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Ancient coppice woods are areas that reflect long-term human influence and contain high species biodiversity. In this type of forest we aimed to: (i) analyze the below- and above ground biomass of stools and estimate the age of largest stool; (ii) define a “zone of interference” for coppices; (iii) describe and classify variability in the shape and size of coppice stools; (iv) define the specific characteristics of the spatial distribution of stems and stools. The study was conducted in the Podyjí National Park, Czech Republic, where two old oak coppice stands were fully stem mapped: Lipina (3.90 ha) and Šobes (2.37 ha). Cores were processed using TimeTable and PAST4. Below- and above-ground biomass of the largest stools was computed using the data from terrestrial laser scanner. Tree zones of influence were analyzed with V-Late landscape analysis tools using Shape Index. The pair correlation function and L function were used to describe the spatial patterns of trees with DBH ≥ 7 cm, and the null model of Complete Spatial Randomness and Matérn cluster process were tested. For a modeled old stool, we estimated a ratio of 2:1 for above/below ground volume with no reduction of below ground biomass regarding the hollow roots. The age of the largest stool was estimated 825 ± 145 (SE) years. An “Inner Zone of Influence” was defined, with a total area covering 323 m2 ha-1. The median area of this zone in both plots was 0.40 m2 for all trees, 0.23 m2 for singles and 0.87 m2 for stools. The Matérn cluster process was successfully fitted to our empirical data. In this model, the mean cluster radius ranged between 1.9 to 2.1 m and mean number of points per cluster was 1.7 and 1.9. The most prevalent characteristics of these ancient oak coppices were their compact shape and clustered spatial distribution up to 10 m.

A conversion of previously even-aged pine-dominated forests to uneven-aged and multi-functional oak-dominated forests has been ongoing since 1993 in the Pyramida experimental forest (95 ha) situated in the buffer zone of Podyjí National Park, Czech Republic. Based on repeated surveys in 1992, 2003 and 2013, the conversion was assessed according to changes in: (i) the proportion of species; (ii) the distribution of DBH; (iii) the distribution of patches; and (iv) the distribution of forest types. The proportion of conifers decreased from 61.0% to 42.0%, and the proportion of broadleaved species increased accordingly. A sharp decline in the number of trees in the DBH class 70-109 mm was caused by the intense release of understorey broadleaved trees in young Scots pine small pole stage stands. The number of large habitat trees steadily increased in the DBH classes 430+ mm. The mean size of one patch decreased from 0.8 ha (1992) to 0.4 ha (2013). The spatial proportion of the target forest type (uneven-aged oak-dominated forest) increased from 8.5% in 1992 to 45.0% in 2013, and 35.1% of the area was fully converted during the 20 years. We expect 69.1% of the area to be converted after 30 years (2023).

Primary forests, defined here as forests where the signs of human impacts, if any, are strongly blurred due to decades without forest management, are scarce in Europe and continue to disappear. Despite these losses, we know little about where these forests occur. Here, we present a comprehensive geodatabase and map of Europe's known primary forests. Our geodatabase harmonizes 48 different, mostly field-based datasets of primary forests, and contains 18,411 individual patches (41.1 Mha) spread across 33 countries. When available, we provide information on each patch (name, location, naturalness, extent and dominant tree species) and the surrounding landscape (biogeographical regions, protection status, potential natural vegetation, current forest extent). Using Landsat satellite-image time series (1985-2018) we checked each patch for possible disturbance events since primary forests were identified, resulting in 94% of patches free of significant disturbances in the last 30 years. Although knowledge gaps remain, ours is the most comprehensive dataset on primary forests in Europe, and will be useful for ecological studies, and conservation planning to safeguard these unique forests., (© 2021. The Author(s).)

Deadwood represents an important carbon stock and contributes to climate change mitigation. Wood decomposition is mainly driven by fungal communities. Their composition is known to change during decomposition, but it is unclear how environmental factors such as wood chemistry affect these successional patterns through their effects on dominant fungal taxa. We analysed the deadwood of Fagus sylvatica and Abies alba across a deadwood succession series of >40 years in a natural fir-beech forest in the Czech Republic to describe the successional changes in fungal communities, fungal abundance and enzymatic activities and to link these changes to environmental variables. The fungal communities showed high levels of spatial variability and beta diversity. In young deadwood, fungal communities showed higher similarity among tree species, and fungi were generally less abundant, less diverse and less active than in older deadwood. pH and the carbon to nitrogen ratio (C/N) were the best predictors of the fungal community composition, and they affected the abundance of half of the dominant fungal taxa. The relative abundance of most of the dominant taxa tended to increase with increasing pH or C/N, possibly indicating that acidification and atmospheric N deposition may shift the community composition towards species that are currently less dominant.

Current and planned space missions will produce aboveground biomass density data products at varying spatial resolution. Calibration and validation of these data products is critically dependent on the existence of field estimates of aboveground biomass and coincident remote sensing data from airborne or terrestrial lidar. There are few places that meet these requirements, and they are mostly in the northern hemisphere and temperate zone. Here we summarize the potential for low-altitude drones to produce new observations in support of mission science. We describe technical requirements for producing high-quality measurements from autonomous platforms and highlight differences among commercially available laser scanners and drone aircraft. We then describe a case study using a heavy-lift autonomous helicopter in a temperate mountain forest in the southern Czech Republic in support of calibration and validation activities for the NASA Global Ecosystem Dynamics Investigation. Low-altitude flight using drones enables the collection of ultra-high-density point clouds using wider laser scan angles than have been possible from traditional airborne platforms. These measurements can be precise and accurate and can achieve measurement densities of thousands of points · m -2 . Analysis of surface elevation measurements on a heterogeneous target observed 51 days apart indicates that the realized range accuracy is 2.4 cm. The single-date precision is 2.1-4.5 cm. These estimates are net of all processing artifacts and geolocation errors under fully autonomous flight. The 3D model produced by these data can clearly resolve branch and stem structure that is comparable to terrestrial laser scans and can be acquired rapidly over large landscapes at a fraction of the cost of traditional airborne laser scanning.

Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene., Main Types of Variables Included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record., Spatial Location and Grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km 2 (158 cm 2 ) to 100 km 2 (1,000,000,000,000 cm 2 )., Time Period and Grain: BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year., Major Taxa and Level of Measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates., Software Format: .csv and .SQL.

Hülsmann and Hartig suggest that ecological mechanisms other than specialized natural enemies or intraspecific competition contribute to our estimates of conspecific negative density dependence (CNDD). To address their concern, we show that our results are not the result of a methodological artifact and present a null-model analysis that demonstrates that our original findings-(i) stronger CNDD at tropical relative to temperate latitudes and (ii) a latitudinal shift in the relationship between CNDD and species abundance-persist even after controlling for other processes that might influence spatial relationships between adults and recruits., (Copyright © 2018, American Association for the Advancement of Science.)

Dead wood represents an important pool of organic matter in forests and is one of the sources of soil formation. It has been shown to harbour diverse communities of bacteria, but their roles in this habitat are still poorly understood. Here, we describe the bacterial communities in the dead wood of Abies alba, Picea abies and Fagus sylvatica in a temperate natural forest in Central Europe. An analysis of environmental factors showed that decomposing time along with pH and water content was the strongest drivers of community composition. Bacterial biomass positively correlated with N content and increased with decomposition along with the concurrent decrease in the fungal/bacterial biomass ratio. Rhizobiales and Acidobacteriales were abundant bacterial orders throughout the whole decay process, but many bacterial taxa were specific either for young (<15 years) or old dead wood. During early decomposition, bacterial genera able to fix N2 and to use simple C1 compounds (e.g. Yersinia and Methylomonas) were frequent, while wood in advanced decay was rich in taxa typical of forest soils (e.g. Bradyrhizobium and Rhodoplanes). Although the bacterial contribution to dead wood turnover remains unclear, the community composition appears to reflect the changing conditions of the substrate and suggests broad metabolic capacities of its members., (© FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Theory predicts that higher biodiversity in the tropics is maintained by specialized interactions among plants and their natural enemies that result in conspecific negative density dependence (CNDD). By using more than 3000 species and nearly 2.4 million trees across 24 forest plots worldwide, we show that global patterns in tree species diversity reflect not only stronger CNDD at tropical versus temperate latitudes but also a latitudinal shift in the relationship between CNDD and species abundance. CNDD was stronger for rare species at tropical versus temperate latitudes, potentially causing the persistence of greater numbers of rare species in the tropics. Our study reveals fundamental differences in the nature of local-scale biotic interactions that contribute to the maintenance of species diversity across temperate and tropical communities., (Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Terrestrial laser scanning is a powerful technology for capturing the three-dimensional structure of forests with a high level of detail and accuracy. Over the last decade, many algorithms have been developed to extract various tree parameters from terrestrial laser scanning data. Here we present 3D Forest, an open-source non-platform-specific software application with an easy-to-use graphical user interface with the compilation of algorithms focused on the forest environment and extraction of tree parameters. The current version (0.42) extracts important parameters of forest structure from the terrestrial laser scanning data, such as stem positions (X, Y, Z), tree heights, diameters at breast height (DBH), as well as more advanced parameters such as tree planar projections, stem profiles or detailed crown parameters including convex and concave crown surface and volume. Moreover, 3D Forest provides quantitative measures of between-crown interactions and their real arrangement in 3D space. 3D Forest also includes an original algorithm of automatic tree segmentation and crown segmentation. Comparison with field data measurements showed no significant difference in measuring DBH or tree height using 3D Forest, although for DBH only the Randomized Hough Transform algorithm proved to be sufficiently resistant to noise and provided results comparable to traditional field measurements.

Host size and distance from an infected plant have been previously found to affect mistletoe occurrence in woody vegetation but the effect of host plant competition on mistletoe infection has not been empirically tested. For an individual tree, increasing competition from neighbouring trees decreases its resource availability, and resource availability is also known to affect the establishment of mistletoes on host trees. Therefore, competition is likely to affect mistletoe infection but evidence for such a mechanism is lacking. Based on this, we hypothesised that the probability of occurrence as well as the abundance of mistletoes on a tree would increase not only with increasing host size and decreasing distance from an infected tree but also with decreasing competition by neighbouring trees. Our hypothesis was tested using generalized linear models (GLMs) with data on Loranthus europaeus Jacq., one of the two most common mistletoes in Europe, on 1015 potential host stems collected in a large fully mapped plot in the Czech Republic. Because many trees were multi-stemmed, we ran the analyses for both individual stems and whole trees. We found that the probability of mistletoe occurrence on individual stems was affected mostly by stem size, whereas competition had the most important effects on the probability of mistletoe occurrence on whole trees as well as on mistletoe abundance. Therefore, we confirmed our hypothesis that competition among trees has a negative effect on mistletoe occurrence.

Global change is impacting forests worldwide, threatening biodiversity and ecosystem services including climate regulation. Understanding how forests respond is critical to forest conservation and climate protection. This review describes an international network of 59 long-term forest dynamics research sites (CTFS-ForestGEO) useful for characterizing forest responses to global change. Within very large plots (median size 25 ha), all stems ≥ 1 cm diameter are identified to species, mapped, and regularly recensused according to standardized protocols. CTFS-ForestGEO spans 25 °S-61 °N latitude, is generally representative of the range of bioclimatic, edaphic, and topographic conditions experienced by forests worldwide, and is the only forest monitoring network that applies a standardized protocol to each of the world's major forest biomes. Supplementary standardized measurements at subsets of the sites provide additional information on plants, animals, and ecosystem and environmental variables. CTFS-ForestGEO sites are experiencing multifaceted anthropogenic global change pressures including warming (average 0.61 °C), changes in precipitation (up to ± 30% change), atmospheric deposition of nitrogen and sulfur compounds (up to 3.8 g N m(-2) yr(-1) and 3.1 g S m(-2) yr(-1)), and forest fragmentation in the surrounding landscape (up to 88% reduced tree cover within 5 km). The broad suite of measurements made at CTFS-ForestGEO sites makes it possible to investigate the complex ways in which global change is impacting forest dynamics. Ongoing research across the CTFS-ForestGEO network is yielding insights into how and why the forests are changing, and continued monitoring will provide vital contributions to understanding worldwide forest diversity and dynamics in an era of global change., (© 2014 John Wiley & Sons Ltd.)