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Rapid mass movements are a major threat in populated landscapes, as they can cause significant loss of life and damage civil infrastructure. Previous work has shown that using environmental seismology methods to monitor such mass movements and establish monitoring systems offers advantages over existing approaches. The first important step in developing an early warning system for rapid mass movements based on seismic signals is automatically detecting events of interest. Though the approach, such as short-term average to long-term average ratio (STA/LTA) and machine learning model, was introduced to detect events (e.g., debris flow and rockfall), it is still challenging to calibrate input parameters and migrate existing methods to other catchments. Detection of debris flows, for instance, is similar to anomaly detection if we consider the seismic stations recording background signals as an overwhelming majority condition. Benford's law describes the probability distribution of the first non-zero digits in numerical datasets, which provides a functional, computationally cheap approach to anomaly detection, such as fraud detection in financial data or earthquake detection in seismic signals. In this study, seismic signals generated by rapid mass movements were collected to check the agreement of the distribution of the first digit with Benford's law. Subsequently, we develop a computationally efficient and non-site-specific model to detect events based on Benford's law using debris flows from the Illgraben, a Swiss torrent, as an example. Our results show that seismic signals generated by high-energy mass movements, such as debris flows, landslides, and lahars, follow Benford's law, while those generated by rockfall and background signals do not. Furthermore, our detector performance in picking debris-flow events is comparable to a published random forest and seismic network-based approach. Our method can be applied at other sites to detect debris-flow events without additional calibration and offers the potential for real-time warnings.

In the coming decades with enhanced rainstorm activity, massive sediment redistribution in Alpine catchments will be a key hazard and challenge in Alpine communities. While several studies have collected data from massive rock slope failures, few studies have quantitatively assessed the cascading sediment redistribution in highly active alpine catchments. Recurrence intervals for cliffs falls are estimated at 80 years (Krautblatter et al., 2012 ), thus, observations of the subsequent sediment cascading are limited or inexistent despite their major role in landscape evolution and sediment fluxes. Digital aerial photogrammetry acquired by governmental agencies is becoming a relevant tool to better understand short landscape response to climate change. Repetitive yearly to bi-yearly orthophotos and DSM extracted from large format aerial surveys represent a valuable monitoring tool at regional scale because of their wide extent coverage (km) at a high spatial resolution (20 cm). This contribution reports the massive sediment redistribution that has been triggered by the multistage failure of >200.000 m³ from the Hochvogel dolomite peak during the summer of 2016. Seven true orthophotos and high-resolution aerial photogrammetric digital surface models (DSM) between 2010 and 2020 were 3D coregistered to a reference system for optimized volume calculation in steep terrain. Three consecutive differential DSMs (2010-2012, 2012-2014, 2014-2015) describe the catchment morphodynamics before the cliff fall, while, the subsequent differential DSMs (2015-2017, 2017-2018, 2018-2020) describe the morphodynamics one year, two years and four years after the cliff fall. Spectrograms from surrounding seismic stations expand the understanding of the cliff fall timing. We observe the decadal throughput of >200.000 m³ of sediment with massive sediments pulses that (i) respond with reaction times of 0-4 years and relaxation times beyond 10 years, (ii) with faster 0-2 years response times in the upper catchment (A&B) and >>2 years response times in the lower catchments, (iii) the inversion of sedimentary (>10²-10³ mm/a) to massive erosive regimes (>10² mm/a) within single years and vice versa and the (iv) dependency of redistribution to rainstorm frequency and intensities. Krautblatter, M., Moser, M., Schrott, L., Wolf, J., Morche, D., 2012. Significance of rockfall magnitude and carbonate dissolution for rock slope erosion and geomorphic work on Alpine limestone cliffs (Reintal, German Alps). Geomorphology 167, 21–34. https://doi.org/10.1016/j.geomorph.2012.04.007

Weather conditions are an important driver of Earth surface dynamics, such as gravitational mass wasting, flood propagation, biological activity events and physical interactions within the critical zone. While there are dedicated sensors to capture meteorological parameters, these sensors are comparably expensive, have a small spatial footprint and often lack the temporal resolution needed to constrain high frequency meteorological dynamics. We introduce the concept of meteo-seismology, i.e. the measurement of first-order ground motion signatures of weather conditions by decisively installed seismic sensors. While meteorological manifestations are generally considered seismic noise and it may seem odd to use seismometers instead of weather stations, geophysical sensors circumvent or complement the above caveats and add further important data to a comprehensive picture of the rapidly changing state of the atmosphere and its interaction with the landscape we live in. Based on examples from prototype forested landscapes in Central Europe and Chilean Patagonia, we demonstrate how seismic stations can be used to infer properties of the pressure and wind field and its coupling to the biosphere, constrain rain intensity and drop properties, yield temperature proxies and their propagation into the ground, and survey ground moisture trends and discharge patterns. Understanding the seismic signatures of a meteorological origin also allows to, vice versa, better handle the contaminating side of these seismic sources in records, where high frequency signals are to be used for other than meteo-seismological studies. Our approach offers an alternative and complementary way to non-invasively monitor hydrometeorological energy and matter fluxes at high temporal and spatial resolution.

On 14th and 15th July 2021 heavy rainfall in western Germany, Belgium and the Netherlands caused severe floodings. The most affected area in Germany was the 86 km long Ahr river valley, which suffered from severe damage to buildings and infrastructure and where more than 130 people died. The Ahr flood exceeded a return period of at minimum 500 years. The river Ahr drains around 900 km2 of the Rhenish Massif with a dendritic catchment from west to east causing differences in slope properties and covering different land uses. The flood water carried large woody debris that caused clogging in bridges of the main valley and some tributaries, some of which collapsed. This extreme event thus offers the opportunity to explore the spatial impact and characteristics of large wood on channel dynamics. This study aims to find thresholds for the initiation of large wood recruitment, dependent on catchment size, valley slopes, water quantity and land use.The study focuses on the whole catchment area of the Ahr river. Using general vegetation data obtained from the German national forest inventory, we quantified the type and amount of flood-affected vegetation. We adopted an NDVI (normalized differential vegetation index) based change detection approach using Landsat/Sentinel satellite data (Google Earth Engine based Hazmapper) to identify recruited live vegetation and deadwood transport during the flood. We validated this remotely obtained data with field surveys along selected valley sections.Large wood was predominantly recruited from the fluvial corridor in the main Ahr valley and not from the tributaries, even if those experienced heavy precipitation and surface runoff (up to few meters high discharge on the flood plains). Although we have observed transported tree trunks in those tributaries, there was no large pattern. We aspire to identify deposition areas using ortho photos to investigate a wood balance.Including large wood in flood modelling would improve flood hazard assessments. Remote sensing analyses offer an interim solution in this regard by helping to identify potential large wood recruitment areas and inform designing flood hazard prevention measures.

Alpine glaciers have been rapidly retreating and at increasing rates in recent decades due to climate warming. As a consequence, large amounts of suspended- and bed-load flux are being released to proglacial environments, such as proglacial forefields. These regions are among the most unstable geomorphic systems of the Earth because they rapidly respond to changing discharge and sediment conditions. Given this, it might be hypothesized that their intense morphodynamic activity, being a complex and non-linear process, could “shred” the sediment transport signal itself, and especially that related to subglacial sediment export.To date, our knowledge on subglacial sediment export by subglacial streams is essentially dominated by suspended sediment dynamics recorded in front of shrinking glaciers because of the limitations in measuring bedload transport. The latter is usually monitored far downstream from glacier termini by permanent stations (e.g. water intakes, geophone systems) leaving major uncertainties in the absolute amounts and temporal patterns of transport in both glacial and proglacial environments, as well as the relative importance compared to suspended sediment in case of morphodynamic filtering. Thus, the aim of this project was to investigate the evolution of the both suspended- and bedload subglacial export signals within the proglacial forefield to quantify the extent and the timescale over which proglacial morphodynamics filter them.This work focuses on a large Alpine glacial forefield, almost 2 km in length, that has formed since the early 1980s at the Glacier d’Otemma (southern-western Swiss Alps, Valais). Data were collected over two entire melt seasons (June-September 2020 and 2021) experiencing different climatic conditions, the first year warm and relatively dry and the second cold and relatively wet. Suspended transport was recorded using conventional turbidity-suspended sediment concentration relationship, bedload transport was monitored seismically, while the morphodynamic filtering was determined using signal post-processing techniques. At present, there are no studies combining continuous measurements of both suspended- and bed-loads in such environments.Results show that the signal of subglacial bedload export, unlike suspended load export, is rapidly shredded by proglacial stream morphodynamics, which we show is due to a particle-size dependent autogenic sorting of sediment transport at both daily and seasonal time-scales. The result is that over very short distances, the signal of subglacial bedload sediment export is lost and replaced by a signal dominated by morphodynamic reworking of the proglacial braidplain. The suspended signal is less impeded but significant floodplain storage and release of suspended sediment was observed. These results question the reliability of current inferences of glacial erosion rates from sediment transport rates often measured some way downstream of glacier margins.

Rock slope instabilities cause significant risk in populated alpine areas. To anticipate the final failure, a detailed understanding of the preparatory process dynamics including all potential promoting and triggering factors is needed. While standard external and internal drivers are known, measured evidence and a quantification of their relevance at a specific site is often lacking.Here, we present the evolution of the imminent Hochvogel summit failure (200,000–600,000 m³) over multiple decades towards the current highly sensitive system. We identified the three most relevant potential drivers at the Hochvogel instability: (i) earthquakes, (ii) seasonal and short-term meteorological effects and (iii) increasing internal stress. To quantify these, we use diverse sources of information. Earthquake catalogues and the records of the regional seismic broadband stations help to constrain known historical rock fall events at the Hochvogel. The effect of precipitation events, snowmelt and temperature is quantified by the analysis of high-resolution crack opening and rain data of the last four years. Finally, we exploit the record of our local seismic network to reveal internal rock bridge failures, rock fall activity in the flanks and the seismic stressing of the instable mass due to local earthquakes.The current process dynamics prove a close-to-failure status of the instability. The combination of historic records and high-resolution real-time data not only makes the Hochvogel a benchmark site for alpine hazard early warning but also enables the comprehensive definition and quantification of its relevant drivers. This will improve the global understanding of rock failure dynamics and so the anticipation ability for instable rock slopes.

Large Alpine glaciers typically export significant quantities of subglacially eroded sediment to their downstream environments via meltwater streams. The supply of this glaciogenically-produced sediment has an extensive impact on landform genesis and evolution; downstream ecology and ecosystem succession; river morphology and flood risk management; hydropower installations and industrial sediment extraction. However, little is known about the processes and mechanisms driving the entrainment and evacuation of subglacial sediment by meltwater flow. Controls on the rate of sediment export remain poorly constrained, limiting the reliability of future sediment yield predictions. Although the fine (suspended) fraction of meltwater-borne subglacial sediment export is relatively well studied, records of suspended sediment load are commonly obtained from distal proglacial locations and may consequently be affected by filtering effects in proglacial rivers and forefields. Additionally, almost nothing is known about the coarse (bedload) component and its relationship to suspended sediment transport due to the difficulties in monitoring bedload flux. In this study, we present a first-of-its-kind dataset from Glacier d’Otemma, Switzerland, capturing three years (2020, 2021 and 2022) of continuous suspended sediment load, bedload and water discharge data from a monitoring site immediately in front of the glacier meltwater portal. Measurements of coarse sediment flux were performed using recently developed environmental seismological monitoring techniques. Data from all three years show that bedload delivery to the glacier margin switches from being transport-limited to being supply-limited during the melt season and was driven by snow-line retreat. Bedload evacuation reduces to very low levels as soon as the snow-line reaches the upper parts of the glacier, which it does increasingly often due to climate warming. We hypothesise that the position of the snow line controls the degree of channelisation – or the efficiency – of the subglacial drainage network above and below it, with consequences for both sediment availability and channel competence. Meltwater in the non-channelised parts of the glacier struggles to transport bedload. As the channelisation develops, accumulated bedload is evacuated until the point at which the subglacial channel network reaches its maximum extent or, due to progressive channel division in a dendritic network, is developing channels that are too small to readily transport it. Thus, recent reports of increases in bedload yield from Alpine glaciers may not reflect increases in glacial erosion but simply an increase in the upstream elevation of snow-lines, the associated subglacial channelization and hence subglacial bedload export capacity.

Seafloor sediment flows (turbidity currents) form some of the largest sediment accumulations on Earth, carry globally significant volumes of organic carbon, and can damage critical seafloor infrastructure. These fast and destructive events are notoriously challenging to measure in action, as they often damage any instruments anchored within the flow. We present the first direct evidence that turbidity currents generate seismic signals which can be remotely sensed (~1-3 km away), revealing the internal structure and remarkably prolonged duration of the longest runout sediment flows on Earth. Passive Ocean Bottom Seismograph (OBS) sensors, located on terraces of the Congo Canyon, offshore West Africa, recorded thirteen turbidity currents over an 8-month period. The occurrence and timing of these turbidity currents was confirmed by nearby moorings with acoustic Doppler current profilers.Results show that turbidity currents travelling over ~1.5 m/s produce a seismic signal concentrated below 10 Hz with a sudden onset and more gentle decay. Comparison of the seismic signals with information on flow velocities from the acoustic Doppler current profilers demonstrates that the seismic signal is generated by the fast-moving front of the flow (frontal cell), which contains higher sediment concentrations compared to the slower-moving body. Long runout flows travelling >1000 km have a fast (3.7-7.6 m s-1) frontal cell, which can be 14 hours, and ~350 km long, with individual flows lasting >3 weeks. Flows travelling >1000 km eroded >1300 Mt of sediment in one year, yet had near-constant front speeds, contrary to past theory. The seismic dataset allows us to propose a fundamental new model for how turbidity currents self-sustain, where sediment fluxes into and from a dense frontal layer are near-balanced.Seismic monitoring of turbidity currents provides a new method to record these hazardous submarine flows, safely, over large areas, continuously for years yet at sub-second temporal resolution. Monitoring these processes from land would considerably ease deployment efforts and costs. Thus, work is underway investigating if terrestrial seismic stations can record submarine seafloor processes in Bute Inlet, a fjord in western Canada where independent measurement of delta-lip failures and turbidity currents can be compared to a passive seismic dataset.

Climate change affects temperate forests particularly by changes in water availability as a result of rising temperatures and changing precipitation dynamics. While the annual mean will remain roughly constant, it is the intensity pattern that will change: light precipitation events decrease and heavy precipitation events increase. Droughts and heat waves are assumed to become more frequent, longer and more intense, also as a feedback mechanism of reduced soil moisture affecting evapotranspiration. In addition to meteorological droughts, edaphic droughts are anticipated to increase in the future. These developments impact the soil hydrological functions with altered infiltration conditions, increased surface runoff and an increasing proportion of preferential flow affecting a more complex and heterogeneous water distribution in the subsurface. Yet the link between tree mortality and the reduced and more heterogenous soil water distribution is still not fully understoodThe majority of approaches analysing soil moisture dynamics are based on point measurements, which do not account for the high spatial variability of soil water. Here, we close this knowledge gap by fusing established point-measurements with geophysical methods to assess the spatio-temporal dynamics of water fluxes in the near-surface subsoil from slope to the root zone scale. The questions we ask focus on how infiltration, subsurface water flow, soil moisture distribution and persistence are affected by (i) the subsurface architecture including textural variations as well as preferential flow paths (macro pores, root tracks) and (ii) hydrological extremes (droughts, rain events).Our study site is located in a beech forest near Ebergötzen (central Germany). The Triassic sandstones are overlain by periglacial slope deposits with varying amounts of loess. The Ebergötzen test site is equipped with numerous sensors for analysing water and element fluxes. In addition to meteorological parameters, we collect 15 min times series of throughfall, stemflow, soil water content, water tension and sap flow. This set-up is ideally suited to quantify water fluxes on a point-by-point basis with high temporal resolution, and to validate complementary, beyond-point approaches. To account for the small-scale variability of processes, geophysical methods with a focus on high-resolution electrical resistivity tomography (Dipole-Dipole, 48 electrodes, 15 cm spacing) were used. Measurements were carried out as a combination of a long-term approach (fortnightly/monthly) and event-based measurements (thunderstorm, round the clock).Our data indicate a relatively uniform decrease in soil moisture during prolonged dry periods, with root-water uptake locally causing higher dynamics. In contrast, subsurface moisture penetration after precipitation events is spatially highly variable, confirming the importance of preferential flow for infiltration and distribution of water in the subsurface and thus show the high demand for spatially high-resolution measurements of soil moisture dynamics.

12 páginas.- 4 figuras.- referencias.- Additional supporting information can be found online in the Supporting Information section at the end of this article.- Full Access in https://onlinelibrary.wiley.com/doi/full/10.1111/geb.13652, Aim Our understanding of the mechanisms that maintain forest diversity under changing climate can benefit from knowledge about traits that are closely linked to fitness. We tested whether the link between traits and seed number and seed size is consistent with two hypotheses, termed the leaf economics spectrum and the plant size syndrome, or whether reproduction represents an independent dimension related to a seed size–seed number trade-off. Location Most of the data come from Europe, North and Central America and East Asia. A minority of the data come from South America, Africa and Australia. Time period 1960–2022. Major taxa studied Trees. Methods We gathered 12 million observations of the number of seeds produced in 784 tree species. We estimated the number of seeds produced by individual trees and scaled it up to the species level. Next, we used principal components analysis and generalized joint attribute modelling (GJAM) to map seed number and size on the tree traits spectrum. Results Incorporating seed size and number into trait analysis while controlling for environment and phylogeny with GJAM exposes relationships in trees that might otherwise remain hidden. Production of the large total biomass of seeds [product of seed number and seed size; hereafter, species seed productivity (SSP)] is associated with high leaf area, low foliar nitrogen, low specific leaf area (SLA) and dense wood. Production of high seed numbers is associated with small seeds produced by nutrient-demanding species with softwood, small leaves and high SLA. Trait covariation is consistent with opposing strategies: one fast-growing, early successional, with high dispersal, and the other slow-growing, stress-tolerant, that recruit in shaded conditions. Main conclusions Earth system models currently assume that reproductive allocation is indifferent among plant functional types. Easily measurable seed size is a strong predictor of the seed number and species seed productivity. The connection of SSP with the functional traits can form the first basis of improved fecundity prediction across global forests., The project has been funded by grants to J.S.C. from the National Science Foundation, most re-cently DEB-1754443, and by the Belmont Forum (1854976), NASA (AIST16-0052 and AIST18-0063) and the Programme d'Investissement d'Avenir under project FORBIC (18-MPGA-0004; Make Our Planet Great Again). Jerry Franklin's data remain acces-sible through NSF LTER DEB-1440409. Data from Hubbard Brook (New Hampshire) were funded through NSF-LTER. Puerto Rico data were funded by NSF grants, most recently DEB 0963447 and LTREB 11222325. Data from the Andes Biodiversity and Ecosystem Research Group were funded by the Gordon and Betty Moore Foundation and NSF 727 LTREB 1754647. M.B. was supported by grant no. 2019/35/D/NZ8/00050 from the (Polish) National Science Centre and by Polish National Agency for Academic Exchange Bekker programme PPN/BEK/2020/1/00009/U/00001. Research by the USDA Forest Service and the USGS was funded by these agencies. Any use of trade, firm or product names does not imply endorsement by the US Government. Any use of trade, firm, or product names is for descriptive purposes only and does not imply en -dorsement by the U.S. Government

Massive sediment pulses in catchments are a key alpine multi-risk component. Substantial sediment redistribution in alpine catchments frequently causes flooding, river erosion, and landsliding, and affects infrastructure such as dam reservoirs as well as aquatic ecosystems and water quality. While systematic rock slope failure inventories have been collected in several countries, the subsequent cascading sediment redistribution is virtually unaccessed. This contribution reports for the first time the massive sediment redistribution triggered by the multi-stage failure of more than 150,000 m3 from the Hochvogel dolomite peak during the summer of 2016. We applied change detection techniques on seven 3D-coregistered high-resolution true-orthophotos and digital surface models (DSM) obtained through digital aerial photogrammetry later optimized for precise volume calculation in steep terrain. The analysis of seismic information from surrounding stations revealed the temporal evolution of the cliff fall. We identified the proportional contribution of > 600 rockfall events (>1 m3) from 4 rock slope catchments with different aspects and their volume estimates. In a sediment cascade approach, we evaluated erosion, transport, and deposition from the rockface to the upper channelized erosive debris flow channel, then to the widened dispersive debris flow channel, and finally to the outlet into the braided sediment-supercharged Jochbach river. We observe the decadal flux of more than 400,000 m3 of sediment with massive sediment pulses that (i) respond with reaction times of 0–4 years and relaxation times beyond 10 years, (ii) with faster response times of 0–2 years in the upper catchment and more than 2 years response times in the lower catchments, (iii) the inversion of sedimentary (102–103 mm/a) to massive erosive regimes (102 mm/a) within single years and the (iv) dependency of redistribution to rainfall frequency and intensity. This study provides generic information on spatial and temporal patterns of massive sediment pulses in highly-charged alpine catchments.

The Coastal Temperate Rainforests (CTRs) of Chilean Patagonia are a valuable forest biome on Earth given its prominent role for biogeochemical cycling, ecological value and dynamic of surface processes. The Patagonian CTRs are amongst the most carbon rich biomes on Earth. Together with frequent landscape disturbances, these forests potentially allow for episodic, massive release of carbon into the atmosphere. We argue that despite their particular biogeographic, geochemical, and ecological role, the Patagonian CTRs in particular, and the global CTRs in general, are not adequately represented in the current catalogue listing critical zone observatories (CZO). Here, we present the Pumalin CZO as the first of its kind, located in the Pumalin National park in northern Chilean Patagonia. We have identified four core research themes for the Pumalin CZO around which our activities circle in an integrative, quantitative, generic approach using a range of emerging techniques. We aim to gain quantitative understanding of these topics: (1) carbon sink functioning, (2) biota-driven landscape evolution, (3) water, biogeological and energy fluxes, and (4) disturbance regime understanding. Our findings highlight the multitude of active functions that trees in particular, and forests in general, may have on the entire chain of carbon cycling. This highlights the importance of an integrated approach, i.e., ‘one physical system’, as proposed by Richter and Billings (2015), and accounting for the recent advances in pushing nature conservation along the Chilean coast.

One of the pillars of geomorphology is the study of geomorphic processes and their drivers, dynamics, and impacts. Like all activity that transfers energy to Earth's surface, a wide range of geomorphic process types create seismic waves that can be measured with standard seismic instruments. Seismic signals provide continuous high-resolution coverage with a spatial footprint that can vary from local to global, and in recent years, efforts to exploit these signals for information about surface processes have increased dramatically, coalescing into the emerging field of environmental seismology. The application of seismic methods has the potential to drive advances in our understanding of the occurrence, timing, and triggering of geomorphic events, the dynamics of geomorphic processes, fluvial bedload transport, and integrative geomorphic system monitoring. As new seismic applications move from development to proof of concept to routine application, integration between geomorphologists and seismologists is key for continued progress. ▪ Geomorphic activity on Earth's surface produces seismic signals that can be measured with standard seismic instruments. ▪ Seismic methods are driving advances in our understanding of the occurrence, triggering, and internal dynamics of a range of geomorphic processes. ▪ Dedicated seismic-based observatories offer the potential to comprehensively characterize geomorphic activity and its impacts across a landscape. ▪ Collaboration between seismologists and geomorphologists is fostering the development of new applications, models, and analysis techniques for geomorphic seismology.

The ability to monitor, understand, and predict the dynamics of the terrestrial carbon cycle requires the capacity to robustly and coherently synthesize multiple streams of information that each provide partial information about different pools and fluxes. In this study, we introduce a new terrestrial carbon cycle data assimilation system, built on the PEcAn model–data eco-informatics system, and its application for the development of a proof-of-concept carbon “reanalysis” product that harmonizes carbon pools (leaf, wood, soil) and fluxes (GPP, Ra, Rh, NEE) across the contiguous United States from 1986–2019. We first calibrated this system against plant trait and flux tower net ecosystem exchange (NEE) using a novel emulated hierarchical Bayesian approach. Next, we extended the Tobit–Wishart ensemble filter (TWEnF) state data assimilation (SDA) framework, a generalization of the common ensemble Kalman filter which accounts for censored data and provides a fully Bayesian estimate of model process error, to a regional-scale system with a calibrated localization. Combined with additional workflows for propagating parameter, initial condition, and driver uncertainty, this represents the most complete and robust uncertainty accounting available for terrestrial carbon models. Our initial reanalysis was run on an irregular grid of ∼ 500 points selected using a stratified sampling method to efficiently capture environmental heterogeneity. Remotely sensed observations of aboveground biomass (Landsat LandTrendr) and leaf area index (LAI) (MODIS MOD15) were sequentially assimilated into the SIPNET model. Reanalysis soil carbon, which was indirectly constrained based on modeled covariances, showed general agreement with SoilGrids, an independent soil carbon data product. Reanalysis NEE, which was constrained based on posterior ensemble weights, also showed good agreement with eddy flux tower NEE and reduced root mean square error (RMSE) compared to the calibrated forecast. Ultimately, PEcAn's new open-source regional data assimilation framework provides a scalable workflow for harmonizing multiple data constraints and providing a uniform synthetic platform for carbon monitoring, reporting, and verification (MRV) as well as accelerating terrestrial carbon cycle research.

Tree-ring time series provide long-term, annually resolved information on the growth of trees. When sampled in a systematic context, tree-ring data can be scaled to estimate the forest carbon capture and storage of landscapes, biomes, and—ultimately—the globe. A systematic effort to sample tree rings in national forest inventories would yield unprecedented temporal and spatial resolution of forest carbon dynamics and help resolve key scientific uncertainties, which we highlight in terms of evidence for forest greening (enhanced growth) versus browning (reduced growth, increased mortality). We describe jump-starting a tree-ring collection across the continent of North America, given the commitments of Canada, the United States, and Mexico to visit forest inventory plots, along with existing legacy collections. Failing to do so would be a missed opportunity to help chart an evidence-based path toward meeting national commitments to reduce net greenhouse gas emissions, urgently needed for climate stabilization and repair.

Debris flows threaten communities in mountain regions worldwide. Combining modern photogrammetric processing with autonomous unmanned aerial vehicle (UAV) flights at sub-weekly intervals allows mapping of sediment dynamics in a debris flow catchment. This provides important information for sediment disposition that pre-conditions the catchment for debris flow occurrence. At the Illgraben debris-flow catchment in Switzerland, our autonomous UAV launched nearly 50 times in the snow-free periods in 2019–2021 with typical flight intervals of 2–4 days, producing 350–400 images every flight. The observed terrain-changes resulting from debris flows exhibit preferred locations of erosion and deposition, including memory effects as previously deposited material is preferentially removed during subsequent debris flows. Such data are critical for the validation of geomorphological process models. Given the remote terrain, the mapped short-term erosion and deposition structures are difficult to obtain with conventional measurements. The proposed method thus fills an observational gap, which ground-based monitoring and satellite based remote sensing cannot fill as a result of limited access, reaction time, spatial resolution, or involved costs.

Canopy radiative transfer is the primary mechanism by which models relate vegetation composition and state to the surface energy balance, which is important to light- and temperature-sensitive plant processes as well as understanding land–atmosphere feedbacks. In addition, certain parameters (e.g., specific leaf area, SLA) that have an outsized influence on vegetation model behavior can be constrained by observations of shortwave reflectance, thus reducing model predictive uncertainty. Importantly, calibrating against radiative transfer outputs allows models to directly use remote sensing reflectance products without relying on highly derived products (such as MODIS leaf area index) whose assumptions may be incompatible with the target vegetation model and whose uncertainties are usually not well quantified. Here, we created the EDR model by coupling the two-stream representation of canopy radiative transfer in the Ecosystem Demography model version 2 (ED2) with a leaf radiative transfer model (PROSPECT-5) and a simple soil reflectance model to predict full-range, high-spectral-resolution surface reflectance that is dependent on the underlying ED2 model state. We then calibrated this model against estimates of hemispherical reflectance (corrected for directional effects) from the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and survey data from 54 temperate forest plots in the northeastern United States. The calibration significantly reduced uncertainty in model parameters related to leaf biochemistry and morphology and canopy structure for five plant functional types. Using a single common set of parameters across all sites, the calibrated model was able to accurately reproduce surface reflectance for sites with highly varied forest composition and structure. However, the calibrated model's predictions of leaf area index (LAI) were less robust, capturing only 46 % of the variability in the observations. Comparing the ED2 radiative transfer model with another two-stream soil–leaf–canopy radiative transfer model commonly used in remote sensing studies (PRO4SAIL) illustrated structural errors in the ED2 representation of direct radiation backscatter that resulted in systematic underestimation of reflectance. In addition, we also highlight that, to directly compare with a two-stream radiative transfer model like EDR, we had to perform an additional processing step to convert the directional reflectance estimates of AVIRIS to hemispherical reflectance (also known as “albedo”). In future work, we recommend that vegetation models add the capability to predict directional reflectance, to allow them to more directly assimilate a wide range of airborne and satellite reflectance products. We ultimately conclude that despite these challenges, using dynamic vegetation models to predict surface reflectance is a promising avenue for model calibration and validation using remote sensing data.

Monitoring leaf phenology tracks the progression of climate change and seasonal variations in a variety of organismal and ecosystem processes. Networks of finite-scale remote sensing, such as the PhenoCam network, provide valuable information on phenological state at high temporal resolution, but they have limited coverage. Satellite-based data with lower temporal resolution have primarily been used to more broadly measure phenology (e.g., 16 d MODIS normalized difference vegetation index (NDVI) product). Recent versions of the Geostationary Operational Environmental Satellites (GOES-16 and GOES-17) can monitor NDVI at temporal scales comparable to that of PhenoCam throughout most of the western hemisphere. Here we begin to examine the current capacity of these new data to measure the phenology of deciduous broadleaf forests for the first 2 full calendar years of data (2018 and 2019) by fitting double-logistic Bayesian models and comparing the transition dates of the start, middle, and end of the season to those obtained from PhenoCam and MODIS 16 d NDVI and enhanced vegetation index (EVI) products. Compared to these MODIS products, GOES was more correlated with PhenoCam at the start and middle of spring but had a larger bias (3.35 ± 0.03 d later than PhenoCam) at the end of spring. Satellite-based autumn transition dates were mostly uncorrelated with those of PhenoCam. PhenoCam data produced significantly more certain (all p values ≤0.013) estimates of all transition dates than any of the satellite sources did. GOES transition date uncertainties were significantly smaller than those of MODIS EVI for all transition dates (all p values ≤0.026), but they were only smaller (based on p value <0.05) than those from MODIS NDVI for the estimates of the beginning and middle of spring. GOES will improve the monitoring of phenology at large spatial coverages and provides real-time indicators of phenological change even when the entire spring transition period occurs within the 16 d resolution of these MODIS products.

Despite their low contribution to forest carbon stocks, lianas (woody vines) play an important role in the carbon dynamics of tropical forests. As structural parasites, they hinder tree survival, growth and fecundity; hence, they negatively impact net ecosystem productivity and long‐term carbon sequestration.Competition (for water and light) drives various forest processes and depends on the local abundance of resources over time. However, evaluating the relative role of resource availability on the interactions between lianas and trees from empirical observations is particularly challenging. Previous approaches have used labour‐intensive and ecosystem‐scale manipulation experiments, which are infeasible in most situations.We propose to circumvent this challenge by evaluating the uncertainty of water and light capture processes of a process‐based vegetation model (ED2) including the liana growth form. We further developed the liana plant functional type in ED2 to mechanistically simulate water uptake and transport from roots to leaves, and start the model from prescribed initial conditions. We then used the PEcAn bioinformatics platform to constrain liana parameters and run uncertainty analyses.Baseline runs successfully reproduced ecosystem gas exchange fluxes (gross primary productivity and latent heat) and forest structural features (leaf area index, aboveground biomass) in two sites (Barro Colorado Island, Panama and Paracou, French Guiana) characterized by different rainfall regimes and levels of liana abundance.Model uncertainty analyses revealed that water limitation was the factor driving the competition between trees and lianas at the drier site (BCI), and during the relatively short dry season of the wetter site (Paracou). In young patches, light competition dominated in Paracou but alternated with water competition between the wet and the dry season on BCI according to the model simulations.The modelling workflow also identified key liana traits (photosynthetic quantum efficiency, stomatal regulation parameters, allometric relationships) and processes (water use, respiration, climbing) driving the model uncertainty. They should be considered as priorities for future data acquisition and model development to improve predictions of the carbon dynamics of liana‐infested forests. Synthesis. Competition for water plays a larger role in the interaction between lianas and trees than previously hypothesized, as demonstrated by simulations from a process‐based vegetation model., Competition for water plays a larger role in the interaction between lianas and trees than previously hypothesized, as demonstrated by simulations from a process‐based vegetation model.

Exceptional rainfalls (up to 200 mm in 72 h) in W-Germany, the Netherlands and Belgium led to severe flooding on 14-15 July 2021. In Germany the Ahr valley (Eifel mountains) was hit heavily, leading to 134 fatalities and substantial loss of property and infrastructure. Besides the damage in the floodplains, multiple shallow landslides were triggered along the Ahr embankments. Furthermore, the flood caused undercutting of several old landslide bodies. One such landslide in Devonian Schist bedrock is located at a narrow, bended stretch of the Ahr, near the town of Müsch. A complete failure has the potential to dam the river posing a considerable hazard.The main objectives of this study are to gain an in-depth understanding of the landslide causes and its transient activity. These objectives are tackled by a multi-method approach: landslide mapping, analysis of pre- and post-event airborne laser scanning (ALS) and terrestrial laser scanning (TLS) data, electrical resistivity tomography (ERT), seismic refraction tomography (SRT), passive seismic monitoring, geotechnical analysis and interviews with local inhabitants.The old landslide is 100 m wide and 200 m long. Preliminary analysis of ERT and SRT indicate a landslide depth of 20-30 m, leading to an overall landslide volume of 400,000 - 600,000 m³. ERT further shows underlying bedrock properties and water saturated zones. An old dumpsite as well as an ancient railway, now used as forest trail, cutting through the landslide horizontally are clearly shown as resistive zones. Analysis of ALS data shows that so far only the frontal part at the Ahr banks has been active and has lost about 6300 m³ due to fluvial erosion and landsliding. Field mapping shows clear signs of retrogressive landsliding. From October 2021 onwards the landslide body has been equipped with five geophones to record both subtle changes in ground rheology and discrete events of rock bridge failure due to incremental mass movement. Currently most seismic signals at the slope can be allocated to daily traffic and road construction in the area.The combination of geophysical and remote sensing methods enables a profound insight into the mechanisms and present processes of the Müsch landslide. Based on this, we will be able to assess the probability for a reactivation of the whole landslide body, which could trigger cascading hazards affecting a much larger region. An improved monitoring concept will be developed which can be adopted to similar structures in the Ahr valley and beyond.

Valley confined floods are a major hazard. In contrast to large river floods with day long warning time, they can evolve within minutes to hours, exhibit higher flow velocities and drive large amounts of debris into populated places. While many Alpine communities have developed mitigation, early warning and rapid response schemes for this natural hazard type, these measures are virtually unknown in Central European upland regions. Beyond flood protection, lacking measurement infrastructure also prevents retrospective collection of event anatomy data, which would be key to understand the evolution of an event and, hence to improve our response to future hazards.The 14–15 July 2021 flood that hit the Ahr valley in the Eifel mountains, west Germany, was a drastic example of the potential of such valley confined floods. A wall of water flushed through the deeply incised valley, flooding more than 15 towns and affecting 42,000 people, resulting in the highest number of casualties in Germany since 1962. All gauges along the main channel were destroyed while the flood hydrograph was still on the rising limb and grid power loss interrupted collection and transmission of data from other potential sensors.Here, we use data from a single seismic station near the town of Ahrweiler, originally deployed for earthquake seismology. Despite grid power cutoff around 23:19 CEST, the station recorded the arrival of the fast rising limb of the flood. We show how even an incomplete record of a single station not set up for flood early warning can be used to infer crucial and timely information about the flood: propagation velocity, water level and debris transport rate. We argue that installing a network of a few distributed low cost seismic sensors could have improved flood early warning and near real time provision of kinetic flood data. More importantly, such a network would be the key for improved response actions for future floods, deemed more likely in Central Europe under the currently changing climate conditions.

Bed load transport is a critical parameter in the study of landscape evolution and also provides valuable information for problems in the fields of ecology, river and landuse management, and civil engineering. Bed load transport is difficult to assess due to its stochastic nature and highly variable transport rates, and traditional measurement techniques have struggled to capture the spatial and temporal variability of bed load transport. In recent years, bed load monitoring based on seismological observations has emerged, which allows non-invasive and continuous indirect measurements. However, there still remains a significant challenge to independently characterise the seismic signature of bed load from other sources of noise, such as turbulence. Our study aims to explore seismic data recorded at the highly braided River Feshie in Scotland, which has undergone significant morphological change in its history and has been highly monitored over the last couple decades through Digital Elevation Models. Since the deployment of our seismometers in December 2020 we have captured three independent high flow events plus an isolated earthquake, which are being used to determine the environmental signals and the site specific signal characteristics. In some previous studies, an observed hysteretic relationship between seismic power and hydrological parameters has been interpreted as being characteristic of bed load transport. From the data we have gathered we have observed a hysteresis in the signals, and through Shields calculations it is suggested that bed load transport would be expected during these events. However, without independent constraints we do not feel we can be absolutely certain that this behaviour is a result of bed load transport. Our ongoing study therefore aims to combine multiple physical measurement techniques, such as hydroacoustic measurements, time-lapse imagery and seismic observations, to try and pinpoint what is contributing to the seismic signals recorded and how we can isolate the bed load transport component.

In order to reduce the societal impact of mass-wasting events, we need observations to investigate the factors that control slope failure, such as the state of crack propagation along a failure plane. However, usually the failure plane is not accessible in-situ. Hence, cracks have to be monitored indirectly, for example using seismic methods.We analysed the data from a seismometer array in the Illgraben catchment, Switzerland, that had registered a series of crack propagation and mass-wasting events, leading to a main event that happened on 2 January 2013. We used a state-of-the-art machine learning technique based on hidden Markov models to detect and classify the seismic signals of crack events. We obtained the temporal evolution of three signal types: (1) single crack signal, (2) rock avalanche and (3) rockfall activity due to debris remobilization. The temporal evolution of the number of cracks showed a linear trend in the weeks prior to the main mass-wasting event and, in the hours preceding the main event, a sigmoidal exponential growth. Using these observations, we propose a mechanistic model to describe the rupture of the failure plane. The model considers the internal parameter of the total crack boundary length as the primary control on failure plane evolution, in addition to the previously suggested crack propagation velocity control parameter. According to this model, internal parameters appear to be the dominant control for the failure plane growth at a slope scale.

Rock glaciers are receiving increased attention as a potential source of water and indicator of climate change in periglacial landscapes. They consist of an ice‐debris mixture, which creeps downslope. Although rock glaciers are a wide‐spread feature on the Tibetan Plateau, characteristics such as its ice fraction are unknown as a superficial debris layer inhibits remote assessments. We investigate one rock glacier in the semiarid western Nyainqêntanglha range (WNR) with a multi‐method approach, which combines geophysical, geological and geomorphological field investigations with remote sensing techniques. Long‐term kinematics of the rock glacier are detected by 4‐year InSAR time series analysis. The ice content and the active layer are examined by electrical resistivity tomography, ground penetrating radar, and environmental seismology. Short‐term activity (11‐days) is captured by a seismic network. Clast analysis shows a sorting of the rock glacier's debris. The rock glacier has three zones, which are defined by the following characteristics: (a) Two predominant lithology types are preserved separately in the superficial debris patterns, (b) heterogeneous kinematics and seismic activity, and (c) distinct ice fractions. Conceptually, the studied rock glacier is discussed as an endmember of the glacier—debris‐covered glacier—rock glacier continuum. This, in turn, can be linked to its location on the semiarid lee‐side of the mountain range against the Indian summer monsoon. Geologically preconditioned and glacially overprinted, the studied rock glacier is suggested to be a recurring example for similar rock glaciers in the WNR. This study highlights how geology, topography and climate influence rock glacier characteristics and development., Plain Language Summary: Climate change has begun to impact all regions of our planet. In cold regions, such as high‐mountain areas, rising temperatures lead to massive melting of glaciers. Besides this evident loss of ice, permafrost, a long‐term ice resource hidden in the subsurface, has started to thaw. Rock glaciers as visible permafrost‐related landforms consist of an ice‐debris mixture, which makes them creep downslope. Due to this movement and their recognizable shape, rock glaciers are permafrost indicators in high‐mountain areas. We investigate one rock glacier in the western Nyaingêntanglha Range (Tibetan Plateau) using field and remote sensing methods to understand its development and to know the current state of its ice core. Our main outcome is, that the heterogeneous creeping behavior, the properties of the debris cover as well as the internal distribution of ice are the results of a continuous development from a glacier into today's rock glacier. In particular, the high ice content in particular sections points to such a glacial precondition. The debris layer covering the internal ice attenuates the effect of climate warming. This makes the rock glacier and similar rock glaciers found in the northern part of the mountain range important future water resources for the semiarid region., Key Points: Geophysical and remote sensing methods in concert reveal the morphostructure, ice fraction, and kinematics of the studied rock glacier. Rock glacier characteristics are controlled by geology, topography and climate on the Tibetan Plateau. The studied rock glacier is conceptually interpreted as the endmember of a glacier—debris‐covered glacier—rock glacier continuum., Deutsche Forschungsgemeinschaft (DFG) http://dx.doi.org/10.13039/501100001659

12 Pág., The relationships that control seed production in trees are fundamental to understanding the evolution of forest species and their capacity to recover from increasing losses to drought, fire, and harvest. A synthesis of fecundity data from 714 species worldwide allowed us to examine hypotheses that are central to quantifying reproduction, a foundation for assessing fitness in forest trees. Four major findings emerged. First, seed production is not constrained by a strict trade-off between seed size and numbers. Instead, seed numbers vary over ten orders of magnitude, with species that invest in large seeds producing more seeds than expected from the 1:1 trade-off. Second, gymnosperms have lower seed production than angiosperms, potentially due to their extra investments in protective woody cones. Third, nutrient-demanding species, indicated by high foliar phosphorus concentrations, have low seed production. Finally, sensitivity of individual species to soil fertility varies widely, limiting the response of community seed production to fertility gradients. In combination, these findings can inform models of forest response that need to incorporate reproductive potential., The project has been funded continuously since 1992 by National Science Foundation grants to J.S.C, most recently DEB-1754443, and by the Belmont Forum (1854976), NASA (AIST16-0052, AIST18-0063), and the Programme d’Investissement d’Avenir under project FORBIC (18-MPGA-0004)(Make Our Planet Great Again). Puerto Rico data were funded by NSF grants to M.U., most recently, DEB 0963447 and LTREB 11222325. Data from the Andes Biodiversity and Ecosystem Research Group were funded by the Gordon and Betty Moore Foundation and NSF LTREB 1754647 to M.S. Additional funding to M.Z. came from the W.Szafer Institute of Botany of the Polish Academy of Sciences and the Polish National Science Foundation (2019/33/B/NZ8/0134). M.B. was supported by the Polish National Science Centre grant no. 2019/35/D/NZ8/00050, and Polish National Agency for Academic Exchange Bekker programme PPN/BEK/2020/1/00009/U/00001. J.M.L. was supported by NSF grant DEB 1745496. Jerry Franklin’s data remain accessible through NSF LTER DEB-1440409. USDA Forest Service and USGS research was funded by those agencies.

12 páginas.- 5 figuras.- 67 referencias.- Additional supporting information may be found in the online version of the article at the publisher’s website .- The peer review history for this article is available at https://publons.com/publon/10.1111/ele.14012 .- All data and code supporting our results are archived on the Zenodo Repository at the following link: https://doi.org/10.5281/zenodo.6381799, Lack of tree fecundity data across climatic gradients precludes the analysis of how seed supply contributes to global variation in forest regeneration and biotic interactions responsible for biodiversity. A global synthesis of raw seedproduction data shows a 250-fold increase in seed abundance from cold-dry to warm-wet climates, driven primarily by a 100-fold increase in seed production for a given tree size. The modest (threefold) increase in forest productivity across the same climate gradient cannot explain the magnitudes of these trends. The increase in seeds per tree can arise from adaptive evolution driven by intense species interactions or from the direct effects of a warm, moist climate on tree fecundity. Either way, the massive differences in seed supply ramify through food webs potentially explaining a disproportionate role for species interactions in the wet tropics., The project has been funded by grants to JSC from the National Science Foundation, most recently DEB-1754443, and by the Belmont Forum (1854976), NASA (AIST16-0052, AIST18-0063) and the Programme d’Investissement d’Avenir under project FORBIC (18-MPGA-0004) (Make Our Planet Great Again). Jerry Franklin’s data remain accessible through NSF LTER DEB-1440409. Puerto Rico data were funded by NSF grants, most recently, DEB 0963447 and LTREB 11222325. Data from the Andes Biodiversity and Ecosystem Research Group were funded by the Gordon and Betty Moore Foundation and NSF LTREB 1754647. MB was supported by grant no. 2019/35/D/NZ8/00050 from the (Polish) National Science Centre, and Polish National Agency for Academic Exchange Bekker programme PPN/BEK/2020/1/00009/U/00001. Research by the USDA Forest Service and the USGS was funded by these agencies. Any use of trade, firm or product names does not imply endorsement by the US Government.

Rapidly evolving floods are rare but powerful drivers of landscape reorganisation that have severe and long-lasting impacts on both the functions of a landscape’s subsystems and the affected society. The July 2021 flood that particularly hit several river catchments of the Eifel region in western Germany and Belgium was a drastic example. While media and scientists highlighted the meteorological and hydrological aspects of this flood, it was not just the rising water levels in the main valleys that posed a hazard, caused damage, and drove environmental reorganisation. Instead, the concurrent coupling of landscape elements and the wood, sediment, and debris carried by the fast-flowing water made this flood so devastating and difficult to predict. Because more intense floods are able to interact with more landscape components, they at times reveal rare non-linear feedbacks, which may be hidden during smaller events due to their high thresholds of initiation. Here, we briefly review the boundary conditions of the 14–15 July 2021 flood and discuss the emerging features that made this event different from previous floods. We identify hillslope processes, aspects of debris mobilisation, the legacy of sustained human land use, and emerging process connections and feedbacks as critical non-hydrological dimensions of the flood. With this landscape scale perspective, we develop requirements for improved future event anticipation, mitigation, and fundamental system understanding.

Rain driven flash floods have severe impacts on society and landscape functions. The July 2021 flood in the Eifel region, west Germany, was one drastic example of such impact. While media and scientists rightfully highlighted the meteorological and hydrological aspects of this flood, it was the concurrent reorganisation of important landscape conditions and the debris carried by the fast flowing water that made this flood so devastating and unpredictable.Here, we take a process-based impact perspective and systematically ask, which were the specific roles of non-hydraulic but geomorphic dynamics that implemented the damage, caused flood non-linearities and amplified the landscape deterioration. We combine insights from field mapping campaigns during, right after and within the relaxation phase of the flood with high resolution geophysical and LiDAR surveys to discuss the role of hillslopes, vegetation, fluvial sediment mobilisation and the legacy of anthropogenic landscape reorganisation. We conclude that some of these elements emerged as the flood event evolved, causing either transient effects or persistent landscape features, thus modifying the response of the landscape to future events, also to less intense precipitation events.Our findings not only support more tailored recovery efforts for the flood affected Eifel catchments, but should also inform landscape development trajectories and potentially crucial factors in other Central European regions.

The Ecosystem Demography model version 2.2 (ED-2.2) is a terrestrial biosphere model that simulates the biophysical, ecological, and biogeochemical dynamics of vertically and horizontally heterogeneous terrestrial ecosystems. In a companion paper (Longo et al., 2019a), we described how the model solves the energy, water, and carbon cycles, and verified the high degree of conservation of these properties in long-term simulations that include long-term (multi-decadal) vegetation dynamics. Here, we present a detailed assessment of the model's ability to represent multiple processes associated with the biophysical and biogeochemical cycles in Amazon forests. We use multiple measurements from eddy covariance towers, forest inventory plots, and regional remote-sensing products to assess the model's ability to represent biophysical, physiological, and ecological processes at multiple timescales, ranging from subdaily to century long. The ED-2.2 model accurately describes the vertical distribution of light, water fluxes, and the storage of water, energy, and carbon in the canopy air space, the regional distribution of biomass in tropical South America, and the variability of biomass as a function of environmental drivers. In addition, ED-2.2 qualitatively captures several emergent properties of the ecosystem found in observations, specifically observed relationships between aboveground biomass, mortality rates, and wood density; however, the slopes of these relationships were not accurately captured. We also identified several limitations, including the model's tendency to overestimate the magnitude and seasonality of heterotrophic respiration and to overestimate growth rates in a nutrient-poor tropical site. The evaluation presented here highlights the potential of incorporating structural and functional heterogeneity within biomes in Earth system models (ESMs) and to realistically represent their impacts on energy, water, and carbon cycles. We also identify several priorities for further model development.

Earth system models (ESMs) have been developed to represent the role of terrestrial ecosystems on the energy, water, and carbon cycles. However, many ESMs still lack representation of within-ecosystem heterogeneity and diversity. In this paper, we present the Ecosystem Demography model version 2.2 (ED-2.2). In ED-2.2, the biophysical and physiological processes account for the horizontal and vertical heterogeneity of the ecosystem: the energy, water, and carbon cycles are solved separately for a series of vegetation cohorts (groups of individual plants of similar size and plant functional type) distributed across a series of spatially implicit patches (representing collections of micro-environments that have a similar disturbance history). We define the equations that describe the energy, water, and carbon cycles in terms of total energy, water, and carbon, which simplifies the differential equations and guarantees excellent conservation of these quantities in long-term simulation (< 0.1 % error over 50 years). We also show examples of ED-2.2 simulation results at single sites and across tropical South America. These results demonstrate the model's ability to characterize the variability of ecosystem structure, composition, and functioning both at stand and continental scales. A detailed model evaluation was conducted and is presented in a companion paper (Longo et al., 2019a). Finally, we highlight some of the ongoing model developments designed to improve the model's accuracy and performance and to include processes hitherto not represented in the model.