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Enough of silos: develop a joint scientific agenda to understand the intertwined global crises of the Earth system. Enough of silos: develop a joint scientific agenda to understand the intertwined global crises of the Earth system.

Tropical forests play an important role in the global carbon cycle. High-resolution remote sensing techniques, e.g., spaceborne lidar, can measure complex tropical forest structures, but it remains a challenge how to interpret such information for the assessment of forest biomass and productivity. Here, we develop an approach to estimate basal area, aboveground biomass and productivity within Amazonia by matching 770,000 GLAS lidar (ICESat) profiles with forest simulations considering spatial heterogeneous environmental and ecological conditions. This allows for deriving frequency distributions of key forest attributes for the entire Amazon. This detailed interpretation of remote sensing data improves estimates of forest attributes by 20–43% as compared to (conventional) estimates using mean canopy height. The inclusion of forest modeling has a high potential to close a missing link between remote sensing measurements and the 3D structure of forests, and may thereby improve continent-wide estimates of biomass and productivity. Improving estimates of forest biomass based on remote sensing data is important to assess global carbon cycling. Here the authors develop an approach to use forest gap models to simulate lidar waveforms and compare the outputs with ICESAT-1 GLAS profiles, showing improved estimates across the Amazon basin.

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.

Unprecedented urbanization has led to a sharp increase in the world’s building stock, increasing material consumption and environmental impact. This study introduces CarbonFiberStone (CFS), a novel lightweight construction material, and assesses its carbon footprint in a specific building application. CFS is defined as a millimeter-thin bio-based carbon fiber fabric bonded to compression-resistant stone slabs using an adhesive. CFS is extremely resistant to compression and tension. The resulting stone powder from the stone cutting process is used for enhanced rock weathering. The wall element presented here incorporates a layer of biochar for insulation purposes. Using life cycle assessment and techno-economic analysis, we compare five CFS-based building blocks with two conventional reinforced concrete blocks in single and multi-story residential buildings. The results show that CFS walls achieve a net carbon negative balance of −56.86–65.32 kg CO2eq m−2, sequestering 0.10–0.15 t CO2 per square meter of living space at similar costs to conventional construction with reinforced concrete. These results show that CFS has the potential to become a viable, sustainable alternative to conventional building materials and thus has the potential to make a significant contribution to the 1.5 °C target of the Paris Agreement.

To understand forest dynamics under today’s changing environmental conditions, it is important to analyze the state of forests at large scales. Forest inventories are not available for all regions, so it is important to use other additional methods, e.g., remote sensing observations. Increasingly, remotely sensed data based on optical instruments and airborne LIDAR are becoming widely available for forests. There is great potential in analyzing these measurements and gaining an understanding of forest states. In this work, we combine the new-generation radiative transfer model mScope with the individual-based forest model FORMIND to generate reflectance spectra for forests. Combining the two models allows us to account for species diversity at different height layers in the forest. We compare the generated reflectances for forest stands in Finland, in the region of North Karelia, with Sentinel-2 measurements. We investigate which level of forest representation gives the best results and explore the influence of different calculation methods of mean leaf parameters. For the majority of the forest stands, we generated good reflectances with all levels of forest representation compared to the measured reflectance. Good correlations were also found for the vegetation indices (especially NDVI with R2=0.62). This work provides a forward modeling approach for relating forest reflectance to forest characteristics. With this tool, it is possible to analyze a large set of forest stands with corresponding reflectances. This opens up the possibility to understand how reflectance is related to succession and different forest conditions.

Accurate accounting of aboveground biomass density (AGBD) is crucial for carbon cycle, biodiversity, and climate change science. The Global Ecosystem Dynamics Investigation (GEDI), which maps global AGBD from waveform lidar, is the first of a new generation of Earth observation missions designed to improve carbon accounting. This paper explores the possibility that lidar waveforms may not be unique to AGBD—that forest stands with different AGBD may produce highly similar waveforms—and we hypothesize that non-uniqueness may contribute to the large uncertainties in AGBD predictions. Our analysis integrates simulated GEDI waveforms from 428 in situ stem maps with output from an individual-based forest gap model, which we use to generate a database of potential forest stands and simulate GEDI waveforms from those stands. We use this database to predict the AGBD of the 428 in situ stem maps via two different methods: a linear regression from waveform metrics, and a waveform-matching approach that accounts for waveform-AGBD non-uniqueness. We find that some in situ waveforms are more unique to AGBD than others, which notably impacts AGBD prediction uncertainty (7–411 Mg ha−1, average of 167 Mg ha−1). We also find that forest structure complexity may influence the non-uniqueness effect; stands with low structural complexity are more unique to AGBD than more mature stands with multiple cohorts and canopy layers. These findings suggest that the non-uniqueness phenomena may be introduced by the measuring characteristics of waveform lidar in combination with how forest structure manifests at small scales, and we discuss how this complexity may complicate uncertainty estimation in AGBD prediction. This analysis suggests a limit to the accuracy and precision of AGBD predictions from lidar waveforms seen in empirical studies, and underscores the need for further exploration of the relationships between lidar remote sensing measurements, forest structure, and AGBD.

Plant functional diversity (FD) is an important component of biodiversity. Evidence shows that FD strongly determines ecosystem functioning and stability and also regulates various ecosystem services that underpin human well-being. Given the importance of FD, it is critical to monitor its variations in an explicit manner across space and time, a highly demanding task that cannot be resolved solely by field data. Today, high hopes are placed on satellite-based observations to complement field plot data. The promise is that multiscale monitoring of plant FD, ecosystem functioning, and their services is now possible at global scales in near real-time. However, non-trivial scale challenges remain to be overcome before plant ecology can capitalize on the latest advances in Earth Observation (EO). Here, we articulate the existing scale challenges in linking field and satellite data and further elaborated in detail how to address these challenges via the latest innovations in optical and radar sensor technologies and image analysis algorithms. Addressing these challenges not only requires novel remote sensing theories and algorithms but also urges more effective communication between remote sensing scientists and field ecologists to foster mutual understanding of the existing challenges. Only through a collaborative approach can we achieve the global plant functional diversity monitoring goal.

Rising temperatures due to climate change influence the wood production of forests. Observations show that some temperate forests increase their productivity, whereas others reduce their productivity. This study focuses on how species composition and forest structure properties influence the temperature sensitivity of aboveground wood production (AWP). It further investigates which forests will increase their productivity the most with rising temperatures. We described forest structure by leaf area index, forest height and tree height heterogeneity. Species composition was described by a functional diversity index (Rao's Q) and a species distribution index (ΩAWP). ΩAWP quantified how well species are distributed over the different forest layers with regard to AWP. We analysed 370 170 forest stands generated with a forest gap model. These forest stands covered a wide range of possible forest types. For each stand, we estimated annual aboveground wood production and performed a climate sensitivity analysis based on 320 different climate time series (of 1-year length). The scenarios differed in mean annual temperature and annual temperature amplitude. Temperature sensitivity of wood production was quantified as the relative change in productivity resulting from a 1 ∘C rise in mean annual temperature or annual temperature amplitude. Increasing ΩAWP positively influenced both temperature sensitivity indices of forest, whereas forest height showed a bell-shaped relationship with both indices. Further, we found forests in each successional stage that are positively affected by temperature rise. For such forests, large ΩAWP values were important. In the case of young forests, low functional diversity and small tree height heterogeneity were associated with a positive effect of temperature on wood production. During later successional stages, higher species diversity and larger tree height heterogeneity were an advantage. To achieve such a development, one could plant below the closed canopy of even-aged, pioneer trees a climax-species-rich understorey that will build the canopy of the mature forest. This study highlights that forest structure and species composition are both relevant for understanding the temperature sensitivity of wood production.

This review of recent advances in biosphere research aims to provide information on eight selected themes related to changes in biodiversity, ecosystem functioning, social and economic interactions with ecosystems, and the impacts of climate change on the biosphere. An interdisciplinary panel of experts selected these eight themes from a public survey based on relevance and scientific evidence that have the potential to guide future actions as well as inspire future research questions. Our focus is on the interactions between climate, biosphere, and society and on strategies to sustain, restore, or promote ecosystems and their services. The themes focus on innovative opportunities for coastal habitats, forest linkages to droughts, and increasing fire risks. We further discuss nature-based carbon dioxide removal (CDR) implementation risks and the share of (semi-)natural habitats in the landscape. Finally, we highlight the importance of comprehensive international policy packages and the social–economic value of ecosystems in the future and present the idea of convivial conservation. Based on an analysis of these eight topics, we have synthesized four overarching insights: (i) improve mechanisms of inclusive decision-making, (ii) establish and strengthen incentives for sustainable practices, (iii) measure and share regional features, and finally (iv) adopt long-lasting holistic landscape management strategies. This review emphasizes that the interlinked challenges for ecosystems, including the socio-economic dimensions, require interdisciplinary and integrative approaches to develop effective and sustainable solutions.

Soil is central to the complex interplay among biodiversity, climate, and society. This paper examines the interconnectedness of soil biodiversity, climate change, and societal impacts, emphasizing the urgent need for integrated solutions. Human‐induced biodiversity loss and climate change intensify environmental degradation, threatening human well‐being. Soils, rich in biodiversity and vital for ecosystem function regulation, are highly vulnerable to these pressures, affecting nutrient cycling, soil fertility, and resilience. Soil also crucially regulates climate, influencing energy, water cycles, and carbon storage. Yet, climate change poses significant challenges to soil health and carbon dynamics, amplifying global warming. Integrated approaches are essential, including sustainable land management, policy interventions, technological innovations, and societal engagement. Practices like agroforestry and organic farming improve soil health and mitigate climate impacts. Effective policies and governance are crucial for promoting sustainable practices and soil conservation. Recent technologies aid in monitoring soil biodiversity and implementing sustainable land management. Societal engagement, through education and collective action, is vital for environmental stewardship. By prioritizing interdisciplinary research and addressing key frontiers, scientists can advance understanding of the soil biodiversity–climate change–society nexus, informing strategies for environmental sustainability and social equity. Soil is central to the complex interplay among biodiversity, climate, and society. This paper examines the interconnectedness of soil biodiversity, climate change, and societal impacts, emphasizing the urgent need for integrated solutions.