Effect of Deadwood on Ectomycorrhizal Colonisation of Old-Growth Oak Forests

The impact of anthropogenic transformation of urban soils on ectomycorrhizal fungal communities associated with silver birch (Betula pendula Roth.) growth in natural versus urban soils

Betula pendula Roth. is considered a pioneering plant species important for urban ecosystems. Based on the sequencing of fungal ITS, we characterized the ectomycorrhizal (ECM) communities of twenty silver birch trees growing in a contaminated, highly anthropo-pressured urban environment and in a natural reserve site. We analysed chemical properties of each tree soil samples, focusing on effects of anthropogenic transformation. Three effects of urbanization: high heavy metal content, increased salinity and soil alkalinity, were highly correlated. The examined trees were divided into two forest and two urban clusters according to the level of anthropogenic soil change. The effect of soil transformation on the ECM communities was studied, with the assumption that stronger urban transformation leads to lower ECM vitality and diversity. The results of the study did not confirm the above hypothesis. The ECM colonization was above 80% in all clusters, but the forest clusters had significantly higher share of vital non-ECM root tips than the urban ones. Eleven mycorrhizal fungal species were identified varying from seven to nine and with seven species observed in the most contaminated urban plot. However, the lowest Shannon species diversity index was found in the most natural forest cluster. In conclusion, our findings demonstrate no significant negative effect of the urban stresses on the ECM communities of silver birch suggesting that both forest and urban trees have the potential to generate a similar set of ECM taxa.

Changes in Soil Ectomycorrhizal Fungi Community in Oak Forests along the Urban–Rural Gradient

The ectomycorrhizal fungi communities of forests are closely correlated with forest health and ecosystem functions. To investigate the structure and composition of ectomycorrhizal fungi communities in oak forest soil and their driving factors along the urban–rural gradient, we set up a Quercus acutissima forest transect and collected samples from the center to the edge of Jinan city (urban, suburban, rural). The results showed that the ectomycorrhizal fungal community composition at the phyla level mainly included Basidiomycota and Ascomycota in three sites. At the genus level, the community compositions of ectomycorrhizal fungi, along the urban–rural gradient, exhibited significant differences. Inocybe, Russula, Scleroderma, Tomentella, Amanita and Tuber were the dominant genera in these Quercus acutissima forests. Additionally, the diversity of ectomycorrhizal fungi was the highest in rural Quercus acutissima forest, followed by urban and suburban areas. Key ectomycorrhizal fungi species, such as Tuber, Russula and Sordariales, were identified among three forests. We also found that pH, soil organic matter and ammonium nitrogen were the main driving factors of the differences in ectomycorrhizal fungi community composition and diversity along the urban–rural gradient. Overall, the differences in composition and diversity in urban–rural gradient forest were driven by the differences in soil physicochemical properties resulting from the forest location.

The ectomycorrhizal community of urban linden trees in Gdańsk, Poland

The linden tree (Tilia spp.) is a popular tree for landscaping and urban environments in central and northwest European countries, and it is one of the most popular in cities in Poland. Ectomycorrhizal fungi form a symbiosis with many urban tree species and protect the host plant from heavy metals and against salinity. The aim of this study was to characterise the ECM fungal community of urban linden trees along the tree damage gradient. The study was performed on two sites located in the centre of the city of Gdańsk, in northern Poland. The vitality assessment of urban linden trees was made according to Roloff’s classification. Tree damage classes were related to soil characteristics using principal component analysis. The five ectomycorrhizal fungal species were shared among all four tree damage classes, and Cenococcum geophilum was found to be the most abundant and frequent ectomycorrhizal fungal species in each class. Soil samples collected in the vicinity of trees belonging to the R0 class had significantly lower pH Na, Cl and Pb content than other soils. Our knowledge of ectomycorrhizal communities in urban areas is still limited, and these findings provide new insights into ectomycorrhizal distribution patterns in urban areas.

Detection of Standing Deadwood from Aerial Imagery Products: Two Methods for Addressing the Bare Ground Misclassification Issue

Deadwood mapping is of high relevance for studies on forest biodiversity, forest disturbance, and dynamics. As deadwood predominantly occurs in forests characterized by a high structural complexity and rugged terrain, the use of remote sensing offers numerous advantages over terrestrial inventory. However, deadwood misclassifications can occur in the presence of bare ground, displaying a similar spectral signature. In this study, we tested the potential to detect standing deadwood (h > 5 m) using orthophotos (0.5 m resolution) and digital surface models (DSM) (1 m resolution), both derived from stereo aerial image matching (0.2 m resolution and 60%/30% overlap (end/side lap)). Models were calibrated in a 600 ha mountain forest area that was rich in deadwood in various stages of decay. We employed random forest (RF) classification, followed by two approaches for addressing the deadwood-bare ground misclassification issue: (1) post-processing, with a mean neighborhood filter for “deadwood”-pixels and filtering out isolated pixels and (2) a “deadwood-uncertainty” filter, quantifying the probability of a “deadwood”-pixel to be correctly classified as a function of the environmental and spectral conditions in its neighborhood. RF model validation based on data partitioning delivered high user’s (UA) and producer’s (PA) accuracies (both > 0.9). Independent validation, however, revealed a high commission error for deadwood, mainly in areas with bare ground (UA = 0.60, PA = 0.87). Post-processing (1) and the application of the uncertainty filter (2) improved the distinction between deadwood and bare ground and led to a more balanced relation between UA and PA (UA of 0.69 and 0.74, PA of 0.79 and 0.80, under (1) and (2), respectively). Deadwood-pixels showed 90% location agreement with manually delineated reference to deadwood objects. With both alternative solutions, deadwood mapping achieved reliable results and the highest accuracies were obtained with deadwood-uncertainty filter. Since the information on surface heights was crucial for correct classification, enhancing DSM quality could substantially improve the results.