Slovenian Forestry Institute

• Developed ecophysiological models for predicting wood growth cessation in conifers. • Temperature and photoperiod jointly regulate wood growth cessation across species. • Soil moisture showed limited added value in improving model performance. • Historical reconstructions show delayed cE, especially at low latitudes and elevations. Cambium phenology is a crucial process in wood production and carbon sequestration of forest ecosystems. Although cambium phenology has been widely studied, research specifically focusing on the cessation of wood formation remains limited. To better understand the influence of environmental and intrinsic factors on the cessation of wood formation, we built and compared three ecophysiological models ( temperature sum model, photoperiod-influenced temperature sum model and soil moisture- and photoperiod-influenced temperature sum model) in their ability to predict the date of cessation of xylem cell enlargement (cE) in three major Northern Hemisphere conifer species (Black spruce, Norway spruce and Scots pine). We developed these models based on xylogenesis data collected for 130 site‐years across Europe and Canada. Our results demonstrate that the photoperiod-influenced temperature sum model is well-supported by data across all conifer species, with a RMSE of 9.2 days, suggesting that both temperature and photoperiod are critical drivers of wood growth cessation. However, incorporating soil moisture effects does not improve model performance. Our model effectively captures the inter-site variability in cE across a wide environmental gradient, with a fair model efficiency (ME = 0.51 ± 0.22), but performed less well for annual anomalies (ME = 0.10 ± 0.09). Additionally, we found that the total ring cell number also affected prediction accuracy. Using this model, we reconstructed historical trends in cE over the past six decades and found a trend to delayed cessation dates. This delay varied geographically, with slower shifts at higher latitudes and elevations, likely due to constrained cambial responses and conservative growth strategies in colder regions. Our model framework offers a simple yet accurate approach for predicting wood growth cessation at large spatial scales, providing a basis for integrating cambium phenology into land surface models and forest productivity assessments.

The genus Agrilus includes two species, Agrilus planipennis and A. anxius , that are of particular phytosanitary concern and that are regulated by the European Union legislation. This implies that phytosanitary agencies of all EU countries are obliged to establish specific surveillance programs to verify the absence of these species from their territory. These activities commonly consist of the use of green-colored traps, which are however attractive not only for A. planipennis and A. anxius, but also for a wide range of other Agrilus species. For this reason, much time and expertise is required to sort and identify specimens to species, impeding an efficient rapid response. In this study, we tested the efficacy of the Entomoscope, a low-cost, open-source photomicroscope that uses high-resolution digital imaging and allows a pre-trained Convolutional Neural Networks (CNN) model to accurately detect, image and classify insect specimens, for automatic identification of 13 Agrilus species, including A. planipennis and A. anxius . We benchmarked models from three different CNN architectures and selected YOLOv8l as the most robust performer; this model achieved a Top-1 accuracy of 90.2% on a “real-world” test set (i.e. a dataset simulating real surveillance conditions). For most species, including A. planipennis and A. anxius , either no errors or only a few errors were made, whereas for a few native species misidentifications were more common. These results provided proof of concept for an AI-driven surveillance system that can strongly aid in surveillance activities of Agrilus species.

High-resolution carbon isotope ratio (δ13C) measurements of tree rings have the potential to provide seasonal environmental information. However, due to the complexity of the wood formation processes, the reliability of this method for intra-seasonal reconstruction of growing conditions remains unclear. We therefore investigated the intra-annual variation of δ13C in tree rings of three conifer species (Pinus sylvestris L., Picea abies (L.) H. Karst., Abies alba Mill.) across sites from the Swiss Alps to assess their response to seasonal variation of soil water potential (SWP) and vapour pressure deficit (VPD). Intra-annual δ13C values at a resolution of 10 points per year were assessed using laser-ablation isotope-ratio mass spectrometry. Seasonal δ13C patterns were analysed for synchronicity across trees and species, and their correlation with on-site environmental variables was used to determine the driving factors of δ13C, to reconstruct growing-season dynamics, and to estimate the timings of the growth dynamics and the allocation of carbon to xylem formation. The δ13C patterns showed high synchronicity between species, with characteristic maxima in wet and dry years occurring in the middle of the ring and at the end of the ring, respectively. Seasonal δ13C variations reliably reflected atmospheric dryness. Higher than normal soil dryness hindered the integration of further fresh assimilates into the xylem, thus allowing the identification of species- and site-specific threshold conditions that disrupt wood formation. The δ13C of Scots pine shows the strongest correlations with VPD and SWP, making it an excellent indicator of environmental variability. Silver fir appeared to integrate carbon into xylem structural material over a longer season than the other conifers, whilst Norway spruce shows more plastic, site-specific responses to environmental conditions. In conclusion, we identify how atmospheric and soil drought jointly impact tree growth and intra-annual δ13C patterns across conifer species, offering valuable insights for climate reconstructions and wider applications in forest dynamics.

The Triad framework seeks to balance the economic and ecological functions in forested landscapes by combining intensively, extensively, and unmanaged areas, assuming a higher support to biodiversity in extensively rather than in intensively managed forests. We quantified the effects of Triad zoning on biodiversity in (sub)montane eutrophic European beech forests. Using a European-wide multitaxon database and a "virtual" landscape approach (i.e., by resampling empirical data), we evaluated how the proportion of Triad management categories affected the landscape-level species diversity of birds, saproxylic beetles, vascular plants, epiphytic bryophytes, lichens, and wood-inhabiting fungi, as well as multitaxonomic diversity. The results varied greatly among taxonomic groups. Multitaxonomic diversity peaked in landscapes composed of 60% unmanaged and 40% intensively managed forests. While intensive management can benefit some taxa through the creation of open habitats, unmanaged forests are the backbone of biodiversity conservation, underlining the need to safeguard the remaining old-growth forests under natural dynamics, and to extend the current area of unmanaged forests in Europe. Extensive forest management, however, did not contribute to biodiversity conservation as expected. As withdrawing such a high proportion of European forest landscapes from management is unfeasible given the increasing demand for timber, efforts are needed to increase the presence of structural features supporting biodiversity into extensively managed forests.

Controlled experiments suggest that the seasonal build-up of nitrogen (N) limitation constrains the responses of forest autumn phenology to elevated temperatures. Therefore, rising soil N is expected to increase the delaying effects of elevated temperature on the end of the season, i.e., leaf senescence. However, the interactive effects of temperature, soil N, and aridity on xylem autumn phenology remain unknown. We conducted a wide spatial analysis from 75 conifer sites in the Northern Hemisphere and found that rising soil N increases the delaying effects of elevated temperature on the end of xylem cell wall thickening but reduced the delaying effects on the cessation of cell enlargement, especially in humid regions. The contrasting effects of elevated soil N on cell enlargement versus cell wall thickening could affect xylem cell anatomy, thereby induce changes in wood density, and induce a decoupling of stem size growth from photosynthate production. These analyses extend previous findings on forest autumn phenology by systematically investigating the spatial variation in the interactive effects of temperature and soil N on xylem autumn phenology at the cellular scale.

Abstract Bark beetle outbreaks have caused large-scale tree mortality and damage in recent decades, primarily following an increase in large-scale forest disturbances induced by climate change. After tree logging operations, leftover branches are traditionally piled to make the potential brood material less suitable for bark beetles, thereby lowering the risk of subsequent attacks on surrounding trees. On the other hand, the residues could prove valuable to biodiversity by supplementing important habitat, given the apparent decline in deadwood in European forests and its associated saproxylic fauna. Our aim was to identify the most successful method of logging residue management for both bark beetle management and biodiversity. We focussed on Norway spruce felling residues, their associated bark beetle pests and saproxylic insect orders, beetle families, and Cerambycidae species. We prepared four treatments: (i) logging residues in piles, (ii) scattered logging residues, (iii) logging residues removed, and (iv) a control plot with no felling activity. Five plots per treatment were established at each site. In total, three sites were selected: one at a high elevation and two at lower elevations in different parts of Slovenia. The catch was counted to the order level, the attracted beetles were identified to the family level, and Cerambycidae and Scolytinae to the species level. We found that the treatments with residues attracted the highest diversity of insect orders and the most beetles across different families, including Cerambycidae. Furthermore, we found that the species composition differed between control and residue treatments, although no difference was observed in species richness. More bark beetles and a higher number of bark beetle species were attracted to both piled and scattered residues. Thick branches were more frequently attacked in scattered residues. There was no difference in the number of attacked trees (within a plot) one month after treatment. Hence, leaving logging residues in the forest could represent an interesting compromise between pest management and biodiversity conservation. Conflicting aims, such as increasing biodiversity or controlling bark beetles, should be carefully considered in the management decisions.

The dataset includes Pan-European maps of timber volume (Vol), above-ground biomass (AGB), and deciduous-coniferous proportion (DCP) with a pixel size of 10×10 m for the reference year 2020. In addition, a measure of prediction uncertainty is provided for each pixel. The maps have been created using a combination of a Sentinel-2 mosaic, Copernicus layers, and National Forest Inventory (NFI) data. The mapping was done with the k-Nearest Neighbour (kNN, k=7) approach with harmonized data of species-specific Vol and AGB from 14 NFIs consisting of approximately 151 000 field plots across Europe. The maps cover 40 European countries, forming a continuous coverage of the western part of the European continent. A sample of 1/3 of NFI plots was left out for validation, whereas 2/3 of the plots were used for mapping. Maps were created independently for 13 multi-country processing areas. Root-mean-squared-errors (RMSEs) for AGB ranged from 53 % in the Nordic processing area to 73 % in the South-Eastern area. The maps are on average nearly unbiased on European level (1.0 % of the mean AGB), but show significant overestimation for small biomass values (53 % bias for forests with AGB less than 150 t/ha) and underestimation for high biomass values (-55 % bias for forests with AGB higher than 500 t/ha). The created maps are the first of their kind as they are utilizing a large number of harmonized NFI plot observations and consistent remote sensing data for high-resolution forest attribute mapping. While the published maps can be useful for visualization and other purposes, they are primarily meant as auxiliary information in model-assisted estimation where model-related biases can be mitigated, and field-based estimates improved. Therefore, additional calibration procedures were not applied, and especially high Vol and AGB values tend to be underestimated. We therefore discourage from summarizing map values (pixel counting) over areas in interest, as this may inadvertently result in biased estimates.