Michael Köhl

In this study, we analyse the suitability of the machine learning algorithm Random Forest in exploring dendroclimatic relationships. Linear methods are commonly used to explain climate related changes in radial growth, but inherently fail to capture thresholds and nonlinear effects contained in the data. Machine learning applications like Random Forest can potentially fill this gap. We use tree ring chronologies from three temperate coniferous tree species Picea abies , Pseudotsuga menziesii and Pinus sylvestris from northern Germany as well as a chronology from Cedrela odorata grown in a tropical forest in Suriname to compare response function correlation and Random Forest variable importance for monthly temperature and precipitation values on tree ring width. We further explore the possibilities of using Accumulated Local Effects to display nonlinear effects on tree ring increment. Our results show that Random Forest importance aligns well with response function analysis for the temperate species and mostly aligns with the results on Cedrela odorata . Accumulated Local Effect plots offer valuable insights into nonlinear climate effects and help in explaining unexpected correlations. While the Random Forest algorithm is not a complete substitute for established methods like response function analysis to analyse climate-growth relations, it is a valuable addition to the available toolset in exploring the hidden information in dendrochronological data.

Species’ traits and environmental conditions determine the abundance of tree species across the globe. The extent to which traits of dominant and rare tree species differ remains untested across a broad environmental range, limiting our understanding of how species traits and the environment shape forest functional composition. We use a global dataset of tree composition of >22,000 forest plots and 11 traits of 1663 tree species to ask how locally dominant and rare species differ in their trait values, and how these differences are driven by climatic gradients in temperature and water availability in forest biomes across the globe. We find three consistent trait differences between locally dominant and rare species across all biomes; dominant species are taller, have softer wood and higher loading on the multivariate stem strategy axis (related to narrow tracheids and thick bark). The difference between traits of dominant and rare species is more strongly driven by temperature compared to water availability, as temperature might affect a larger number of traits. Therefore, climate change driven global temperature rise may have a strong effect on trait differences between dominant and rare tree species and may lead to changes in species abundances and therefore strong community reassembly.

The density of wood is a key indicator of the carbon investment strategies of trees, impacting productivity and carbon storage. Despite its importance, the global variation in wood density and its environmental controls remain poorly understood, preventing accurate predictions of global forest carbon stocks. Here we analyse information from 1.1 million forest inventory plots alongside wood density data from 10,703 tree species to create a spatially explicit understanding of the global wood density distribution and its drivers. Our findings reveal a pronounced latitudinal gradient, with wood in tropical forests being up to 30% denser than that in boreal forests. In both angiosperms and gymnosperms, hydrothermal conditions represented by annual mean temperature and soil moisture emerged as the primary factors influencing the variation in wood density globally. This indicates similar environmental filters and evolutionary adaptations among distinct plant groups, underscoring the essential role of abiotic factors in determining wood density in forest ecosystems. Additionally, our study highlights the prominent role of disturbance, such as human modification and fire risk, in influencing wood density at more local scales. Factoring in the spatial variation of wood density notably changes the estimates of forest carbon stocks, leading to differences of up to 21% within biomes. Therefore, our research contributes to a deeper understanding of terrestrial biomass distribution and how environmental changes and disturbances impact forest ecosystems.

In this forest perspectives paper, we explore issues and concepts involved in the enhancement of regional monitoring frameworks for reporting on forest disturbances and damages. First, we consider the different meanings of “forest disturbance” and “forest damage,” terms that are often used interchangeably but have important differences in meaning and management implications. Human expectations, goals and concerns underlie both terms, especially forest damage, and they condition the data-gathering efforts and interpretations of resulting information. Accordingly, we also address the overall motivations for reporting forest disturbances and damages, the potentially impacted human expectations, and the general categories of impact and response. Next, we present some general observations on the ecological processes underlying forest disturbances and forest damages and the approaches used to measure them, noting the following challenges these processes pose for clear and consistent reporting across space and time: complexity of disturbance processes; attributing causality and distinguishing between proximate, intermediate and ultimate causes; spatial and temporal discontinuities; measurement protocol variations between countries. Both ecological processes and their related measurement techniques are particularistic, involving various and specific measurement techniques and protocols, and they do not always conform to conceptual generalizations. We conclude with a discussion on bridging the gap between concept and practical application of disturbance and damage monitoring and reporting. Despite challenges in aggregating diverse data on forest disturbances, doing so is crucial for improving scientific understanding, policy-making, and environmental management on regional and global scales.

We explored the proactive responses of local communities against locally experienced climate change impacts and anticipated threats. This study interviewed 124 rural households from three community forestry user groups representing three ecological regions of Nepal using a semi-structured questionnaire. The study used eight criteria to distinguish the proactive nature of adaptation. Both qualitative and quantitative methods were used to analyze data, including the use of a chi-square (χ²) test to determine the proactive measures and their association with livelihood options and the ordered logistic regression model to explain determining factors of choosing proactive adaptations. The results indicate that 83.9% of households adapted both proactive and reactive measures, while 10.5% applied solely reactive adaptation and 5.6% were earmarked only for proactive adaptation measures. Over 50 different proactive adaptation measures were implemented by the households. The measures were significantly associated with agricultural diversification, cash crop cultivation, livestock raising, small-scale enterprise development, and disaster control. Socio-economic and spatial factors such as a household’s wellbeing, land holding size, geographical location, livelihood options, and the number of adaptation measures implemented by households were found to be decisive factors in choosing proactive adaptation. The study concludes that local people in Nepal are not only aware of escalating climate risks but also engage their cognition and knowledge proactively to adapt locally. The results suggest that even small proactive initiatives by households can offer multiple benefits against climate risks as an architect of individuals. Therefore, adopting a trans-disciplinary approach and nurturing local proactive actions in strategic connectivity between environmental, political, and societal functions is pivotal, which primarily takes a step to drive expediently successful climate change policy and strategy implementation. The findings of this study offer valuable insights into policy and strategy planning for the unsolicited consequences of climate change and highlight the importance of understanding the perspective of local communities in adaptation planning and implementation.

It is likely that changing monsoon patterns and changes in other climatic parameters will have an impact on forests. Tree growth and biomass may respond differently across the different forest recovery contexts after the disturbance regimes. It is essential to understand the response of different tree species in order to comprehend their ability to adapt to climate change. An enhanced understanding of how tree species dynamics change with a substantial shift in climate attributes is crucial to develop adaptive forest management strategies. Advances in the statistical application of tree ring data results in more reliable dating with the high accuracy and precision of any of the paleo-records and robust and long-term reconstructions of key indices such as temperature and precipitation. In this study, we analyzed how different species inhabiting together respond to changes in climatic variables using dendroclimatic analysis. We assessed the growth performance of Abies pindrow, Pinus wallichiana, and Tsuga dumosa in the temperate region of Nepal. The climate sensitivity of the species was analyzed using bootstrap correlation analysis and the climate-growth relationship over time was assessed using the moving correlation function. Tree ring growth of Abies pindrow is stimulated by higher June temperatures and higher March precipitation. This positive relationship is consistent and stationary over time. However, in the other two species, both response function and moving correlation analysis showed that the relationship between climate and growth is inconsistent and changes over time.

Zusammenfassung: In der Vergangenheit haben sich Wälder an die geringen Veränderungen des am Wuchsort herrschenden Klimas angepasst. Die gegenwärtige Geschwindigkeit des Klimawandels in Verbindung mit der aktuellen Verteilung der Baumarten überfordert jedoch die natürliche Anpassungsfähigkeit. Vegetationszonen, Verbreitungsgebiete der Baumarten und Artzusammensetzung der Wälder verschieben sich. Das Kapitel charakterisiert die Folgen, die der Klimawandel für die Wälder mit sich bringt, stellt Schadfaktoren im Einzelnen vor und schildert die Auswirkungen auf die Produktivität. Darüber hinaus wird detailliert auf die Rolle des Waldes als Kohlenstoffspeicher eingegangen, denn Wälder produzieren nicht nur den nachwachsenden Rohstoff Holz, sondern sie leisten auch viel für die Umwelt und wirken ausgleichend auf das Klima. Auch mögliche Anpassungsoptionen werden dargestellt.