Search Results (39)

Carbon (C) sequestration and nitrogen (N) and phosphorus (P) accumulation in urban forest green spaces are significant for global climate regulation and alleviating nutrient pollution. However, the effects of management and conservation practices across different urban forest vegetation types on soil C, N, and P contents and stoichiometric ratios remain largely unexplored. We selected forest soils from Guangzhou, a major Metropolis in China, as our study area. Soil samples were collected from two urban secondary forests that naturally regenerated after disturbance (108 samples) and six urban forest parks primarily composed of artificially planted woody plant communities (72 samples). We employed mixed linear models and variance partitioning to analyze and compare soil C, N, and P contents and their stoichiometry and its main driving factors beneath suburban forests and urban park vegetation. These results exhibited that soil pH and bulk density in urban parks were higher than those in suburban forests, whereas soil water content, maximum storage capacity, and capillary porosity were higher in urban forests than in urban parks. Soil C, N, and P contents and their stoichiometry (except for N:P ratio) were significantly higher in suburban forests than in urban parks. Multiple analyzes showed that soil pH had the most pronounced negative influence on soil C, N, C:N, C:P, and N:P, but the strongest positive influence on soil P in urban parks. Soil water content had the strongest positive effect on soil C, N, P, C:N, and C:P, while soil N:P was primarily influenced by the positive effect of soil non-capillary porosity in suburban forests. Overall, our study emphasizes that suburban forests outperform urban parks in terms of carbon and nutrient accumulation, and urban green space management should focus particularly on the impact of soil pH and moisture content on soil C, N, and P contents and their stoichiometry. Full article

The precise spatially explicit data on land cover and land use changes is one of the essential variables for enhancing the quantification of greenhouse gas emissions and removals, which is relevant for meeting the goal of the European economy and society to become climate-neutral by 2050. The accuracy of the machine learning models trained on remote-sensed data suffers from a lack of reliable training datasets and they are often site-specific. Therefore, in this study, we proposed a method that integrates the bi-temporal analysis of the combination of spectral indices that detects the potential changes, which then serve as reference data for the Random Forest classifier. In addition, we examined the transferability of the pre-trained model over time, which is an important aspect from the operational point of view and may significantly reduce the time required for the preparation of reliable and accurate training data. Two types of vegetation losses were identified: woody coverage converted to non-woody vegetation, and vegetated areas converted to sealed surfaces or bare soil. The vegetation losses were detected annually over the period 2018–2021 with an overall accuracy (OA) above 0.97 and a Kappa coefficient of 0.95 for all time intervals in the study regions in Poland and Norway. Additionally, the pre-trained model’s temporal transferability revealed an improvement of the OA by 5 percentage points and the macroF1-Score value by 12 percentage points compared to the original model. Full article

This study explores how floristic composition, diversity, and woody vegetation structure vary across floristic zones in Andean montane forests under the dominance of Aulonemia queko Goudot (Poaceae, Bambusoideae) dominance. As a culturally and ecologically significant non-timber forest product, A. queko plays a key role in shaping plant communities and requires effective propagation strategies for sustainable management. Significant differences in floristic composition were observed among zones, with indicator species identified in the lower and upper zones. However, despite environmental variability, species richness and structural attributes remained stable across the elevation gradient, suggesting resilience in woody plant communities. A. queko density was highest in the upper zone, while its basal area peaked in the lower and middle zones, probably shaping floristic composition through competitive interactions and habitat modification. Propagation experiments revealed that shoots with rhizomes exhibited higher survival and growth, particularly in mulch substrates with 1000 ppm indole-3-butyric acid (IBA), highlighting the importance of shoot type, substrate, and hormone dose. These findings suggest that A. queko is a structuring species and a potential restoration target. However, its dominance may alter forest composition, requiring adaptive management strategies that balance its ecological role with conservation and sustainable use, ensuring biodiversity and ecosystem resilience. Full article

Leaf water potential ($\psi$_leaf) is a key indicator of plant water status, but its measurement is labor-intensive and limited in spatial coverage. While remote sensing has emerged as a useful tool for estimating vegetation water status, $\psi$_leaf remains unexplored, particularly in mixed forests. Here, we use spectral indices derived from unmanned aerial vehicle-based hyperspectral imaging and machine learning algorithms to assess $\psi$_leaf in a mixed, multi-species Mediterranean forest comprised of five key woody species: Pinus halepensis, Quercus calliprinos, Cupressus sempervirens, Ceratonia siliqua, and Pistacia lentiscus. Hyperspectral images (400–1000 nm) were acquired monthly over one year, concurrent with $\psi$_leaf measurements in each species. Twelve spectral indices and thousands of normalized difference spectral index (NDSI) combinations were evaluated. Three machine learning algorithms—random forest (RF), extreme gradient boosting (XGBoost), and support vector machine (SVM)—were used to model $\psi$_leaf. We compared the machine learning model results with linear models based on spectral indices and the NDSI. SVM, using species information as a feature, performed the best with a relatively good $\psi$_leaf assessment (R² = 0.53; RMSE = 0.67 MPa; rRMSE = 28%), especially considering the small seasonal variance in $\psi$_leaf ($\pm \sigma$ = 0.8 MPa). Predictions were best for Cupressus sempervirens (R² = 0.80) and Pistacia lentiscus (R² = 0.49), which had the largest $\psi$_leaf variances ($\pm \sigma$ > 1 MPa). Aggregating data at the plot scale in a ‘general’ model markedly improved the $\psi$_leaf model (R² = 0.79, RMSE = 0.31 MPa; rRMSE = 13%), providing a promising tool for monitoring mixed forest $\psi$_leaf. The fact that a non-species-specific, ‘general’ model could predict $\psi$_leaf implies that such a model can also be used with coarser resolution satellite data. Our study demonstrates the potential of combining hyperspectral imagery with machine learning for non-invasive $\psi$_leaf estimation in mixed forests while highlighting challenges in capturing interspecies variability. Full article

The combination of logging, burning, and livestock farming has been the main driver of European landscape sustainability for thousands of years. Whether or not livestock could keep these habitats on their own is under debate when extensive livestock grazing is kept understory in forests of high environmental value that, in turn, are affected by global warming. In this work, the impact of beef cattle on the diversity, shrub cover, and primary production of the Atlantic Pyrenean oak (Quercus pyrenaica Willd.) in northern Spain has been evaluated. The research studied their feeding habits using the faecal cuticle micro histological analysis in dung samples. Then, the effects of cattle grazing on the cover and alpha diversity of woody plants were evaluated. Finally, oaks’ primary production and phenology in grazed and control areas were compared. The results show that cattle feed on woody (an average of 30% of non-leguminous woody) and annual plant species (more than 20% of forbs) but do not affect plant cover or alpha diversity of vegetation. However, oak phenology differed between grazed and ungrazed treatments, probably due to the spatial variability of grazed forests. It can be concluded that understory grazing in Pyrenean oak forests could be considered a sustainable silvopastoral activity with a neutral impact on forest integrity. Full article

Riparian softwood forests support numerous ecological functions and high biodiversity. In the context of the LIFE+ Traisen project, a non-regulated new riverbed for the lower Traisen River (“New Traisen”) was created within an artificially lowered floodplain corridor. Using vegetation monitoring from 2014 to 2021, we determined (i) the role of Solidago gigantea in the establishment of softwood forests, (ii) the habitat parameters (such as flooding height, fine substrate layer thickness, and vegetation cover) that impact the establishment and growth of woody plants, and (iii) the successional phase at which woody plants become established, as well as the potential creation of new germination habitats. During early succession, the softwood species, as light-tolerant pioneer species, colonized the open sites together with S. gigantea and subsequently established a floodplain softwood forest. Unexpectedly, we observed negative forest development only when the S. gigantea cover exceeded 90%. Neither the habitat parameters nor S. gigantea cover significantly impacted tree occurrence. However, we highlight the need for optimum habitat parameters for softwood forest development in early succession phases, ideally before S. gigantea forms dense, monospecific stands. Tailored monitoring strategies are needed to guide the succession of such semi-aquatic habitats toward the development of the desired habitat type. Full article

Old growth forests are increasingly rare but important carbon sinks which harbour rich biodiversity. Chronic browsing by the white-tailed deer (Odocoileus virginianus) is a threat to the sustainability of the services provided by these forests, particularly in northern temperate forests where deer numbers have increased in recent decades (driven by stricter hunting rules and reduced predation) and necessitating local monitoring of vegetation responses. The objective of this study was to determine the effects of deer exclusion on tree regeneration dynamics and soil nutrients in an old growth Carolinian forest. This was performed using exclusion fencing and tip-up mounds at McMaster Forest Nature Preserve and the Sheelah Dunn Dooley Nature Sanctuary in Hamilton Ontario. Tree regeneration was surveyed from thirty 1 m × 1 m quadrats within exclusion plots and another thirty quadrats from deer-browsed areas adjacent to the exclusion plots. Soil samples were taken from each quadrat to analyze browsing impacts on nitrate, phosphate and soil organic matter. Red oak (Quercus rubra) was planted at the top and base of tip-up mounds of varying heights and widths and monitored for deer access and browsing activity. Results show a significantly higher density of woody plants within exclosures compared to non-exclosures (p = 0.0089) and twice more abundance of highly palatable species within the exclosures. However, species richness (p > 0.05) and diversity (p > 0.05) were minimally impacted by deer browsing, showing a resilient old growth forest. Soil nitrate was consistently higher in the non-exclosures, while phosphate was consistently higher within deer exclosures. Finally, more seedlings survived at the top of mounds than the bases, showing the potential of tip-up mounds to be a natural method of deer exclusion and a critical avenue for restoring over-browsed forests. Full article

Water limitations will pose significant challenges to forest ecosystems across Europe. To gain a deeper understanding of the potential impacts, we investigated the response of the common shrub Crataegus monogyna to two summer droughts, each followed by rewatering. The experimental design consisted of a common garden with potted saplings from a local Belgian (n = 48), a Swedish (n = 47), and a Spanish-Pyrenean provenance (n = 48). We quantified the effects on growth and leaf phenology, focusing on the legacies in the year following the droughts. Responses were influenced by the severity of the drought and by its timing. Most strikingly, height increment was enhanced by 24% (p = 0.046) in comparison to the controls in the year following the droughts in the group of plants that endured the two drought treatments, each time without developing visible stress symptoms. Only one such mild drought, whether early or late summer, did not lead to this response, suggesting stress memory acting as a growth promoter. A late summer drought that resulted in visible drought symptoms led to a reduced diameter increment in the year following the droughts, independent of the preceding treatment (severe, mild, or no drought), whereas this was not the case for a similar drought in early summer. Minor leaf phenological responses were detected in the year following the droughts. Finally, the non-local provenances did not respond in a deviating way to the droughts compared to the local provenance. Our findings contribute to the prediction of carbon sequestration in forests and other woody vegetations in the temperate regions of Europe. Full article

The spread of neophytes (non-native plant species) challenges the conservation status and ecological integrity of forests, especially in lowland areas. Long-term resurvey studies are needed to evaluate the temporal dynamics of neophytes in forests; however, such data are scarce. In 2023, we resampled a set of 45 permanent vegetation plots (established in 1992/93) in two forest vegetation types: oak–hornbeam forests dominated by Quercus robur and colline oak–beech forests dominated by Q. petraea. Over the last 30 years, oak forests have experienced extensive oak tree mortality, with the degree of habitat degradation being greater in Q. robur forests. In the early 1990s, only three neophytes with low abundance were recorded across all plots. In the 2023 resurvey, the total number of neophytes increased to 22 species (15 herbaceous and 7 woody species), comprising 6.9% of the total species pool in the understory layer. The increase in the plot-level number and cover of neophytes was significant in plots dominated by Q. robur but not in those with Q. petraea. The most frequent neophytes were Impatiens parviflora (present in 31% of plots), Solidago gigantea (27%), Erigeron annuus (16%) and Erechtites hieraciifolia (16%). The richness and cover of neophytes were significantly affected by the tree layer cover (negative correlation) and the degree of soil disturbance (positive correlation). All neophytes established in disturbed patches, whereas the occurrence of I. parviflora was exceptional as it was able to colonize less degraded, shaded understory environments. Habitat degradation (the mortality-induced loss of stand-forming oak trees resulting in extensive tree layer cover decrease) emerged as a key driver promoting neophyte proliferation, coupled with the impact of management-induced disturbances affecting overstory and soil conditions. The spread is expected to continue or even intensify in the future because novel light regimes and disturbances make forest habitats less resistant to neophyte proliferation. Full article

The use of pixel-based remote sensing techniques in archaeology is usually limited by spectral confusion between archaeological material and the surrounding environment because they rely on the spectral contrast between features. To deal with this problem, we investigated the possibility of using geographic object-based image analysis (GEOBIA) to predict archaeological and non-archaeological features. The chosen study area was previously occupied by farming communities and is characterised by natural soils (non-sites), vitrified dung, non-vitrified dung, and savannah woody vegetation. The study uses a three-stage GEOBIA that comprises (1) image object segmentation, (2) feature selection, and (3) object classification. The spectral mean of each band and the area extent of an object were selected as input variables for object classifications in support vector machines (SVM) and random forest (RF) classifiers. The results of this study have shown that GEOBIA approaches have the potential to map archaeological landscapes. The SVM and RF classifiers achieved high classification accuracies of 96.58% and 94.87%, respectively. Visual inspection of the classified images has demonstrated the importance of the aforementioned models in mapping archaeological and non-archaeological features because of their ability to manage the spectral confusion between non-sites and vitrified dung sites. In summary, the results have demonstrated that the GEOBIAs ability to incorporate spatial elements in the classification model ameliorates the chances of distinguishing materials with limited spectral differences. Full article

It is generally accepted that mycobiota diversity in urban greenhouses is poorer than in natural ecosystems, but our knowledge on this field of research is fragmentary. Here, we present the results of a long-term study of aphyllophoroid macrofungi (Basidiomycota) forming fruitbodies on non-native sub/tropical woody and herbaceous plants in the greenhouses of Saint Petersburg, Moscow, and Ekaterinburg botanical gardens located in the hemiboreal vegetation subzone of Eastern Europe. Over 20 years of research, fruitbodies of 58 species of aphyllophoroid fungi have been identified. Fungal species that developed on the wooden structures of greenhouses and building materials made of local wood are discussed separately. The list of fungi on non-native substrates is dominated by saprobes (93.1% of total list) as well as mycorrhizal with basidiomata on plants (8.6%). Phytopathogens have the lowest number (7.0%), and ¾ of species are widespread locally. Non-native plants are dominated by native fungal species (78.9%), while the percentage of non-native species is low (21.1%). In the three surveyed cities, the area of the studied greenhouses is 2.8 ha, and not a single species of fungi has been found twice on the same substrate. Half of the identified species are characterized by a single specimen (29 species/50.9%). Hymenochaete rheicolor was discovered in Russia for the first time and its known distribution is discussed. Only six (Antrodia gossypium, Hyphodontia arguta, Lyomyces sambuci, Peniophora cinerea, Ramariopsis kunzei, and Trechispora farinacea) local species (10.5%) were collected in all the three cities. The α-diversity of mycobiota (mean number of species per site, Shannon Index, and Menhinick Index) in the Ekaterinburg’s greenhouses is 1.2–3.0 times lower compared to suburban forest parks and old-growth natural forests, while β-diversity (Whittaker Index, Jaccard Index, and Morisita–Horn Index), on the contrary, is 2.1–7.7 times higher. With the plants’ age, the probability of detecting fungi on them increases significantly. In greenhouses, phytopathogenic aphyllophoroid macrofungi are collected on woody plants only, but the probability of their development is not related to the plants’ age. Full article

This paper specifies the invasibility of common plant community types in the natural habitats of the Middle Urals. Invasibility was defined as the vulnerability of a community to alien plant species invasions, regardless of the conditions in which the community existed. We analyzed 749 vegetation relevés made in natural bogs, floodplains, rocky grasslands, meadows, and forest communities. We surveyed urban and non-urban habitats (30–40 km from the city). Invasibility was calculated in two different ways based on two parameters: the number and proportion of alien species in the relevé. These invasibility parameters are widely applicable and comparable, scale-independent, measurable, and reliable, based on data that do not require the destruction of ecosystems or biota and are based on available data. Based on the invasibility degree, we identified three community-type groups with two subgroups in one group. In ascending order of invasibility degree, the community types were arranged as follows: (1) bogs with and without trees; (2a) coniferous forests; grass communities in floodplains; (2b) deciduous forests, coniferous plantations, floodplain communities with woody plants; and (3) dry meadows and rocky grasslands. Obtained results of the assessment of different plant community invasibility may be used to understand patterns of alien plant distribution in local habitats and the reasons for the different vulnerability of communities to plant invasions. Full article

In light of pollinator decline, plant species suitable for the restoration and conservation of pollinators need to be selected. In this systemic review, we concentrated on the importance of NFWV (non-forest woody vegetation, i.e., linear or grouped trees/shrubs) for pollinators across agricultural landscapes. In the temperate climate zone, flowering trees and shrubs provide nectar sugar (energy) and pollen (nutrients) for managed and wild pollinators. They also create nesting niches and serve as host plants that support the full life cycle of wild pollinators. The creation of woodland strips/groups is a cost-effective and time-saving strategy to improve self-repeatable nectar and pollen resources on a landscape scale. The spatial distribution of NFWV can help to create an entire network of pollinator-friendly habitats. NFWV can support the continuity of food resources outside of the crop flowering season, i.e., during seasonal bottlenecks. This concept also offers other environmental benefits (e.g., water and air quality improvement, climate mitigation). However, future work should address the usefulness of trees/shrubs for different crops and regions to develop a network of flower-rich corridors. Likewise, more advanced and detailed studies are necessary to determine the qualitative characteristics of nectar and pollen, which may result in optimization of pollinator nutrition. Full article

European hornbeam (Carpinus betulus L.) is a tree species widely distributed in Europe and the Asian part of the Near East. However, since European hornbeam is not very attractive for commercial purposes, scientific interest in this species has been rather sparse. Our study focused on dense young (up to 10 years old) European hornbeam stands originating from natural regeneration from seeds in Slovakia because in future the importance of this species may increase due to the climate change. We combined previously constructed tree-level biomass models, data on basic leaf traits, i.e., weight and area, and measurements from thirty plots located at ten different sites across Slovakia to construct stand-level allometric relations of the biomass stock in tree components, i.e., leaves, branches, bark, stem under bark and roots, to mean stand diameter at stem base, i.e., at the ground level. Moreover, we calculated and modelled leaf characteristics, namely the specific leaf area (SLA), leaf area ratio (LAR) and leaf area index (LAI), at a stand level. The total tree biomass stock including all tree components ranged between 0.75 and 13.63 kg per m², out of which the biomass of stem with bark was from 0.31 to 8.46 kg per m². The biomass models showed that the contribution of roots (omitting those with a diameter under 2 mm) decreased with the increasing mean stand diameter at stem base, whereas the opposite pattern was observed for branches and stem biomass. Further, we found that the mean stand diameter at stem base was a good predictor of both LAR and LAI. The results indicated the high photosynthetic efficiency of European hornbeam leaves per one-sided surface leaf area. Moreover, the growth efficiency (GE), expressed as the biomass increment of woody parts per leaf area unit, of young European hornbeam trees was high. The models proved a close positive linear correlation between LAI and stand biomass stock that may be used for estimating the biomass in young stands from LAI that can be measured using non-destructive terrestrial or aerial methods. The results further indicated that young stands may sequester a non-negligible quantity of carbon; therefore, they should not be omitted from local or country-wide estimates of carbon stocks in forest vegetation. Full article

Urban ecosystems have great potential for urban biodiversity conservation, but achieving conservation goals relies on comprehensive ecological assessments to assist in active management practices; however, land use changes in urban ecosystems have led to unique abiotic and biotic inputs that have affected and altered below-ground soil composition, with potentially negative implications across trophic levels. We investigated the relationships between soil attributes and key indicators of forest health, specifically the composition and condition of vegetation and soils in an urban remnant forest area. The major findings revealed a dominance of native plant species, with some invasion by non-native plants, and acidic high-carbon soils sufficient in most plant available nutrients. Moreover, stepwise regression analysis showed significant relationships between soil attributes and native species diversity and abundance; prevalence of invasive plants (Lonicera maackii, Pueraria montana, Albizia julibrissin, Ligustrum sinense, Lonicera japonica, Ailanthus altissima, and Paulownia tomentosa); forest canopy gaps; and fine woody debris on the forest floor. These findings identified attributes of urban soils affecting forest health and biodiversity conservation, with broad implications for the long-term monitoring of urban forests. Full article