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Using measurements from high resolution monitoring of radial tree-growth we present new data of the growth reactions of four widespread broadleaved tree-species to the combined European drought years 2018 and 2019. We can show that, in contrast to field crops, trees could make better use of the winter soil moisture storage in 2018 which buffered them from severe drought stress and growth depressions in this year. Nevertheless, legacy effects of the 2018 drought accompanied by sustained low soil moisture conditions (missing recharge in winter) and again higher than average temperatures and low precipitation in spring/summer 2019 have resulted in severe growth reductions for all studied tree-species in this year. This highlights the pivotal role of soil water recharge in winter. Although short term resistance to hot summers can be high if sufficient winter precipitations buffers forest stands from drought damage, legacy effects will strongly impact tree growth in subsequent years if the drought persists. The two years 2018 and 2019 are extreme with regard to historical instrumental data but, according to regional climate models, resemble rather normal conditions of the climate in the second half of the 21st century. Therefore the observed strongly reduced growth rates can provide an outlook on future forest growth potential in northern Central Europe and beyond.

Range dynamics of tree species are largely driven by seedling establishment and survival, mainly at and beyond current treelines. Although numerous studies document the growth of mature white spruce (Picea glauca) trees in Alaska, research on seedling establishment and growth, particularly dendroecological studies addressing climate sensitivity, remains limited. This study examines seedling densities and age distributions, growth performance, and climate–growth correlations of white spruce seedlings at five Alaskan sites: a “dry treeline” with potential drought limitations and the adjacent “dry forest,” a reference forest in Interior Alaska, and a “cold treeline” with expected cold temperature limitations and the adjacent “cold forest” in the Brooks Range. Seedling densities were highest at the cold treeline and especially the cold forest, moderate at the reference forest and dry forest, and very low at the dry treeline. Growth rates and height:diameter ratio were greatest at the dry treeline, with slightly lower growth at the cold treeline and cold forest. We found some evidence for drought sensitivity in spring at the dry treeline and in summer at the dry forest, while warm temperatures in fall positively influenced seedling growth at both sites. Notably, growth was more often significantly correlated with climate during the transitional seasons compared to only once in summer and not at all in winter. This pattern likely reflects that seedling growth, especially at the cold sites, is shaped less by direct macroclimatic influences and more by indirect effects on growing season dynamics, such as snow accumulation and melt. Despite growth peaking at the dry treeline, low seedling densities suggest a potential retreat of Pi. glauca at dry, low‐elevation treelines in Alaska. In contrast, high seedling densities and growth rates at the cold treeline and cold forest indicate favorable conditions for seedling establishment and densification. The complexity of seedling growth and climate–growth correlations demands careful consideration, as growth is only partially influenced by macroclimate and is likely more strongly shaped by factors like competition, snowpack, soil moisture and temperature, and nutrient availability. Overall, our local data lend credibility to the hypothesized biome shift of white spruce, albeit unfolding at a slow pace.

Recent research using repeat photography, long-term ecological monitoring and dendrochronology has documented shrub expansion in arctic, high-latitude and alpine tundra ecosystems. Here, we (1) synthesize these findings, (2) present a conceptual framework that identifies mechanisms and constraints on shrub increase, (3) explore causes, feedbacks and implications of the increased shrub cover in tundra ecosystems, and (4) address potential lines of investigation for future research. Satellite observations from around the circumpolar Arctic, showing increased productivity, measured as changes in 'greenness', have coincided with a general rise in high-latitude air temperatures and have been partly attributed to increases in shrub cover. Studies indicate that warming temperatures, changes in snow cover, altered disturbance regimes as a result of permafrost thaw, tundra fires, and anthropogenic activities or changes in herbivory intensity are all contributing to observed changes in shrub abundance. A large-scale increase in shrub cover will change the structure of tundra ecosystems and alter energy fluxes, regional climate, soil–atmosphere exchange of water, carbon and nutrients, and ecological interactions between species. In order to project future rates of shrub expansion and understand the feedbacks to ecosystem and climate processes, future research should investigate the species or trait-specific responses of shrubs to climate change including: (1) the temperature sensitivity of shrub growth, (2) factors controlling the recruitment of new individuals, and (3) the relative influence of the positive and negative feedbacks involved in shrub expansion.

Purpose Nowadays, several higher education institutions around the world are integrating sustainability topics into their daily operations, functionality and education systems. This paper presents a case study from a pilot project implemented by the Ernst-Moritz-Arndt-Universität Greifswald (hereafter, Greifswald University), Germany on its way towards a “carbon-neutral university”. The purpose of this paper is to share an institutional process targeting a gradual transformation towards achieving carbon neutrality. This might be relevant to other higher education institutions striving for a systematic and progressive change from a traditional system to a low emission or carbon-neutral pathway. Design/methodology/approach To achieve carbon neutrality, three major transformative strategies were adopted: carbon reduction, carbon offsetting and mainstreaming sustainable actions via teaching and research. Findings A locally adaptable institutional framework on sustainability was successfully developed to: promote changes in daily operations, implement interdisciplinary research, incorporate sustainability into teaching and education and enhance outreach programs. Strong commitment from all stakeholders resulted in reduction of the university’s carbon footprint from 8,985 to 4,167 tCO2e year−1. Further, the unavoidable emissions could be locally offset through enhanced carbon sequestration on the university-owned forests. Originality/value Based on the experiences of Greifswald University, this paper presents major challenges and success lessons learned during the process of gradual institutional transformation to achieve the target of carbon neutrality.

This paper introduces a new approach-the Principal Component Gradient Analysis (PCGA)-to detect ecological gradients in time-series populations, i.e. several time-series originating from different individuals of a population. Detection of ecological gradients is of particular importance when dealing with time-series from heterogeneous populations which express differing trends. PCGA makes use of polar coordinates of loadings from the first two axes obtained by principal component analysis (PCA) to define groups of similar trends. Based on the mean inter-series correlation (rbar) the gain of increasing a common underlying signal by PCGA groups is quantified using Monte Carlo Simulations. In terms of validation PCGA is compared to three other existing approaches. Focusing on dendrochronological examples, PCGA is shown to correctly determine population gradients and in particular cases to be advantageous over other considered methods. Furthermore, PCGA groups in each example allowed for enhancing the strength of a common underlying signal and comparably well as hierarchical cluster analysis. Our results indicate that PCGA potentially allows for a better understanding of mechanisms causing time-series population gradients as well as objectively enhancing the performance of climate transfer functions in dendroclimatology. While our examples highlight the relevance of PCGA to the field of dendrochronology, we believe that also other disciplines working with data of comparable structure may benefit from PCGA.

Wood is a sustainable natural resource and an important global commodity. According to the ‘moon wood theory’, the properties of wood, including its growth and water content, are believed to oscillate with the lunar cycle. Despite contradicting our current understanding of plant functioning, this theory is commonly exploited for marketing wooden products. To examine the moon wood theory, we applied a wavelet power transformation to series of 2,000,000 hourly stem radius records from dendrometers. We separated the influence of 74 consecutive lunar cycles and meteorological conditions on the stem variation of 62 trees and six species. We show that the dynamics of stem radius consist of overlapping oscillations with periods of 1 day, 6 months, and 1 year. These oscillations in stem dimensions were tightly coupled to oscillations in the series of air temperature and vapour pressure deficit. By contrast, we revealed no imprint of the lunar cycle on the stem radius variation of any species. We call for scepticism towards the moon wood theory, at least as far as the stem water content and radial growth are concerned. We foresee that similar studies employing robust scientific approaches will be increasingly needed in the future to cope with misleading concepts.

The recent developments in artificial intelligence have the potential to facilitate new research methods in ecology. Especially Deep Convolutional Neural Networks (DCNNs) have been shown to outperform other approaches in automatic image analyses. Here we apply a DCNN to facilitate quantitative wood anatomical (QWA) analyses, where the main challenges reside in the detection of a high number of cells, in the intrinsic variability of wood anatomical features, and in the sample quality. To properly classify and interpret features within the images, DCNNs need to undergo a training stage. We performed the training with images from transversal wood anatomical sections, together with manually created optimal outputs of the target cell areas. The target species included an example for the most common wood anatomical structures: four conifer species; a diffuse-porous species, black alder ( Alnus glutinosa L.); a diffuse to semi-diffuse-porous species, European beech ( Fagus sylvatica L.); and a ring-porous species, sessile oak ( Quercus petraea Liebl.). The DCNN was created in Python with Pytorch, and relies on a Mask-RCNN architecture. The developed algorithm detects and segments cells, and provides information on the measurement accuracy. To evaluate the performance of this tool we compared our Mask-RCNN outputs with U-Net, a model architecture employed in a similar study, and with ROXAS, a program based on traditional image analysis techniques. First, we evaluated how many target cells were correctly recognized. Next, we assessed the cell measurement accuracy by evaluating the number of pixels that were correctly assigned to each target cell. Overall, the “learning process” defining artificial intelligence plays a key role in overcoming the issues that are usually manually solved in QWA analyses. Mask-RCNN is the model that better detects which are the features characterizing a target cell when these issues occur. In general, U-Net did not attain the other algorithms’ performance, while ROXAS performed best for conifers, and Mask-RCNN showed the highest accuracy in detecting target cells and segmenting lumen areas of angiosperms. Our research demonstrates that future software tools for QWA analyses would greatly benefit from using DCNNs, saving time during the analysis phase, and providing a flexible approach that allows model retraining.

Plant-associated mycobiomes in extreme habitats are understudied and poorly understood. We analysed Illumina-generated ITS1 sequences from the needle mycobiome of white spruce (Picea glauca) at the northern treeline in Alaska (USA). Sequences were obtained from the same DNA that was used for tree genotyping. In the present study, fungal metabarcoding and tree microsatellite data were compared for the first time. In general, neighbouring trees shared more fungal taxa with each other than trees growing in further distance. Mycobiomes correlated strongly with phenological host traits and local habitat characteristics contrasting a dense forest stand with an open treeline site. Genetic similarity between trees did not influence fungal composition and no significant correlation existed between needle mycobiome and tree genotype. Our results suggest the pronounced influence of local habitat conditions and phenotypic tree traits on needle-inhabiting fungi. By contrast, the tree genetic identity cannot be bench-marked as a dominant driver for needle-inhabiting mycobiomes, at least not for white spruce in this extreme environment.

Warming-induced drought has widely affected forest dynamics in most places of the northern hemisphere. In this study, we assessed how climate warming has affected Picea crassifolia (Qinghai spruce) forests using tree growth-climate relationships and the normalized difference vegetation index (NDVI) along the Qilian Mountains, northeastern Tibet Plateau (the main range of Picea crassifolia). Based on the analysis on trees radial growth data from the upper tree line and the regional NDVI data, we identified a pervasive growth decline in recent decades, most likely caused by warming-induced droughts. The drought stress on Picea crassifolia radial growth were expanding from northeast to southwest and the favorable moisture conditions for tree growth were retreating along the identical direction in the study area over the last half century. Compared to the historical drought stress on tree radial growth in the 1920s, recent warming-induced droughts display a longer-lasting stress with a broader spatial distribution on regional forest growth. If the recent warming continues without the effective moisture increasing, then a notable challenge is developed for Picea crassifolia in the Qilian Mountains. Elaborate forest management is necessary to counteract the future risk of climate change effects in this region.

Human-driven peatland drainage has occurred in Europe for centuries, causing habitat degradation and leading to the emission of greenhouse gases. As such, in the last decades, there has been an increase in policies aiming at restoring these habitats through rewetting. Alder ( Alnus glutinosa L.) is a widespread species in temperate forest peatlands with a seemingly high waterlogging tolerance. Yet, little is known about its specific response in growth and wood traits relevant for tree functioning when dealing with changing water table levels. In this study, we investigated the effects of rewetting and extreme flooding on alder growth and wood traits in a peatland forest in northern Germany. We took increment cores from several trees at a drained and a rewetted stand and analyzed changes in ring width, wood density, and xylem anatomical traits related to the hydraulic functioning, growth, and mechanical support for the period 1994–2018. This period included both the rewetting action and an extreme flooding event. We additionally used climate-growth and climate-density correlations to identify the stand-specific responses to climatic conditions. Our results showed that alder growth declined after an extreme flooding in the rewetted stand, whereas the opposite occurred in the drained stand. These changes were accompanied by changes in wood traits related to growth (i.e., number of vessels), but not in wood density and hydraulic-related traits. We found poor climate-growth and climate-density correlations, indicating that water table fluctuations have a stronger effect than climate on alder growth. Our results show detrimental effects on the growth of sudden water table changes leading to permanent waterlogging, but little implications for its wood density and hydraulic architecture. Rewetting actions should thus account for the loss of carbon allocation into wood and ensure suitable conditions for alder growth in temperate peatland forests.