30 years. However, at the species level, we found significant changes in the growth dynamics. While beech had a PAI of 8.2 m3ha-1y-1 over the entire period (1980-2010), the PAI of spruce dropped significantly from 14.2 to 10.8 m3ha-1y-1, and the PAI of fir rose significantly from 7.2 to 11.3 m3ha-1y-1. Consequently, we observed stable stand volume increments in relation to climate change.T.H. received scholarship from the Rudolf and Helene Glaser Foundation organized in the ‘Stifterverband für die deutsche Wissenschaft’. This study was supported by the grant ‘EVA4.0’, No. CZ.02.1.01/0.0/0.0/16_019/0000803 financed by OP RDE and the Ministry of Science and Higher Education of The Republic of Poland.Peer reviewe

Countrywide Stereo-Image Matching for Updating Digital Surface Models in the Framework of the Swiss National Forest Inventory

Surface models provide key knowledge of the 3-d structure of forests. Aerial stereo imagery acquired during routine mapping campaigns covering the whole of Switzerland (41,285 km2), offers a potential data source to calculate digital surface models (DSMs). We present an automated workflow to generate a nationwide DSM with a resolution of 1 × 1 m based on photogrammetric image matching. A canopy height model (CHM) is derived in combination with an existing digital terrain model (DTM). ADS40/ADS80 summer images from 2007 to 2012 were used for stereo matching, with ground sample distances (GSD) of 0.25 m in lowlands and 0.5 m in high mountain areas. Two different image matching strategies for DSM calculation were applied: one optimized for single features such as trees and for abrupt changes in elevation such as steep rocks, and another optimized for homogeneous areas such as meadows or glaciers. The country was divided into 165,500 blocks, which were matched independently using an automated workflow. The completeness of successfully matched points was high, 97.9%. To test the accuracy of the derived DSM, two reference data sets were used: (1) topographic survey points (n = 198) and (2) stereo measurements (n = 195,784) within the framework of the Swiss National Forest Inventory (NFI), in order to distinguish various land cover types. An overall median accuracy of 0.04 m with a normalized median absolute deviation (NMAD) of 0.32 m was found using the topographic survey points. The agreement between the stereo measurements and the values of the DSM revealed acceptable NMAD values between 1.76 and 3.94 m for forested areas. A good correlation (Pearson’s r = 0.83) was found between terrestrially measured tree height (n = 3109) and the height derived from the CHM. Optimized image matching strategies, an automatic workflow and acceptable computation time mean that the presented approach is suitable for operational usage at the nationwide extent. The CHM will be used to reduce estimation errors of different forest characteristics in the Swiss NFI and has high potential for change detection assessments, since an aerial stereo imagery update is available every six years