Key Uncertainties Research Articles

A challenging path to rational and harmonised international regulation of indoor radon.

The main trends of indoor radon regulation in Europe are expressed through the standard ISO 11665-8. This standard, however, ignores the short-term tests (2-7days in practice)-the main tests in the USA, and instead requires conducting long-term tests only (2-12months)-without any justification. Moreover, the temporal (key) uncertainty of indoor radon is ignored altogether, a fact that does not allow the assessment of a room's conformity with a normative at a given reliability (usually 95%). Thus, the current international regulation is neither harmonised nor rational. This paper reports the interim results of storming discussions within the ISO 11665-8 Focus Group, in charge of revising the aforementioned standard. Proposed are the rational criterion for conformity assessment of a room with a normative for both short- and long-term measurements, as well as the indicative values and the algorithm for determining indoor radon temporal uncertainty depending on the measurement duration.

On the variability of the leaf relative uptake rate of carbonyl sulfide compared to carbon dioxide: Insights from a paired field study with two soybean varieties

Carbonyl sulfide (COS) has been proposed as a promising tracer for the estimation of the gross primary productivity (GPP) from ecosystem to global scale in recent years. Despite substantial work at spatial scales from leaf to regions, the uncertainty of COS-based GPP estimates are poorly known compared to widely used GPP estimates derived from the net ecosystem CO2 exchange. One key uncertainty in this context is the leaf relative uptake (LRU) of the COS with respect to the GPP, which must be known a priori. To investigate the influence of environmental factors, like drought, on the variability of the LRU, we conducted an experiment using ecosystem flux measurements of COS, CO2 and H2O from two eddy covariance towers above a soybean field, growing a commercial cultivar and a chlorophyll deficient mutant variety, in two separate plots. Our findings suggest that the LRU does not only differ between plant varieties due to differences in the ratio of the internal to ambient CO2 mole fraction and the internal resistance to COS, but also changes in response to drought. We also found the internal resistance to COS uptake to be a significant factor in controlling the total COS flux for both varieties, but more so for the commercial cultivar. Our study indicates that species-specific differences in the LRU need to be investigated further, and that environmental stress might complicate the usage of COS as a tracer for predicting GPP at ecosystem and global scale.

Examining the differential risk from high-level artificial intelligence and the question of control

Artificial Intelligence (AI) is one of the most transformative technologies of the 21st century. The extent and scope of future AI capabilities remain a key uncertainty, with widespread disagreement on timelines and potential impacts. As nations and technology companies race toward greater complexity and autonomy in AI systems, there are concerns over the extent of integration and oversight of opaque AI decision processes. This is especially true in the subfield of machine learning (ML), where systems learn to optimize objectives without human assistance. Objectives can be imperfectly specified or executed in an unexpected or potentially harmful way. This becomes more concerning as systems increase in power and autonomy, where an abrupt capability jump could result in unexpected shifts in power dynamics or even catastrophic failures. This study presents a hierarchical complex systems framework to model AI risk and provide a template for alternative futures analysis. Survey data were collected from domain experts in the public and private sectors to classify AI impact and likelihood. The results show increased uncertainty over the powerful AI agent scenario, confidence in multiagent environments, and increased concern over AI alignment failures and influence-seeking behavior.

Value of information analysis for pandemic response: intensive care unit preparedness at the onset of COVID-19

BackgroundDuring the early stages of the COVID-19 pandemic, there was considerable uncertainty surrounding epidemiological and clinical aspects of SARS-CoV-2. Governments around the world, starting from varying levels of pandemic preparedness, needed to make decisions about how to respond to SARS-CoV-2 with only limited information about transmission rates, disease severity and the likely effectiveness of public health interventions. In the face of such uncertainties, formal approaches to quantifying the value of information can help decision makers to prioritise research efforts.MethodsIn this study we use Value of Information (VoI) analysis to quantify the likely benefit associated with reducing three key uncertainties present in the early stages of the COVID-19 pandemic: the basic reproduction number (R_0), case severity (CS), and the relative infectiousness of children compared to adults (CI). The specific decision problem we consider is the optimal level of investment in intensive care unit (ICU) beds. Our analysis incorporates mathematical models of disease transmission and clinical pathways in order to estimate ICU demand and disease outcomes across a range of scenarios.ResultsWe found that VoI analysis enabled us to estimate the relative benefit of resolving different uncertainties about epidemiological and clinical aspects of SARS-CoV-2. Given the initial beliefs of an expert, obtaining more information about case severity had the highest parameter value of information, followed by the basic reproduction number R_0. Resolving uncertainty about the relative infectiousness of children did not affect the decision about the number of ICU beds to be purchased for any COVID-19 outbreak scenarios defined by these three parameters.ConclusionFor the scenarios where the value of information was high enough to justify monitoring, if CS and R_0 are known, management actions will not change when we learn about child infectiousness. VoI is an important tool for understanding the importance of each disease factor during outbreak preparedness and can help to prioritise the allocation of resources for relevant information.

Australia’s Onshore Basin Inventories – foundational knowledge synthesis for better design of precompetitive data acquisition

Geoscience Australia’s Onshore Basin Inventories project provides a whole-of-basin inventory of geology, petroleum systems, exploration status and data coverage of hydrocarbon-prone onshore Australian sedimentary basins. Two existing volumes cover many central and north Australian onshore basins, providing a single point of reference and creating a standardised national basin inventory. In addition to summarising the current state of knowledge within each basin, the onshore basin inventory reports identify critical science questions and key exploration uncertainties that may help inform future work program planning and aid in decision making for both government and industry organisations. Under Geoscience Australia’s Exploring for the Future (EFTF) program, several new onshore basin inventory reports are being delivered. The next releases include the Adavale Basin of southern Queensland and a compilation of Australia’s Mesoproterozoic basins. These reports are supported by value-add products that address identified data gaps and evolve regional understanding of basin evolution and prospectivity, including petroleum systems modelling, seismic reprocessing and regional geochemical studies. The Onshore Basin Inventories project continues to provide scientific and strategic direction for precompetitive data acquisition under the EFTF work program, guiding program planning and shaping post-acquisition analysis programs.

Stratospheric Gas‐Phase Production Alone Cannot Explain Observations of Atmospheric Perchlorate on Earth

AbstractPerchlorate has been observed in many environments on Earth and Mars but its sources remain poorly quantified. In this study, we use a global three‐dimensional chemical transport model to simulate perchlorate's gas‐phase photochemical production, atmospheric transport, and deposition on Earth's surface. Model predictions are compared to newly compiled observations of atmospheric concentrations, deposition flux, and oxygen isotopic composition of perchlorate. We find that the modeled gas‐phase production of perchlorate is consistent with reported stratospheric observations. Nevertheless, we show that this mechanism alone cannot explain the high levels of perchlorate observed at many near‐surface sites (aerosol concentrations >0.1 ng m−3 and deposition fluxes >10 g km−2 yr−1) or the low 17O‐excess observed in perchlorate sampled from pristine environments (<+18.4‰). We discuss four hypotheses to explain the model‐observation discrepancies and recommend laboratory and field observations to address key uncertainties in atmospheric sources of perchlorate.

Pest categorisation of Neoscytalidium dimidiatum.

The EFSA Plant Health Panelperformed a pest categorisation of Neoscytalidium dimidiatum, a clearly defined plant pathogenic fungus of the family Botryosphaeriaceae. The pathogen affects a wide range of woody perennial crops and ornamental plants causing symptoms such as leaf spot, shoot blight, branch dieback, canker, pre- and post-harvest fruit rot, gummosis and root rot. The pathogen is present in Africa, Asia, North and South America, and Oceania. It has also been reported from Greece, Cyprus and Italy, with a restricted distribution. Nevertheless, there is a key uncertainty on the geographical distribution of N. dimidiatum worldwide and in the EU, because in the past, when molecular tools were not available, the two synanamorphs of the pathogen (Fusicoccum-like and Scytalidium-like) might have been misidentified based only on morphology and pathogenicity tests. N. dimidiatum is not included in Commission Implementing Regulation (EU) 2019/2072. Because of the wide host range of the pathogen, this pest categorisation focuses on those hosts for which there is robust evidence that the pathogen was formally identified by a combination of morphology, pathogenicity and multilocus sequence analysis. Plants for planting, fresh fruits and bark and wood of host plants as well as soil and other plant growing media are the main pathways for the further entry of the pathogen into the EU. Host availability and climate suitability factors occurring in parts of the EU are favourable for the further establishment of the pathogen. In the areas of its present distribution, including Italy, the pathogen has a direct impact on cultivated hosts. Phytosanitary measures are available to prevent the further introduction and spread of the pathogen into the EU. N. dimidiatum satisfies the criteria that are within the remit of EFSA to assess for this species to be regarded as potential Union quarantine pest.

The impact of policy and model uncertainties on emissions projections of the Paris Agreement pledges

Tracking progress towards the Paris Agreement climate goal requires understanding the 2030 emission levels implied by countries’ National Determined Contributions (NDCs). However, key uncertainties and assumptions impact greenhouse gas (GHG) emission projections implied by the NDCs. This study analyses this impact, both globally and for major emitting countries. We find that the assessed uncertainties markedly affect global GHG emission projections. Full achievement of NDC targets is estimated to result in a range of 46–60 GtCO2eq by 2030 (median estimate: 53 GtCO2eq). The uncertainty in measuring historical emissions, including land-use, as reflected by different datasets is the most important contributing factor. This is followed by two equally important factors globally: socio-economic baseline uncertainty and uncertainty about the emissions implied by current policies in case NDCs are less ambitious than these. Overall, the impact of policy uncertainty (i.e. uncertainty resulting from conditionality of or ranges in NDC targets and uncertainty in emissions resulting from current policies) is about equally important as model/technical uncertainty (i.e. uncertainty in historical emissions and socio-economic baseline variations). This new insight is important for decision makers and researchers because a larger share of the total uncertainty is now attributable to aspects that can be influenced by policy decisions compared to previous analyses of NDC uncertainty.

Pest categorisation of coconut cadang-cadang viroid.

The EFSA Panel on Plant Health updated its 2017 pest categorisation of coconut cadang cadang viroid (CCCVd) for the EU territory due to new data on its host range. The identity of CCCVd, a member of the genus Cocadviroid (family Pospiviroidae), is established and detection and identification methods are available. It is included as a quarantine pest for the EU in the Commission Implementing Regulation (EU) 2019/2072. CCCVd has been reported from the Philippines and Malaysia. It is not known to be present in the EU. The host range of CCCVd is restricted to Arecaceae species (palms), in particular, coconut palm (Cocos nucifera) to which it causes a lethal disease. Oil palm (Elaeis guineensis) and buri palm (Corypha utan) are other natural hosts of CCCVd. Palm species of several genera, including Phoenix spp. and other species grown and/or cultivated in the EU, have been identified as potential hosts. The viroid is naturally transmitted at low rate by seeds and pollen and possibly by additional not yet identified natural transmission means. It can be transmitted through vegetative propagation applied to some palm species. Plants for planting including seeds of its hosts have been identified as the main entry pathway of CCCVd. Potential hosts of CCCVd are present in the EU, therefore establishment is possible. Should the pest establish in the EU, an impact is expected, with uncertainty on its magnitude. The Panel identified the susceptibility of palm species grown in the EU as a key uncertainty potentially affecting the conclusion of this pest categorisation. Nevertheless, the pest satisfies the criteria that are within the remit of EFSA to assess for this viroid to be regarded as potential Union quarantine pest.

Making the metaverse real

Key stakeholders across different industries with competing visions, motivations and technology bets are investing significant financial resources in developing the building blocks of the metaverse. The purpose of this opinion piece aimed primarily at practitioners is to explore the key question: What is needed to make the metaverse real? What are the key uncertainties that must be resolved? We are motivated by shedding light on whether the metaverse is just a new marketing buzzword or a new transformative trend. We have identified six areas with key uncertainties, which require agreement and solutions from industry players – the space, the interface, the IT infrastructure, the monetary infrastructure, the digital ID and the energy. These uncertainties will be resolved in a series of cooperative and competitive games among the key stakeholders who will need to work on being aligned on a set of standards. The practical implication is that the metaverse cannot be ignored, but there are non-trivial challenges that need to be resolved first. Our paper provides a framework for practitioners to think through these issues in a more systematic fashion.

Characterization of key manufacturing uncertainties in next generation therapeutics and vaccines across scales

AbstractViral vectors are advanced therapy products used as genetic information carriers in vaccine and cell therapy development and manufacturing. Despite the first product receiving market authorization in 2012, viral vector manufacturing has still not reached the level of maturity of biologics and is still highly susceptible to process uncertainties, such as viral titers and chromatography yields. This was exacerbated by the COVID‐19 pandemic when viral vector manufacturers were challenged to respond to the global demand in a timely manner. A key reason for this was the lack of a systematic framework and approach to support capacity planning under uncertainty. To address this, we present a methodology for: (i) identification of process cost and volume bottlenecks, (ii) quantification of process uncertainties and their impact on target key performance indicators, and (iii) quantitative analysis of scale‐dependent uncertainties. We use global sensitivity analysis as the backbone to evaluate three industrially relevant vector platforms: adeno‐associated, lentiviral, and adenoviral vectors. For the first time, we quantify how operating parameters can affect process performance and, critically, the trade‐offs among them. Results indicate a strong, direct proportional correlation between volumetric scales and propagation of uncertainties, while we identify viral titer as the most critical scale‐up bottleneck across the three platforms. The framework can de‐risk investment decisions, primarily related to scale‐up and provides a basis for proactive decision‐making in manufacturing and distribution of advanced therapeutics.

Key nuclear data for non-LWR reactivity analysis

An assessment of nuclear data performance for non-light-water reactor (non-LWR) reactivity calculations was performed at Oak Ridge National Laboratory that involved a thorough literature review to collect related observations made across different research institutions, an interrogation of the latest ENDF/B evaluated nuclear data libraries, and propagation of nuclear data uncertainties to key figures of merit associated with reactor safety for six non-LWR benchmarks. The outcome of this comprehensive study was published in a technical report issued by the US Nuclear Regulatory Commission. This paper provides a summary of the study’s key observations and conclusions and demonstrates with two examples how the various methods available in the SCALE code system were used to identify key cross section uncertainties for non-LWR reactivity analyses.

A benthic substrate classification method for seabed images using deep learning: Application to management of deep‐sea coral reefs

Abstract Protecting deep‐sea coral‐based vulnerable marine ecosystems (VMEs) from human impacts, particularly bottom trawling, is a major conservation challenge in world oceans. Management processes for these ecosystems are weakened by key uncertainties that could be substantially addressed by having much greater volumes of quantitative image‐derived data that detail the distribution and abundance of coral reefs and the nature of impacts upon them. Considerably greater volumes of data could be available if the resource costs of image annotation are reduced. In this paper we propose a solution: a deep learning system capable of automatically identifying reef‐building stony corals amongst other seabed substrata in much larger volumes of seabed imagery than was previously possible. Using a previously annotated dataset, we trained a convolutional neural network on approximately 70,000 classified images (‘snips’) comprising six benthic substrate classes, including reef‐building stony coral—‘coral matrix’. Model performance improvements, chiefly by dataset cleaning, transfer learning and hyperparameter optimisation, resulted in the final trained model achieving validation accuracy of 98.19%. The classification was robust: benthic substrate types were accurately differentiated, and in some cases more consistently than was achieved by human annotators. Synthesis and applications. The availability of much larger volumes of automatically annotated image‐derived data will improve spatial management of impacts on coral‐based VMEs in the deep sea by (1) improved cross‐validation and performance of spatial models required to predict coral distribution and abundance over the large scales of managed areas, and (2) establishing empirical relationships between coral abundance on the seabed and coral bycatch landed during fishing operations.

The bonded area growth at diffusion bonding determined by the numerical modelling of Gleeble 3800 experiments and in comparison with the model by Hill and Wallach

Diffusion bonding or HIP (Hot Isostatic Pressing) is a common manufacturing process at several ITER components inside the Vacuum Vessel. The key uncertainties during diffusion bonding the unknown surface contaminations, remaining oxides. Diffusion bonding and reference tests were performed on specimens made from 316 L on a Gleeble 3800 Thermal-Mechanical Physical Simulation System. The contact electrical resistance on the bonded surfaces were determined in earlier work, where the decreasing contact electrical resistance predicted the increasing contact area during the welding process. Using the theoretical calculations to the electrical resistance of the surface asperities modelled by Zhang the bonded area growth was determined in time for the cylindrical specimens.A theoretical diffusion bonded model by Hill and Wallach was used to calculate the bonded area grow (a/b) on the examined tests. The results were comparable between the growth rate of (A/B) estimated by the Zhang model and bonded area growth by Hill and Wallach (a/b). The theoretical diffusion bonding models show much faster bonding, where the ideal model and the presumable re-oxidation of the surface gave the explanation to this phenomenon.

Uncertainty in aerosol–cloud radiative forcing is driven by clean conditions

Abstract. Atmospheric aerosols and their impact on cloud properties remain the largest uncertainty in the human forcing of the climate system. By increasing the concentration of cloud droplets (Nd), aerosols reduce droplet size and increase the reflectivity of clouds (a negative radiative forcing). Central to this climate impact is the susceptibility of cloud droplet number to aerosol (β), the diversity of which explains much of the variation in the radiative forcing from aerosol–cloud interactions (RFaci) in global climate models. This has made measuring β a key target for developing observational constraints of the aerosol forcing. While the aerosol burden of the clean, pre-industrial atmosphere has been demonstrated as a key uncertainty for the aerosol forcing, here we show that the behaviour of clouds under these clean conditions is of equal importance for understanding the spread in radiative forcing estimates between models and observations. This means that the uncertainty in the aerosol impact on clouds is, counterintuitively, driven by situations with little aerosol. Discarding clean conditions produces a close agreement between different model and observational estimates of the cloud response to aerosol but does not provide a strong constraint on the RFaci. This makes constraining aerosol behaviour in clean conditions an important goal for future observational studies.

Filling global gaps in monitoring data with local knowledge

Filling global gaps in monitoring data with local knowledge

The Mental Imagery for Suicidality in Students Trial (MISST): study protocol for a feasibility randomised controlled trial of broad-minded affective coping (BMAC) plus risk assessment and signposting versus risk assessment and signposting alone

BackgroundGoing to university is an important milestone in many people’s lives. It can also be a time of significant challenge and stress. There are growing concerns about mental health amongst student populations including suicide risk. Student mental health and counselling services have the potential to prevent suicide, but evidence-based therapies are required that fit these service contexts. The Broad-Minded Affective Coping intervention (BMAC) is a brief (6 sessions), positive imagery-based intervention that aims to enhance students access to past positive experiences and associated emotions and cognitions. Pilot data provides preliminary support for the BMAC for students struggling with suicidal thoughts and behaviours, but this intervention has not yet been evaluated in the context of a randomised controlled trial (RCT). The Mental Imagery for Suicidality in Students Trial (MISST) is a feasibility RCT that aims to determine the acceptability and feasibility of evaluating the BMAC as an intervention for university students at risk of suicide within a larger efficacy trial. Key feasibility uncertainties have been identified relating to recruitment, retention, and missing data. Intervention acceptability and safety will also be evaluated.MethodMISST is a feasibility randomised controlled trial design, with 1:1 allocation to risk assessment and signposting plus BMAC or risk assessment and signposting alone. Participants will be university students who self-report experiences of suicidal ideation or behaviour in the past 3 months. Assessments take place at baseline, 8, 16, and 24 weeks. The target sample size is 66 participants. A subset of up to 20 participants will be invited to take part in semi-structured qualitative interviews to obtain further data concerning the acceptability of the intervention.DiscussionThe BMAC intervention may provide an effective, brief talking therapy to help university students struggling with suicidal thoughts that could be readily implemented into university student counselling services. Depending on the results of MISST, the next step would be to undertake a larger-scale efficacy trial.Trial registrationThe trial was preregistered (17 December 2021) on ISRCTN (ISRCTN13621293) and ClinicalTrials.gov (NCT05296538).

Wood traits explain microbial but not termite‐driven decay in Australian tropical rainforest and savanna

Abstract Variation in decay rates across woody species is a key uncertainty in predicting the fate of carbon stored in deadwood, especially in the tropics. Quantifying the relative contributions of biotic decay agents, particularly microbes and termites, under different climates and across species with diverse wood traits could help explain this variation. To fill this knowledge gap, we deployed woody stems from 16 plant species native to either rainforest (n = 10) or savanna (n = 6) in northeast Australia, with and without termite access. For comparison, we also deployed standardized, non‐native pine blocks at both sites. We hypothesized that termites would increase rates of deadwood decay under conditions that limit microbial activity. Specifically, termite contributions to wood decay should be greater under dry conditions and in wood species with traits that constrain microbial decomposers. Termite discovery of stems was surprisingly low with only 17.6% and 22.6% of accessible native stems discovered in the rainforest and savanna respectively. Contrary to our hypothesis, stems discovered by termites decomposed faster only in the rainforest. Termites discovered and decayed pine blocks at higher rates than native stems in both the rainforest and savanna. We found significant variation in termite discovery and microbial decay rates across native wood species within the same site. Although wood traits explained 85% of the variation in microbial decay, they did not explain termite‐driven decay. For stems undiscovered by termites, decay rates were greater in species with higher wood nutrient concentrations and syringyl:guiacyl lignin ratios but lower carbon concentrations and wood densities. Synthesis. Ecosystem‐scale predictions of deadwood turnover and carbon storage should account for the impact of wood traits on decomposer communities. In tropical Australia, termite‐driven decay was lower than expected for native wood on the ground. Even if termites are present, they may not always increase decomposition rates of fallen native wood in tropical forests. Our study shows how the drivers of wood decay differ between Australian tropical rainforest and savanna; further research should test whether such differences apply world‐wide.

Cold-water habitats, climate refugia, and their utility for conserving salmonid fishes

Anthropogenic climate change is warming global temperatures, with significant implications for salmonid fishes that depend on the availability of cold water during one or more life stages. Along the southern range extents of many species, and elsewhere that warm temperatures are increasingly problematic, identification and protection or restoration of habitats that may serve as climate refugia where local populations can persist is emerging as an important conservation tactic. In this perspective piece, we address the concept and utility of climate refugia—drawing a distinction with the more commonly considered thermal refuges—describe technological advances that enable accurate temperature mapping and species distribution modeling in lotic environments, and outline key uncertainties and opportunities to chart a constructive path forward on a topic that will continue to grow in importance. Identifying climate refugia is not a panacea for salmonid conservation, but we argue that there are tangible benefits to doing so, not the least of which are the options it affords for thinking and acting strategically within the context of a changing climate this century.

Sediment dispersal and basin evolution during contrasting tectonic regimes along the western Gondwanan margin in the central Andes

A >15-20 km-thick succession in southern Bolivia forms the most-complete stratigraphic record in western Gondwana. Upper Neoproterozoic–Carboniferous clastic rocks record ∼300 Myr of marine, nonmarine, and glacially influenced sedimentation in diverse basin systems generated by variable tectonic regimes along the western edge of Gondwana during active and passive-margin conditions. New provenance results help resolve key uncertainties regarding source regions and sediment dispersal patterns. The findings are integrated with spatial variations in stratigraphic thicknesses to evaluate regional patterns of basin subsidence, magmatism, and deformation during long-term evolution of the western Gondwanan margin in the central Andes.Detrital zircon U–Pb geochronological data for 17 sandstone samples reveal sedimentary input from Precambrian cratonic basement provinces and pre-Andean basement, magmatic arc, and fold-thrust belt source regions. The basement age signatures indicate derivation from the flanking Brasiliano (900-560 Ma) and Pampean (650-500 Ma) provinces to the south and east, and the distal Rio de la Plata craton (2400-2000 Ma) along the eastern South American margin ∼1000–1500 km to the southeast. Although the greater Amazonian craton was not a major contributor, subordinate Amazonian signatures from the Sunsás (1300-950 Ma) province to the east and northeast selectively fed the northern basin regions of the central Andes. Despite the lack of Paleozoic igneous rocks in Bolivia, detrital zircons of Ordovician age attest to the pre-Andean influence of the subduction-related Famatinian magmatic arc. Limited Devonian-Carboniferous igneous material was contributed locally from western pre-Andean highlands or regionally by axial northward transport from selected igneous sources in Argentina and Chile. Episodic recycling of Neoproterozoic–Paleozoic basin fill, including a sharp reappearance of Famatinian-age detritus, can be linked to periods of Paleozoic crustal shortening and foreland sedimentation ascribed to Famatinian, Ocloyic, Chañic, or Gondwanide phases of deformation.The spatial distribution of sediment sources along with temporal shifts in sediment routing highlight several stages in the paleogeographic evolution of the western Gondwanan margin preserved in the central Andes. Initial regional subsidence spanned a multiphase Neoproterozoic to early Paleozoic history of Rodinia breakup, Brasiliano-Pampean orogenesis, and post-orogenic back-arc extension prior to final late Paleozoic amalgamation of Gondwana. The early Paleozoic onset of subduction and Famatinian arc magmatism led to high-magnitude subsidence (>10–15 km) likely driven by Ordovician slab rollback in an extensional back-arc basin. Thereafter, intermittent Paleozoic contraction in a poorly understood pre-Andean system (best expressed in the Eastern Cordillera of Bolivia and neighboring segments of northern Argentina and southern Peru) generated transient topographic loads that produced superimposed flexural foreland and successor basin systems.