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Forests, critical components of global ecosystems, face unprecedented challenges due to climate change. This study investigates the influence of functional diversity—as a component of biodiversity—to enhance long-term biomass of European forests in the context of changing climatic conditions. Using the next-generation flexible trait-based vegetation model, LPJmL-FIT, we explored the impact of functional diversity on long-term forest biomass under three different climate change scenarios (video abstract: https://www.pik-potsdam.de/~billing/video/2023/video_abstract_billing_et_al_LPJmLFIT.mp4). Four model set-ups were tested with varying degrees of functional diversity and best-suited functional traits. Our results show that functional diversity positively influences long-term forest biomass, particularly when climate warming is low (RCP2.6). Under these conditions, high-diversity simulations led to an approximately 18.2% increase in biomass compared to low-diversity experiments. However, as climate change intensity increased, the benefits of functional diversity diminished (RCP8.5). A Bayesian multilevel analysis revealed that both full leaf trait diversity and diversity of plant functional types contributed significantly to biomass enhancement under low warming scenarios in our model simulations. Under strong climate change, the presence of a mixture of different functional groups (e.g. summergreen and evergreen broad-leaved trees) was found more beneficial than the diversity of leaf traits within a functional group (e.g. broad-leaved summergreen trees). Ultimately, this research challenges the notion that planting only the most productive and climate-suited trees guarantees the highest future biomass and carbon sequestration. We underscore the importance of high functional diversity and the potential benefits of fostering a mixture of tree functional types to enhance long-term forest biomass in the face of climate change.

"There are no scientifically justified obstacles to protecting biodiversity in all its beauty and diversity. There are only six years left to achieve the biodiversity targets by 2030. We must work together now to get there in time."In the 10 Must Knows from Biodiversity Science 2024, 64 scientists have further developed their well-founded and diverse findings and recommendations from the 10MustKnows22. The content of the ten selected key areas of the Earth-human system is supplemented by relevant publications from 2022 and 2023 and linked to the 23 global goals of the Kunming-Montreal Global Biodiversity Framework (GBF) adopted in December 2022. The authors are aware that the next six years until 2030 are essential for achieving an ecologically sustainable and socially just life on our planet in the medium and long term. With the 10MustKnows24, they want to actively contribute to accelerating the socio-ecological transformation by providing scientifically sound recommendations for politics and society.These are the 10MustKnows24: 1: Achieving climate and biodiversity protection together 2: Enabling a healthy life on a healthy planet 3: Considering undiscovered biodiversity 4: Linking linguistic, cultural and biological diversity 5: Harmonising the diverse use of forest ecosystems and biodiversity conservation 6: Transforming agricultural and food systems 7: Protecting land and resources 8: Releasing transformative change through international collaboration and Education for Sustainable Development 9: Ensuring free access and open use of biodiversity-related data 10: Reducing biodiversity impacts from food consumption

"Es gibt wissenschaftlich keine begründeten Hindernisse, die Biodiversität in ihrer Schönheit und Vielfalt zu schützen. Es bleiben nur noch sechs Jahre, um die Biodiversitätsziele bis 2030 zu erreichen. Dafür müssen wir jetzt gemeinsam anpacken."In den 10 Must-Knows aus der Biodiversitätsforschung 2024 haben 64 Wissenschaftlerinnen und Wissenschaftler ihre fundierten und vielseitigen Erkenntnisse und Empfehlungen aus den 10MustKnows22 weiterentwickelt. Die zehn ausgewählten Schlüsselbereiche des Erde-Mensch-Systems werden inhaltlich durch relevante Publikationen von 2022 und 2023 ergänzt und mit den im Dezember 2022 verabschiedeten 23 globalen Zielen des Kunming-Montreal Global Biodiversity Framework (GBF) verknüpft. Den Autorinnen und Autoren ist bewusst, dass die kommenden sechs Jahre bis 2030 wesentlich sind, um mittel- und langfristig ein ökologisch nachhaltiges und sozial gerechtes Leben auf unserer Erde zu erreichen. Mit den 10MustKnows24 möchten sie durch wissenschaftlich gesicherte Empfehlungen für Politik und Gesellschaft ihren aktiven Beitrag leisten, um die sozial-ökologische Transformation zu beschleunigen.Das sind die 10MustKnows24: 1. Klima- und Biodiversitätsschutz gemeinsam verwirklichen 2. Ein gesundes Leben auf einem gesunden Planeten ermöglichen 3. Unentdeckte Biodiversität beachten 4. Sprachliche, kulturelle und biologische Vielfalt verknüpfen 5. Vielfältige Nutzung von Waldökosystemen und Biodiversitätsschutz in Einklang bringen 6. Agrar- und Ernährungssysteme transformieren 7. Land und Ressourcen schützen 8. Transformativen Wandel durch internationale Zusammenarbeit und Bildung für nachhaltige Entwicklung bewirken 9. Freien Zugang und offene Nutzung von biodiversitätsbezogenen Daten sicherstellen 10. Auswirkungen des Lebensmittelkonsums auf die Biodiversität verringern

Uncertainty in how the land carbon (C) sink will change over time contributes to uncertainty in Earth system model (ESM) projections of climate change. Much of the land sink is thought to reside in old-growth tropical forests, but recent analyses suggest a diminishing C sink in these forests due to rising temperatures and drought. Thus, there is an urgent need to better understand tropical forest responses to drought and to incorporate this understanding into ESMs. Previous work with vegetation demographic models (VDMs) – which represent the dynamics of individuals or cohorts, along with hydrology and biogeochemistry − suggest that functional diversity can enhance tropical forest resilience to climate change. However, there is little understanding of how different approaches to representing trait diversity and demography affect model outcomes. To explore the potential for trait diversity to moderate tropical forest responses to drought, we explored the behavior of nine VDMs, ranging from models with detailed site-level parameterizations to more generalized land models designed as ESM components. The behavior of each model was studied using soil and meteorological data collected at each of two tropical forest sites: Paracou Research Station, French Guiana, and Tapajos National Forest, Brazil. Low and high trait-diversity scenarios were simulated for each model using historical meteorology, as well as reduced rainfall scenarios. Few models showed strong effects of trait diversity on drought resistance (short-term response of forest biomass to rainfall reduction), but most models showed positive effects of diversity on resilience (long-term recovery of forest biomass following the initial biomass loss due to rainfall reduction). Long-term recovery was always associated with shifts in community composition towards greater drought-tolerance. However, there were large differences among models in the degree and time-scale of recovery. These differences were unrelated to th

In the 10 Must Knows from Biodiversity Science 45 scientists present facts about biodiversity in a well-founded and generally intelligible way. They analyse the complex systems of the earth by highlighting ten key areas, each of which, in turn, is inextricably linked to all the others. And they show ways to stop the continued loss of species diversity and ecosystems, and to promote biodiversity. The underlying aim is to provide policy-makers and society with scientifically validated assessments of the latest knowledge to facilitate improved policy decisions and action at local, regional, national and global levels, in order to conserve the diversity of life – biodiversity. These are the 10MustKnows 2022: 1. Achieving climate and biodiversity protection together 2. Strengthening planetary health 3. Considering hidden biodiversity 4. Promoting biocultural habitats 5. Using forests sustainably 6. Transforming agriculture 7. Protecting land and resources 8. Expanding transnational infrastructure and education for sustainability 9. Ensuring access and open use of research data 10. Setting biodiversity-friendly incentives

In the 10 Must Knows from Biodiversity Science 45 scientists present facts about biodiversity in a well-founded and generally intelligible way. They analyse the complex systems of the earth by highlighting ten key areas, each of which, in turn, is inextricably linked to all the others. And they show ways to stop the continued loss of species diversity and ecosystems, and to promote biodiversity. The underlying aim is to provide policy-makers and society with scientifically validated assessments of the latest knowledge to facilitate improved policy decisions and action at local, regional, national and global levels, in order to conserve the diversity of life – biodiversity. These are the 10MustKnows 2022: 1. Achieving climate and biodiversity protection together 2. Strengthening planetary health 3. Considering hidden biodiversity 4. Promoting biocultural habitats 5. Using forests sustainably 6. Transforming agriculture 7. Protecting land and resources 8. Expanding transnational infrastructure and education for sustainability 9. Ensuring access and open use of research data 10. Setting biodiversity-friendly incentives

Non-technical summary We summarize some of the past year's most important findings within climate change-related research. New research has improved our understanding about the remaining options to achieve the Paris Agreement goals, through overcoming political barriers to carbon pricing, taking into account non-CO2 factors, a well-designed implementation of demand-side and nature-based solutions, resilience building of ecosystems and the recognition that climate change mitigation costs can be justified by benefits to the health of humans and nature alone. We consider new insights about what to expect if we fail to include a new dimension of fire extremes and the prospect of cascading climate tipping elements. Technical summary A synthesis is made of 10 topics within climate research, where there have been significant advances since January 2020. The insights are based on input from an international open call with broad disciplinary scope. Findings include: (1) the options to still keep global warming below 1.5 °C; (2) the impact of non-CO2 factors in global warming; (3) a new dimension of fire extremes forced by climate change; (4) the increasing pressure on interconnected climate tipping elements; (5) the dimensions of climate justice; (6) political challenges impeding the effectiveness of carbon pricing; (7) demand-side solutions as vehicles of climate mitigation; (8) the potentials and caveats of nature-based solutions; (9) how building resilience of marine ecosystems is possible; and (10) that the costs of climate change mitigation policies can be more than justified by the benefits to the health of humans and nature. Social media summary How do we limit global warming to 1.5 °C and why is it crucial? See highlights of latest climate science.

Understanding the processes that shape forest functioning, structure, and diversity remains challenging, although data on forest systems are being collected at a rapid pace and across scales. Forest models have a long history in bridging data with ecological knowledge and can simulate forest dynamics over spatio‐temporal scales unreachable by most empirical investigations.We describe the development that different forest modelling communities have followed to underpin the leverage that simulation models offer for advancing our understanding of forest ecosystems.Using three widely applied but contrasting approaches – species distribution models, individual‐based forest models, and dynamic global vegetation models – as examples, we show how scientific and technical advances have led models to transgress their initial objectives and limitations. We provide an overview of recent model applications on current important ecological topics and pinpoint ten key questions that could, and should, be tackled with forest models in the next decade.Synthesis. This overview shows that forest models, due to their complementarity and mutual enrichment, represent an invaluable toolkit to address a wide range of fundamental and applied ecological questions, hence fostering a deeper understanding of forest dynamics in the context of global change.

Global Water Models (GWMs), which include Global Hydrological, Land Surface, and Dynamic Global Vegetation Models, present valuable tools for quantifying climate change impacts on hydrological processes in the data scarce high latitudes. Here we performed a systematic model performance evaluation in six major Pan-Arctic watersheds for different hydrological indicators (monthly and seasonal discharge, extremes, trends (or lack of), and snow water equivalent (SWE)) via a novel Aggregated Performance Index (API) that is based on commonly used statistical evaluation metrics. The machine learning Boruta feature selection algorithm was used to evaluate the explanatory power of the API attributes. Our results show that the majority of the nine GWMs included in the study exhibit considerable difficulties in realistically representing Pan-Arctic hydrological processes. Average APIdischarge (monthly and seasonal discharge) over nine GWMs is > 50% only in the Kolyma basin (55%), as low as 30% in the Yukon basin and averaged over all watersheds APIdischarge is 43%. WATERGAP2 and MATSIRO present the highest (APIdischarge > 55%) while ORCHIDEE and JULES-W1 the lowest (APIdischarge ≤ 25%) performing GWMs over all watersheds. For the high and low flows, average APIextreme is 35% and 26%, respectively, and over six GWMs APISWE is 57%. The Boruta algorithm suggests that using different observation-based climate data sets does not influence the total score of the APIs in all watersheds. Ultimately, only satisfactory to good performing GWMs that effectively represent cold-region hydrological processes (including snow-related processes, permafrost) should be included in multi-model climate change impact assessments in Pan-Arctic watersheds.

Ecosystems respond in various ways to disturbances. Quantifying ecological stability therefore requires inspecting multiple stability properties, such as resistance, recovery, persistence and invariability. Correlations among these properties can reduce the dimensionality of stability, simplifying the study of environmental effects on ecosystems. A key question is how the kind of disturbance affects these correlations. We here investigated the effect of three disturbance types (random, species‐specific, local) applied at four intensity levels, on the dimensionality of stability at the population and community level. We used previously parameterized models that represent five natural communities, varying in species richness and the number of trophic levels. We found that disturbance type but not intensity affected the dimensionality of stability and only at the population level. The dimensionality of stability also varied greatly among species and communities. Therefore, studying stability cannot be simplified to using a single metric and multi‐dimensional assessments are still to be recommended.

LEGATO stands for “Land-use intensity and Ecological EnGineering—Assessment Tools for risks and Opportunities in irrigated rice based production systems.”

© 2017, The Author(s). In a cross-disciplinary project (LEGATO) combining inter- and transdisciplinary methods, we quantify the dependency of rice-dominated socio-ecological systems on ecosystem functions (ESF) and the ecosystem services (ESS) the integrated system provides. In the collaboration of a large team including geo- and bioscientists, economists, political and cultural scientists, the mutual influences of the biological, climate and soil conditions of the agricultural area and its surrounding natural landscape have been analysed. One focus was on sociocultural and economic backgrounds, another on local as well as regional land use intensity and biodiversity, and the potential impacts of future climate and land use change. LEGATO analysed characteristic elements of three service strands defined by the Millennium Ecosystem Assessment (MA): (a) provisioning services: nutrient cycling and crop production; (b) regulating services: biocontrol and pollination; and (c) cultural services: cultural identity and aesthetics. However, in line with much of the current ESS literature, what the MA called supporting services is treated as ESF within LEGATO. As a core output, LEGATO developed generally applicable principles of ecological engineering (EE), suitable for application in the context of future climate and land use change. EE is an emerging discipline, concerned with the design, monitoring and construction of ecosystems and aims at developing strategies to optimise ecosystem services through exploiting natural regulation mechanisms instead of suppressing them. Along these lines LEGATO also aims to create the knowledge base for decision-making for sustainable land management and livelihoods, including the provision of the corresponding governance and management strategies, technologies and system solutions.

Comparing model output and observed data is an important step for assessing model performance and quality of simulation results. However, such comparisons are often hampered by differences in spatial scales between local point observations and large-scale simulations of grid cells or pixels. In this study, we propose a generic approach for a pixel-to-point comparison and provide statistical measures accounting for the uncertainty resulting from landscape variability and measurement errors in ecosystem variables. The basic concept of our approach is to determine the statistical properties of small-scale (within-pixel) variability and observational errors, and to use this information to correct for their effect when large-scale area averages (pixel) are compared to small-scale point estimates. We demonstrate our approach by comparing simulated values of aboveground biomass, woody productivity (woody net primary productivity, NPP) and residence time of woody biomass from four dynamic global vegetation models (DGVMs) with measured inventory data from permanent plots in the Amazon rainforest, a region with the typical problem of low data availability, potential scale mismatch and thus high model uncertainty. We find that the DGVMs under- and overestimate aboveground biomass by 25 % and up to 60 %, respectively. Our comparison metrics provide a quantitative measure for model–data agreement and show moderate to good agreement with the region-wide spatial biomass pattern detected by plot observations. However, all four DGVMs overestimate woody productivity and underestimate residence time of woody biomass even when accounting for the large uncertainty range of the observational data. This is because DGVMs do not represent the relation between productivity and residence time of woody biomass correctly. Thus, the DGVMs may simulate the correct large-scale patterns of biomass but for the wrong reasons. We conclude that more information about the underlying processes driving bi

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In a cross-disciplinary project (LEGATO) combining inter- and transdisciplinary methods, we quantify the dependency of rice-dominated socio-ecological systems on ecosystem functions (ESF) and the ecosystem services (ESS) the integrated system provides. In the collaboration of a large team including geo- and bioscientists, economists, political and cultural scientists, the mutual influences of the biological, climate and soil conditions of the agricultural area and its surrounding natural landscape have been analysed. One focus was on sociocultural and economic backgrounds, another on local as well as regional land use intensity and biodiversity, and the potential impacts of future climate and land use change. LEGATO analysed characteristic elements of three service strands defined by the Millennium Ecosystem Assessment (MA): (a) provisioning services: nutrient cycling and crop production; (b) regulating services: biocontrol and pollination; and (c) cultural services: cultural identity and aesthetics. However, in line with much of the current ESS literature, what the MA called supporting services is treated as ESF within LEGATO. As a core output, LEGATO developed generally applicable principles of ecological engineering (EE), suitable for application in the context of future climate and land use change. EE is an emerging discipline, concerned with the design, monitoring and construction of ecosystems and aims at developing strategies to optimise ecosystem services through exploiting natural regulation mechanisms instead of suppressing them. Along these lines LEGATO also aims to create the knowledge base for decision-making for sustainable land management and livelihoods, including the provision of the corresponding governance and management strategies, technologies and system solutions.

Irrigated rice croplands are among the world's most important agro-ecosystems. They provide food for more than 3.5 billion people and a range of other ecosystem services (ESS). However, the sustainability of rice agro-ecosystems is threatened by continuing climate and land-use changes. To estimate their combined effects on a bundle of ESS, we applied the vegetation and hydrology model LPJmL to seven study areas in the Philippines and Vietnam. We quantified future changes in the provision of four essential ESS (carbon storage, carbon sequestration, provision of irrigation water and rice production) under two climate scenarios (until 2100) and three site-specific land-use scenarios (until 2030), and examined the synergies and trade-offs in ESS responses to these drivers. Our results show that not all services can be provided in the same amounts in the future. In the Philippines and Vietnam the projections estimated a decrease in rice yields (by approximately 30%) and in carbon storage (by 15%) and sequestration (by 12%) towards the end of the century under the current land-use pattern. In contrast, the amount of available irrigation water was projected to increase in all scenarios by 10%–20%. However, the results also indicate that land-use change may partially offset the negative climate impacts in regions where cropland expansion is possible, although only at the expense of natural vegetation. When analysing the interactions between ESS, we found consistent synergies between rice production and carbon storage and trade-offs between carbon storage and provision of irrigation water under most scenarios. Our results show that not only the effects of climate and land-use change alone but also the interaction between ESS have to be considered to allow sustainable management of rice agro-ecosystems under global change.

Impacts of climate change require that society urgently develops ways to reduce amounts of carbon in the atmosphere. Tropical forests present an important opportunity, as they take up and store large amounts of carbon. It is often suggested that forests with high biodiversity have large stocks and high rates of carbon uptake. Evidence is, however, scattered across geographic areas and scales, and it remains unclear whether biodiversity is just a co-benefit or also a requirement for the maintenance of carbon stocks and uptake. Here, we perform a quantitative review of empirical studies that analyzed the relationships between plant biodiversity attributes and carbon stocks and carbon uptake in tropical forests. Our results show that biodiversity attributes related to species, traits or structure significantly affect carbon stocks or uptake in 64% of the evaluated relationships. Average vegetation attributes (community-mean traits and structural attributes) are more important for carbon stocks, whereas variability in vegetation attributes (i.e., taxonomic diversity) is important for both carbon stocks and uptake. Thus, different attributes of biodiversity have complementary effects on carbon stocks and uptake. These biodiversity effects tend to be more often significant in mature forests at broad spatial scales than in disturbed forests at local spatial scales. Biodiversity effects are also more often significant when confounding variables are not included in the analyses, highlighting the importance of performing a comprehensive analysis that adequately accounts for environmental drivers. In summary, biodiversity is not only a co-benefit, but also a requirement for short- and long-term maintenance of carbon stocks and enhancement of uptake. Climate change policies should therefore include the maintenance of multiple attributes of biodiversity as an essential requirement to achieve long-term climate change mitigation goals.

Understanding the processes that determine aboveground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity (woody NPP) and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size-structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influence AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates, and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP, and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs. This article is protected by copyright. All rights reserved.

Extreme weather events are likely to occur more often under climate change and the resulting effects on ecosystems could lead to a further acceleration of climate change. But not all extreme weather events lead to extreme ecosystem response. Here, we focus on hazardous ecosystem behaviour and identify coinciding weather conditions. We use a simple probabilistic risk assessment based on time series of ecosystem behaviour and climate conditions. Given the risk assessment terminology, vulnerability and risk for the previously defined hazard are estimated on the basis of observed hazardous ecosystem behaviour. We apply this approach to extreme responses of terrestrial ecosystems to drought, defining the hazard as a negative net biome productivity over a 12-month period. We show an application for two selected sites using data for 1981–2010 and then apply the method to the pan-European scale for the same period, based on numerical modelling results (LPJmL for ecosystem behaviour; ERA-Interim data for climate). Our site-specific results demonstrate the applicability of the proposed method, using the SPEI to describe the climate condition. The site in Spain provides an example of vulnerability to drought because the expected value of the SPEI is 0.4 lower for hazardous than for non-hazardous ecosystem behaviour. In northern Germany, on the contrary, the site is not vulnerable to drought because the SPEI expectation values imply wetter conditions in the hazard case than in the non-hazard case. At the pan-European scale, ecosystem vulnerability to drought is calculated in the Mediterranean and temperate region, whereas Scandinavian ecosystems are vulnerable under conditions without water shortages. These first model-based applications indicate the conceptual advantages of the proposed method by focusing on the identification of critical weather conditions for which we observe hazardous ecosystem behaviour in the analysed data set. Application of the method to empirical time