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Publications

NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.

2024

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Abstract

Decision Support Indicators (DSIs) are metrics designed to inform local and regional stakeholders about the characteristics of a predicted (or ongoing) event to facilitate decision-making. In this paper, the DSI concept was developed to clarify the different aims of different kinds of indicators by naming them, and a framework was developed to describe and support the usage of such DSIs. The framework includes three kinds of DSI: hydroclimatic DSIs which are easy to calculate but hard to understand by non-experts; impact-based DSIs which are often difficult to calculate but easy to understand by non-experts; and event-based DSIs, which compare a current or projected state to a locally well-known historical event, where hydroclimatic and impact-based DSIs are currently mainly used. Tables and figures were developed to support the DSI development in collaboration with stakeholders. To develop and test the framework, seven case studies, representing different hydrological pressures on three continents (South America, Asia, and Europe), were carried out. The case studies span several temporal and spatial scales (hours-decades; 70–6,000 km2) as well as hydrological pressures (pluvial and riverine floods, drought, and water scarcity), representing different climate zones. Based on stakeholder workshops, DSIs were developed for these cases, which are used as examples of the conceptual framework. The adaptability of the DSI framework to this wide range of cases shows that the framework and related concepts are useful in many contexts.

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The decision support indicators (DSIs) are specifically designed to inform local and regional stakeholders on the characteristics of a predicted event to facilitate decision-making. They can be classified as conventional, impact-based and event-based DSIs. This study aims to develop methodologies for calculating event-based DSIs and to evaluate the usefulness of different classes of DSIs for climate impact assessment and climate actions by learning about users' perceptions. The DSIs are calculated based on an ensemble of hydrological projections in western Norway under two representative concentration pathway (RCP) scenarios. The definitions, methodologies and results of the indicators are summarized in questionnaires and evaluated by key stakeholders in terms of understandability, importance, plausibility and applicability. Based on the feedback, we conclude that the conventional DSIs are still preferred by stakeholders and an appropriate selection of conventional DSIs may overcome the understanding problems between the scientists and stakeholders. The DSIs based on well-known historical events are easy to understand and can be a useful tool to convey climate information to the public. However, they are not readily implemented by stakeholders in the decision-making process. The impact-based DSI is generally easy to understand and important but it can be restricted to specific impact sectors.

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Aim Ecological and anthropogenic factors shift the abundances of dominant and rare tree species within local forest communities, thus affecting species composition and ecosystem functioning. To inform forest and conservation management it is important to understand the drivers of dominance and rarity in local tree communities. We answer the following research questions: (1) What are the patterns of dominance and rarity in tree communities? (2) Which ecological and anthropogenic factors predict these patterns? And (3) what is the extinction risk of locally dominant and rare tree species? Location Global. Time period 1990–2017. Major taxa studied Trees. Methods We used 1.2 million forest plots and quantified local tree dominance as the relative plot basal area of the single most dominant species and local rarity as the percentage of species that contribute together to the least 10% of plot basal area. We mapped global community dominance and rarity using machine learning models and evaluated the ecological and anthropogenic predictors with linear models. Extinction risk, for example threatened status, of geographically widespread dominant and rare species was evaluated. Results Community dominance and rarity show contrasting latitudinal trends, with boreal forests having high levels of dominance and tropical forests having high levels of rarity. Increasing annual precipitation reduces community dominance, probably because precipitation is related to an increase in tree density and richness. Additionally, stand age is positively related to community dominance, due to stem diameter increase of the most dominant species. Surprisingly, we find that locally dominant and rare species, which are geographically widespread in our data, have an equally high rate of elevated extinction due to declining populations through large-scale land degradation. Main conclusions By linking patterns and predictors of community dominance and rarity to extinction risk, our results suggest that also widespread species should be considered in large-scale management and conservation practices.

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The emergence of alternative stable states in forest systems has significant implications for the functioning and structure of the terrestrial biosphere, yet empirical evidence remains scarce. Here, we combine global forest biodiversity observations and simulations to test for alternative stable states in the presence of evergreen and deciduous forest types. We reveal a bimodal distribution of forest leaf types across temperate regions of the Northern Hemisphere that cannot be explained by the environment alone, suggesting signatures of alternative forest states. Moreover, we empirically demonstrate the existence of positive feedbacks in tree growth, recruitment and mortality, with trees having 4–43% higher growth rates, 14–17% higher survival rates and 4–7 times higher recruitment rates when they are surrounded by trees of their own leaf type. Simulations show that the observed positive feedbacks are necessary and sufficient to generate alternative forest states, which also lead to dependency on history (hysteresis) during ecosystem transition from evergreen to deciduous forests and vice versa. We identify hotspots of bistable forest types in evergreen-deciduous ecotones, which are likely driven by soil-related positive feedbacks. These findings are integral to predicting the distribution of forest biomes, and aid to our understanding of biodiversity, carbon turnover, and terrestrial climate feedbacks.

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As the overall demand for wood-based products continues to grow, questions arise on how local wood resources and industry characteristics can effectively meet this growing demand. In the European Union (EU) 550 million m3 of wood is harvested annually, and is to a large extent processed by the wood industry. Little is known about the interplay between industrial capacity and the regional availability of timber resources. We compared the capacities from the European Forest Industry Facilities Database (EUFID) with the estimated wood supply from the procurement areas around processing industries, calculated using a spatially explicit resource model (EFISCEN-Space). We found that the estimated total capacity for the available European countries is 427 M m3 roundwood equivalent (rw. Eq.) for pulp and paper (including both virgin and recycled fibres), 102 M m3 for bioenergy (only bioenergy plants), and 153 M m3 for sawmills. We then conducted an in-depth analysis of three case studies: Norway, the Czech Republic, and Germany. Given the current probability of trees being harvested (excluding disturbances) and the hypothetical optimal grading of the logs, the volume for each assortment type is closely aligned with the current capacity of each industry branch, indicating no overcapacity. We found undersupply of softwood of 3.4 M m3 for the Czech Republic, 1.5 M m3 for Norway, and 3.8 M m3 for Germany. At the same time, in Germany, we found an oversupply of hardwood of 3.0 M m3. Additionally, a substantial amount of biomass graded as bioenergy was found for Germany and the Czech Republic, potentially serving as fuelwood in households. Concerning wood procurement areas, we concluded that a fixed radius of 100 km from the facility limited the availability of raw material procurement, particularly for bioenergy and pulp and paper mills, suggesting that these two product chains use a broader procurement basin than sawlogs. This study provides a high-resolution, spatially explicit modelling methodology for assessing the interaction between potential wood harvest and industrial processing capacity, which can support projections of sustainable development of the forest industry.

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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.

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Introduction: Plantations located outside the species distribution area represent natural experiments to assess tree tolerance to climate variability. Climate change amplifies warming-related drought stress but also leads to more climate extremes. Methods: We studied plantations of the European larch (Larix decidua), a conifer native to central and eastern Europe, in northern Spain. We used climate, drought and tree-ring data from four larch plantations including wet (Valgañón, site V; Santurde, site S), intermediate (Ribavellosa, site R) and dry (Santa Marina, site M) sites. We aimed to benchmark the larch tolerance to climate and drought stress by analysing the relationships between radial growth increment (hereafter growth), climate data (temperature, precipitation, radiation) and a drought index. Results: Basal area increment (BAI) was the lowest in the driest site M (5.2 cm2 yr-1; period 1988–2022), followed by site R (7.5 cm2 yr-1), with the youngest and oldest and trees being planted in M (35 years) and R (150 years) sites. BAI peaked in the wettest sites (V; 10.4 cm2 yr-1; S, 10.8 cm2 yr-1). We detected a sharp BAI reduction (30% of the regional mean) in 2001 when springto-summer conditions were very dry. In the wettest V and S sites, larch growth positively responded to current March and June-July radiation, but negatively to March precipitation. In the R site, high April precipitation enhanced growth. In the driest M site, warm conditions in the late prior winter and current spring improved growth, but warm-sunny conditions in July and dry-sunny conditions in August reduced it. Larch growth positively responded to spring-summer wet conditions considering short (1-6 months) and long (9-24 months) time scales in dry (site M) and wet-intermediate (sites S and R) sites, respectively. Discussion: Larch growth is vulnerable to drought stress in dry slow-growing plantations, but also to extreme spring wet-cloudy events followed by dry-hot conditions in wet fast-growing plantations.

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Forest soils harbor hyper-diverse microbial communities which fundamentally regulate carbon and nutrient cycling across the globe. Directly testing hypotheses on how microbiome diversity is linked to forest carbon storage has been difficult, due to a lack of paired data on microbiome diversity and in situ observations of forest carbon accumulation and storage. Here, we investigated the relationship between soil microbiomes and forest carbon across 238 forest inventory plots spanning 15 European countries. We show that the composition and diversity of fungal, but not bacterial, species is tightly coupled to both forest biotic conditions and a seven-fold variation in tree growth rates and biomass carbon stocks when controlling for the effects of dominant tree type, climate, and other environmental factors. This linkage is particularly strong for symbiotic endophytic and ectomycorrhizal fungi known to directly facilitate tree growth. Since tree growth rates in this system are closely and positively correlated with belowground soil carbon stocks, we conclude that fungal composition is a strong predictor of overall forest carbon storage across the European continent.