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The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.Measurement(s)net ecosystem exchange • carbon dioxide • water • energyTechnology Type(s)eddy covariance • measurement deviceSample Characteristic - Environmentterrestrial biome • atmosphereSample Characteristic - LocationEarth (planet)Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12295910

Year-round observations of the physical snow and ice properties and processes that govern the ice pack evolution and its interaction with the atmosphere and the ocean were conducted during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern in the Arctic Ocean from October 2019 to September 2020. This work was embedded into the interdisciplinary design of the five MOSAiC teams, studying the atmosphere, the sea ice, the ocean, the ecosystem and biogeochemical processes. The overall aim of the snow and sea ice observations during MOSAiC was to characterize the physical properties of the snow and ice cover comprehensively in the central Arctic over an entire annual cycle. This objective was achieved by detailed observations of physical properties, and of energy and mass balance of snow and ice. By studying snow and sea ice dynamics over nested spatial scales from centimeters to tens of kilometers, the variability across scales can be considered. On-ice observations of in-situ and remote sensing properties of the different surface types over all seasons will help to improve numerical process and climate models, and to establish and validate novel satellite remote sensing methods; the linkages to accompanying airborne measurements, satellite observations, and results of numerical models are discussed. We found large spatial variabilities of snow metamorphism and thermal regimes impacting sea ice growth. We conclude that the highly variable snow cover needs to be considered in more detail (in observations, remote sensing and models) to better understand snow-related feedback processes. The ice pack revealed rapid transformations and motions along the drift in all seasons. The number of coupled ice-ocean interface processes observed in detail are expected to guide upcoming research with respect to the changing Arctic sea ice.

As the Arctic warms, vegetation is responding, and satellite measures indicate widespread greening at high latitudes. This ‘greening of the Arctic’ is among the world’s most important large-scale ecological responses to global climate change. However, a consensus is emerging that the underlying causes and future dynamics of so-called Arctic greening and browning trends are more complex, variable and inherently scale-dependent than previously thought. Here we summarize the complexities of observing and interpreting high-latitude greening to identify priorities for future research. Incorporating satellite and proximal remote sensing with in-situ data, while accounting for uncertainties and scale issues, will advance the study of past, present and future Arctic vegetation change.As tundra ecosystems respond to rapid Arctic warming, satellite records suggest a widespread greening. This Perspective highlights the challenges of interpreting complex Arctic greening trends and provides direction for future research by combining ecological and remote sensing approaches.

Torrential rainfall predisposes hills to catastrophic landslides resulting in serious damage to life and property. Landslide inventory maps are therefore essential for rapid response and developing disaster mitigation strategies. Manual mapping techniques are laborious and time-consuming, and thus not ideal in rapid response situations. Automated landslide mapping from optical satellite imagery using deep neural networks (DNNs) is becoming popular. However, distinguishing landslides from other changed objects in optical imagery using backbone DNNs alone is difficult. Attention modules have been introduced recently into the architecture of DNNs to address this problem by improving the discriminative ability of DNNs and suppressing noisy backgrounds. This study compares two state-of-the-art attention-boosted deep Siamese neural networks in mapping rainfall-induced landslides in the mountainous Himalayan region of Nepal using Planetscope (PS) satellite imagery. Our findings confirm that attention networks improve the performance of DNNs as they can extract more discriminative features. The Siamese Nested U-Net (SNUNet) produced the best and most coherent landslide inventory map among the methods in the test area, achieving an F1-score of 0.73, which is comparable to other similar studies. Our findings demonstrate a prospect for application of the attention-based DNNs in rapid landslide mapping and disaster mitigation not only for rainfall-triggered landslides but also for earthquake-triggered landslides.

The effects of single macrofauna taxa on benthic nitrogen (N) cycling have been extensively studied, whereas how macrofaunal communities affect N-related processes remains poorly explored. In this study, we characterized benthic N-cycling in bioturbated sediments of the oligotrophic Öre Estuary (northern Baltic Sea). Solute fluxes and N transformations (N2 fixation, denitrification and dissimilative nitrate reduction to ammonium [DNRA]) were measured in sediments and macrofauna-associated microbes (holobionts) to partition the role of three dominant taxa (the filter feeder Limecola balthica, the deep deposit feeder Marenzelleria spp., and the surface deposit feeder Monoporeia affinis) in shaping N-cycling. In the studied area, benthic macrofauna comprised a low diversity community with dominance of the three taxa, which are widespread and dominant in the Baltic. The biomass of these taxa in macrofaunal community explained up to 30% of variation in measured biogeochemical processes, confirming their important role in ecosystem functioning. The results also show that these taxa significantly contributed to the benthic metabolism and N-cycling (direct effect) as well as to sediments bioturbation with positive feedback to dissimilative nitrate reduction (indirect effect). Taken together, these functions promoted a reuse of nutrients at the benthic level, limiting net losses (e.g. denitrification) and effluxes to bottom water. Finally, the detection of multiple N transformations in macrofauna holobionts suggested a community-associated versatile microbiome, however, its role was of minor importance as compared to the activity of sediment-associated microbial communities. The present study highlights hidden and interactive effects among microbes and macrofauna, which should be considered analysing benthic functioning.

The major objectives of this paper are: (1) to review the pros and cons of the scenarios of past anthropogenic land cover change (ALCC) developed during the last ten years, (2) to discuss issues related to pollen-based reconstruction of the past land-cover and introduce a new method, REVEALS (Regional Estimates of VEgetation Abundance from Large Sites), to infer long-term records of past land-cover from pollen data, (3) to present a new project (LANDCLIM: LAND cover - CLIMate interactions in NW Europe during the Holocene) currently underway, and show preliminary results of REVEALS reconstructions of the regional land-cover in the Czech Republic for five selected time windows of the Holocene, and (4) to discuss the implications and future directions in climate and vegetation/land-cover modeling, and in the assessment of the effects of human-induced changes in land-cover on the regional climate through altered feedbacks. The existing ALCC scenarios show large discrepancies between them, and few cover time periods older than AD 800. When these scenarios are used to assess the impact of human land-use on climate, contrasting results are obtained. It emphasizes the need for methods such as the REVEALS model-based land-cover reconstructions. They might help to fine-tune descriptions of past land-cover and lead to a better understanding of how long-term changes in ALCC might have influenced climate. The REVEALS model is demonstrated to provide better estimates of the regional vegetation/land-cover changes than the traditional use of pollen percentages. This will achieve a robust assessment of land cover at regional- to continental-spatial scale throughout the Holocene. We present maps of REVEALS estimates for the percentage cover of 10 plant functional types (PFTs) at 200 BP and 6000 BP, and of the two open-land PFTs \"grassland\" and \"agricultural land\" at five time-windows from 6000 BP to recent time. The LANDCLIM results are expected to provide crucial data to reassess ALCC estimates for a better understanding of the land suface-atmosphere interactions.

Fluvial floods can cause significant damages and are expected to increase in magnitude and frequency throughout the twenty-first century due to global warming. Alongside hazard characteristics, damage potentials depend on exposure and vulnerability, which are changing in the wake of socio-economic developments. In the context of continuously evolving damage-causing factors, assessments of future changes in flood damage potentials are increasingly asked for by decision-makers in flood risk management. This study addresses this need by (a) providing a systematic review of contemporary assessment approaches to quantitatively compare direct economic losses from fluvial flooding under current and future conditions and (b) combining the reviewed approaches to an applicable methodology which is used in a case study to quantify changing flood damage potentials in the Neckar River basin in southern Germany. Therefore, a scoping study of contemporary flood damage assessment approaches supported by geographic information systems (GIS) is performed. The subsequent case study of the Neckar River prognoses a significant increase in average annual flood damages in the study area throughout the twenty-first century. The case study produces valid results with regards to current precipitation data, whereas the absence of verification data makes the validation of projected scenarios more difficult. To account for uncertainties surrounding these future projections, a nascent qualitative confidence estimation is introduced to reflect on the strength of knowledge underlying the used flood damage assessment methodology.

Increasing occurrences of extreme weather events, such as the 2018 drought over northern Europe, are a concerning issue under global climate change. High-resolution archives of natural hydroclimate proxies, such as rapidly accumulating sediments containing biogenic carbonates, offer the potential to investigate the frequency and mechanisms of such events in the past. Droughts alter the barium (Ba) concentration of near-continent seawater through the reduction in Ba input from terrestrial runoff, which in turn may be recorded as changes in the chemical composition (Ba/Ca) of foraminiferal calcium carbonates accumulating in sediments. However, so far the use of Ba/Ca as a discharge indicator has been restricted to planktonic foraminifera, despite the high relative abundance of benthic species in coastal, shallow-water sites. Moreover, benthic foraminiferal Ba/Ca has mainly been used in open-ocean records as a proxy for paleo-productivity. Here we report on a new geochemical data set measured from living (CTG-labeled) benthic foraminiferal species to investigate the capability of benthic Ba/Ca to record changes in river runoff over a gradient of contrasting hydroclimatic conditions. Individual foraminifera (Bulimina marginata, Nonionellina labradorica) were analyzed by laser-ablation ICP-MS over a seasonal and spatial gradient within Gullmar Fjord, Swedish west coast, during 2018–2019. The results are compared to an extensive meteorological and hydrological data set, as well as sediment and pore-water geochemistry. Benthic foraminiferal Ba/Ca correlates significantly to riverine runoff; however, the signals contain both spatial trends with distance to Ba source and species-specific influences such as micro-habitat preferences. We deduce that shallow-infaunal foraminifera are especially suitable as proxy for terrestrial Ba input and discuss the potential influence of water-column and pore-water Ba cycling. While distance to Ba source, water depth, pore-water geochemistry, and species-specific effects need to be considered in interpreting the data, our results demonstrate confidence in the use of Ba/Ca of benthic foraminifera from near-continent records as a proxy for past riverine discharge and to identify periods of drought.

Groundwater is an essential resource for drinking water, food production, and industrial applications worldwide. Over-exploitation and pollution pose significant risks to groundwater sustainability. Groundwater models can be powerful tools for optimizing use, managing risks, and aiding decision-making. For this purpose, models should assimilate pertinent data and quantify uncertainties in outcomes. We examine applied modelling for characterization and decision support in Sweden from 2010 to 2023. We also review syllabi of water-related courses in Swedish higher education to assess the inclusion and extent of groundwater modelling education. We find that important academic advances in groundwater modelling over the past two decades have not translated into practical application within Sweden’s industry, that uncertainty quantification is rarely undertaken, and that groundwater modelling remains a low priority in higher education. Based on these findings, we offer recommendations that, while informed by the Swedish context, hold relevance for educational institutions, industry, and decision-makers internationally.