The study of modern pollen and vegetation relationships is vital for interpreting fossil pollen records and assessing human impacts on forests, both of which are essential for effective forest management strategies. Despite numerous studies on fossil pollen records in the Rif landscape, there is a notable lack of research specifically focusing on modern pollen and its implications for understanding human impacts on these forests. This paper introduces novel anthropogenic pollen indicators for the Rif Mountains and aims to evaluate the gradients of human impact on the forests of the southern Mediterranean. A combination of modern pollen studies, vegetation surveys, and ordination techniques using both quantitative and presence/absence data were employed, along with various environmental and land-use variables. Canonical correspondence analysis enabled us to assess the relationships between pollen types and environmental variables, allowing us to identify the most anthropogenic pollen indicators associated with land use and human practices, (e.g., Poaceae, Cannabis-t, Olea-t, and Asteraceae). Furthermore, an anthropogenic index score (AIS) was calculated for each sampled location to correlate pollen types with specific levels of human impact using correspondence analysis (CA). These levels were categorised as (a) low (e.g., Cedrus atlantica and Quercus canariensis), (b) moderate (e.g., Erica-t, Arbutus unedo, and Alnus-t), and (c) high (e.g., Cannabis-t, Pistacia lentiscus-t, and Plantago-t).

The introduction of non-native conifers in Patagonia poses a significant environmental threat. These invasive trees disrupt essential ecosystem services, diminish biodiversity, and heighten wildfire risks. This study, driven by the multi-actor partnership "Red PINOS," investigates the potential of citizen science to assess public concern regarding the encroachment of these conifers in wildland–urban interfaces (WUIs) around Bariloche, a Patagonian city (Argentina).

To engage the public in mapping invasive conifer invasions and to gather information on locations of concern, a popular messaging platform was used to collect geospatial data and photographic evidence of these trees within Patagonian WUIs. Participants were invited to join a dedicated group within the platform. Once they joined, the participants received instructions on how to capture and submit relevant data. Citizen participation was heavily promoted across media (social media, radio, TV, newspapers).

We received records of 58 invasion foci, which reported the removal of 839 small-sized individuals up to 1,5 m tall. The most reported species were Pseudotsuga menziesii (57%) and Pinus contorta (24%), followed by Pinus ponderosa (8%). The records were widely distributed across WUIs in Bariloche, including areas dominated by diverse habitats: steppe, shrubland, and forest. Despite being the first public call for citizen participation, the initiative generated a significant number of contributions, suggesting potential for public engagement regarding invasive conifer threats.

These early results represent a significant achievement for Red PINOS, demonstrating the effectiveness of citizen science in fostering participatory governance and highlighting the importance of incorporating public perspectives into invasive species management strategies. As Red PINOS continues to expand its outreach and engagement efforts, citizen science is poised to play an increasingly crucial role in addressing the complex issue of the invasive spread of non-native conifers in Patagonia.

This study investigates whether plant richness or soil conditions affect the productivity of silver birch (Betula pendula Roth.) stands naturally regenerated in central Poland to a greater extent. We analysed 31 plots with birch regeneration aged from 2 to 19 years. At each plot, we determined the features of birch stands, vegetation cover, and soil. Relevés were elaborated according to the Braun--Blannquet procedure and ecological indicator values were calculated according to Zarzycki et al. To describe soil characteristics, we sampled its upper 50 cm layer. In the laboratory, texture, reaction, total carbon, total nitrogen (C and N, respectively), and base cation contents were determined. These features served to calculate the soil fertility index. Tree height measurements were applied to determine the site index (i.e., height at the base age of 25 years) for the analysed stands with a previously developed formula. The stands were also characterised with density and volume. We found that the site index depended significantly on the C:N ratio and soil fertility index (r = 0.36, p = 0.045 and r = -0.49, p = 0.005, respectively), while the stand density and volume were driven by both soil features, namely pH and loam content (r = 0.44, p = 0.013 and r = 0.36, p = 0.044, respectively) and plant richness, i.e., the number of trees and ingrowths (r = -0.52, p = 0.003 and r = -0.37, p = 0.038, respectively). At the early stage of silver birch regeneration, soil conditions play a more important role in stand development than the vegetation cover, which has the negative effect on birch productivity.

Introduction:

We analyzed several leaf morphological traits of two Quercus species widely distributed in the Iberian Peninsula (Q. faginea and Q. pyrenaica) and their hybrids, under contrasting environmental conditions, to determine differences between groups, if they are consistent in the different climatic zones and whether they could confer an advantage to any of the groups in the new predicted climate scenario.

Methods:

This study was carried out in three areas located in the central-west of Spain; in each area, three plots relatively close to each other were selected: one with apparent dominance of Q. faginea, another with dominance of Q. pyrenaica and intermediate zones with both species. In each plot, 10 specimens of the supposedly dominant category in each case were selected, after having been categorized using AFLPs. From each of the 90 specimens, leaf samples were taken and used for morphological analysis, including a total of 18 different traits.

Results:

Only three traits revealed discriminant value between the three genetic groups (leaf weight per unit area, maximum width of the blade and depth of lobes), with the hybrids showing greater proximity to Q. faginea for the rest of the characteristics and consistent results in the different study areas. In all three groups, the leaves tend to be larger, with larger petioles and a greater number of and deeper lobes in the area where temperatures are higher.

Conclusions:

Contrary to what was expected, it was not the hybrids that showed the greatest variability between areas, but rather the Q. faginea individuals that showed the greatest capacity to modify these traits in response to the different climatic conditions between study areas, which, together with their characteristic foliar traits (greater weight per unit area, smaller leaf size and shorter petioles), could determine a greater probability of persistence in the face of climate change.

A new method of digital wood anatomy, pixel-contrast densitometry, was proposed recently for conifers. This technique can replace the X-ray densitometer with software that scans and analyzes the image. A photograph of the wood cross-section consists of pixels, i.e., dots of equal area belonging to either the cell wall or the lumen (empty space). By measuring the number of pixels of the cell walls and lumens, the ratio of the cell wall area to the total area of the scan can be determined. The result of multiplying this ratio by the cell wall matter density is the wood density, averaged for the scan area. We used this method to obtain another alternative parameter of wood structure, wood porosity, that is, the proportion of lumen area within scan. We applied this approach to eight angiosperm species of shrubs and trees in Southern Siberia, varying from ring-porous to diffuse-porous wood. The original software was created to implement the technique automatically.

Before analyzing images, their transformations were performed: (1) the Gaussian smoothing algorithm to clean the photo from noise and (2) the Otsu method to separate the cell walls and lumens. Then, a porosity profile over the entire cross-section of the growth ring can be constructed using the program’s virtual sensor.

Good synchronicity between several measurements within ring proved that profiles of wood porosity describe the ring structure and capture inter-annual differences.

For samples of the three most long-living species, Prunus padus L., Caragana arborescens Lam., and Alnus alnobetula Ehrh., 14-32 year-long series of maximum, mean, and minimum porosity determinations and ring widths were analyzed, showing comparable inter-series correlations, common signals, and consistent inter-relations between these parameters of wood. This means that these easily measured characteristics register environmental variability during their formation. Directions for further research were also discussed.

The success of forest management depends to a large extent on the ecological classification on which it is based [1]. The purpose of this work is to review the current state, priority lines of development and unresolved problems of the original directions of ecological classification: genetic and dynamic forest typologies. Articles in journals on genetic and dynamic forest typologies from the past 10 years were selected and analyzed. Since its inception, genetic forest typology has focused on the study and classification of forests with complex structure and dynamics, and the use of new data analysis methods. The dynamic forest typology was originally developed to classify the disturbed vegetation of northern areas, which have relatively simple structures and dynamics. The current priority research areas of genetic and dynamic forest typology are the improvement of the conceptual and methodological bases of accounting in classification units for forest dynamics; the development of systems of regional classification of disturbed territories for their restoration; and the improvement of the methodology for identifying forest types based on the remote sensing of territories and modern data analysis methods. Currently, these typologies are being developed in parallel, using their scientific basis as well as the strengths of the European forest ecological classifications and the Braun–Blanquet approach. These typologies are of key importance for forest management in the Russian Federation and have great potential for further development under conditions of climate change and anthropogenic impacts.

This research was funded by the state assignment of the Institute Botanic Garden, the Ural Branch of the Russian Academy of Sciences.

References

1. Ivanova, N.; Fomin, V.; Kusbach, A. Experience of Forest Ecological Classification in Assessment of Vegetation Dynamics. Sustainability 2022, 14, 3384. https://doi.org/10.3390/su14063384

Findings from monitoring Greek fir forests in central Greece, regarding radial growth, insect infestations, plant communities, and climate response, have indicated the need for the immediate implementation of further field research within the fir forest ecosystem of the Giona and Parnassus mountains. This underscores the urgency of adopting measures to mitigate the impacts of both abiotic and biotic factors.

Our findings so far, encompassing biometric data, tree ring analysis, observations on plant communities, climatic response, and insect infestations—primarily Choristoneura murinana—across various stands on the mountains, have revealed significant local infestations of varying degrees. In many instances, these infestations were detected in adult trees, particularly in sunny areas or near country roads. Furthermore, our research has revealed the varied ability of the fir trees to adapt to both minor and significant climatic variations. The proposed research aims to monitor, preserve, and protect the fir trees, utilizing new knowledge for informed decision-making in their management. The project's scope includes studying the growth characteristics of the fir forest, mitigating threats from biological factors (primarily the moth Choristoneura murinana-Lepidoptera, Tortricidae) by involving pheromones and other biological methods, promoting natural regeneration, preserving biodiversity, and evaluating the water status of the fir trees in response to climate change. Investigating their interactions and understanding the ecosystem's status concerning the previously mentioned aspects is a significant priority for biological and genetic diversity, landscape aesthetics, recreation, and sustainable regional development (with economic impacts on local beekeepers and guesthouse owners).

The evaluation of the implementation of the National Biodiversity Strategy in Greece has shown partial or minimal progress in addressing new threats and challenges. The proposed project, with specific actions, aligns with the spirit of the National Biodiversity Strategy and contributes to the strategy goals, within the framework of conservation, restoration, and the strengthening of nationwide enhancement actions.

The Amazon rainforest is composed of dense and large vegetation; this implies arduous data collection to study forest dynamics. To assist with these studies, remotely piloted aircrafts (RPAs) can be used to collect images of the forest to acquire characteristics such as the height of the forest, used for biomass and carbon calculations. This technology with machine learning can help in the processing of extensive data; however, it has not yet been applied to Amazon forests, and it offers an opportunity to improve the accuracy of carbon estimates. The aim of this study was to investigate the performance of the artificial intelligence (AI) YOLOv5 in a Google Colab environment to count palms and trees in aerophotogrammetric images captured with the DJI Phantom 4 Pro and a camera. The AI training, validation and testing phases were applied with 1229 images to generate six models to detect and quantify palms and trees in three sites in the state of Amazonas in Brazil. The models were evaluated using the AI metrics precision, recall and mean average precision (mAP) and the remote sensing metrics omission errors, commission errors and accuracy. The models Palms400 and Trees600 obtained the best performances in mAP, with 76% for both; nevertheless, accuracy was highest in the Trees200 and Palms200 models, with 53% and 38%, respectively. In all models, the omission was higher than the commission, where the models did not detect all the objects, while commission errors did not exceed 20%. Thus, it is possible to say that the models performed well and it is recommended to use more different images of the objects in the AI phases, such as different shapes and colors, to improve AI for forestry applications, in order to satisfy remote sensing metrics as well as AI metrics.

In the boreal biome, natural disturbances shape vegetation dynamics and forest recovery. However, increasing anthropogenic disturbances raise concerns about their combined effects on forest regeneration. This is especially relevant in Alberta's boreal forest, where oil exploration creates seismic lines that fragment forests and often coincide with forest harvesting. An important question for seismic line restoration is whether forest harvesting can naturally restore composition and structure, potentially eliminating the need for further restoration efforts. We measured the abundance and composition of trees and shrubs at 15 mesic upland forest sites that were recently harvested and contained within them a conventional seismic line. For each site, we compared two pairs of plots on and off seismic lines to inside and outside of forest harvests to test differences in woody stem regeneration and relative abundance in plant communities. We discovered that harvested seismic lines exhibited approximately 130% more woody stems compared to untreated lines adjacent to mature forests, indicating that forest harvesting contributed to the structural recovery of the forest within the line. However, the co-occurrence of both disturbances resulted in an increase in deciduous stem abundance while decreasing shrub species abundance. Furthermore, we observed a significant interactive effect of the two disturbances on the relative abundance of around 40% of the species assemblage. We demonstrate that the spatial overlap of seismic lines and forest harvesting can facilitate the restoration of forest structure, but also produces a distinct signature on species composition through composite effects. While forest harvesting appeared effective in "erasing" seismic lines without further active restoration efforts, emerging composite effects can significantly influence forest composition, with potential long-term implications for regeneration that require further investigation.

Industries contribute to environmental pollution, and increasing tree cover is an often-proposed urban climate change adaptation strategy. This study examined the governance of amenity trees so as to encourage industries to create policy frameworks to ensure trees perform to their maximum capacity. Twenty industries were randomly selected in Ibadan Metropolis. Structured questionnaires were distributed to three departmental/unit heads in each industry. Data were analysed using descriptive and chi-square analysis.
Nineteen amenity trees were identified. Polyalthia longifolia (30.8%) had the highest number, while Eucalyptus camaldulensis (0.6%) and Alstonia boonei (0.6%) had the smallest. Black Horse Plastic Limited had the most trees (33) on her property, followed by Premier Feedmill (30). Premier Feedmill company, on the other hand, had a higher species richness (six) than Black Horse Plastic Limited, which had only five species. Deepee Global had the fewest trees (eight) in and around their surroundings. Respondents (25.0%) stated that they had no idea when trees were planted, 38.3% revealed that there was no department(unit) responsible for tree management, and there was no precise tree maintenance schedule. However, the planting (38%), watering (55%), pruning (30%), cutting (30%), and cleaning of trees' surroundings (45%) were all conducted when needed. Respondents (98.0%) responded that no funds were set aside for tree management. The year of the planting, who conducted the planning, and the planting objective all have a significant relationship with silvicultural activities practiced in different industries.
The study confirmed that industries have trees, but there is no consistent tree management schedule and funding. It is therefore recommended that every industry creates a policy framework to guide strategic decision making in tree management.