Sea-level responses to rapid sediment erosion and deposition in Taiwan

Numerous studies have shown that sediment deposition can perturb sea level by several meters over millennial timescales by modifying the gravity field, crustal elevation, and sediment thickness. Relatively few studies have focused on the complementary role of erosion on sea-level change despite its effects on the same quantities, partly because many rapidly eroding mountains are too far from shorelines to strongly perturb sea level at the coast. Taiwan, a mountainous island eroding rapidly within tens of km of the coast, offers an opportunity to investigate the joint influences of rapid onshore erosion and rapid offshore deposition on sea-level change. Here we develop a sediment loading history for Taiwan since the previous interglacial (∼120 ka) by compiling published erosion and deposition rate measurements and by applying a geometric marine sediment deposition and compaction model for sites without deposition rate measurements. We use the resulting sediment redistribution history to drive sea-level responses in a gravitationally self-consistent sea-level model. Our simulations show that the effects of rapid onshore erosion outweigh the effects of rapid offshore deposition along Taiwan's east coast. Along the east coast of Taiwan, sediment redistribution induces rapid sea-level fall, a response that differs in sign from the coastal sea-level rise induced by rapid sediment redistribution in many other river systems around the world. The spatial extent of the modeled sea-level fall is sensitive to the Earth model, particularly the effective elastic thickness of the lithosphere, a sensitivity that we describe in further detail in the Discussion. These results suggest that sediment redistribution could have generated sea-level changes of >10m on the east coast of Taiwan since 10 ka and >100m since 120 ka. This can account for some of the discrepancy between observed and modeled paleo-sea-level marker elevations, which reduces estimates of tectonically driven rock uplift rates inferred from the elevation differences between paleo-sea-level markers and modeled sea level. This highlights the importance of accounting for erosional unloading in interpretations of paleo-sea-level reconstructions and associated estimates of tectonically driven uplift rates

Landslides on Ceres: Diversity and Geologic Context.

Landslides are among the most widespread geologic features on Ceres. Using data from Dawn's Framing Camera, landslides were previously classified based upon geomorphologic characteristics into one of three archetypal categories, Type 1(T1), Type 2 (T2), and Type 3 (T3). Due to their geologic context, variation in age, and physical characteristics, most landslides on Ceres are, however, intermediate in their morphology and physical properties between the archetypes of each landslide class. Here we describe the varied morphology of individual intermediate landslides, identify geologic controls that contribute to this variation, and provide first-order quantification of the physical properties of the continuum of Ceres's surface flows. These intermediate flows appear in varied settings and show a range of characteristics, including those found at contacts between craters, those having multiple trunks or lobes; showing characteristics of both T2 and T3 landslides; material slumping on crater rims; very small, ejecta-like flows; and those appearing inside of catenae. We suggest that while their morphologies can vary, the distribution and mechanical properties of intermediate landslides do not differ significantly from that of archetypal landslides, confirming a link between landslides and subsurface ice. We also find that most intermediate landslides are similar to Type 2 landslides and formed by shallow failure. Clusters of these features suggest ice enhancement near Juling, Kupalo and Urvara craters. Since the majority of Ceres's landslides fall in the intermediate landslide category, placing their attributes in context contributes to a better understanding of Ceres's shallow subsurface and the nature of ground ice

Quantifying erosion rates and weathering pathways that maximize soil organic carbon storage

Primary minerals that enter soils through bedrock weathering and atmospheric deposition can generate poorly crystalline minerals (PCM) that preferentially associate with soil organic carbon (SOC). These associations hinder microbial decomposition and the release of CO₂ from soils to the atmosphere, making them a critical geochemical control on terrestrial carbon abundance and persistence. Studies that explore these relationships are typically derived from soil chronosequences that experience negligible erosion and thus do not readily translate to eroding landscapes. Here, we propose a theoretical framework to estimate steady-state PCM density and stocks for hilly and mountainous settings by coupling geochemical and geomorphic mass balance equations that account for soil production from bedrock and dust, soil erosion, PCM formation from weathering, and the transformation of PCMs into crystalline phases. We calculate an optimal erosion rate for maximum PCM abundance that arises because PCMs are limited by insufficient weathering at faster erosion rates and loss via “ripening” into more crystalline forms at slower erosion rates. The optimal erosion rate for modeled hilltop soil is modulated by reaction rate constants that govern the efficiency of primary mineral weathering and PCM ripening. By comparing our analysis with global compilations of erosion and soil production rates derived from cosmogenic nuclides, we show that landscapes with slow-to-moderate erosion rates may be optimal for harboring abundant PCM stocks that can facilitate SOC sequestration and limit turnover. Given the growing array of erosion-topography metrics and the widespread availability of high-resolution topographic data, our framework demonstrates how weathering and critical zone processes can be coupled to inform landscape prioritization for persistent SOC storage potential across a broad range of spatial and temporal scales

Characterising and Predicting Benthic Biodiversity for Conservation Planning in Deepwater Environments

Understanding patterns of biodiversity in deep sea systems is increasingly important because human activities are extending further into these areas. However, obtaining data is difficult, limiting the ability of science to inform management decisions. We have used three different methods of quantifying biodiversity to describe patterns of biodiversity in an area that includes two marine reserves in deep water off southern Australia. We used biological data collected during a recent survey, combined with extensive physical data to model, predict and map three different attributes of biodiversity: distributions of common species, beta diversity and rank abundance distributions (RAD). The distribution of each of eight common species was unique, although all the species respond to a depth-correlated physical gradient. Changes in composition (beta diversity) were large, even between sites with very similar environmental conditions. Composition at any one site was highly uncertain, and the suite of species changed dramatically both across and down slope. In contrast, the distributions of the RAD components of biodiversity (community abundance, richness, and evenness) were relatively smooth across the study area, suggesting that assemblage structure (i.e. the distribution of abundances of species) is limited, irrespective of species composition. Seamounts had similar biodiversity based on metrics of species presence, beta diversity, total abundance, richness and evenness to the adjacent continental slope in the same depth ranges. These analyses suggest that conservation objectives need to clearly identify which aspects of biodiversity are valued, and employ an appropriate suite of methods to address these aspects, to ensure that conservation goals are met

Characterisation of Genome-Wide PLZF/RARA Target Genes

The PLZF/RARA fusion protein generated by the t(11;17)(q23;q21) translocation in acute promyelocytic leukaemia (APL) is believed to act as an oncogenic transcriptional regulator recruiting epigenetic factors to genes important for its transforming potential. However, molecular mechanisms associated with PLZF/RARA-dependent leukaemogenesis still remain unclear

Utilizing individual fish biomass and relative abundance models to map environmental niche associations of adult and juvenile targeted fishes

Many fishes undergo ontogenetic habitat shifts to meet their energy and resource needs as they grow. Habitat resource partitioning and patterns of habitat connectivity between conspecific fishes at different life-history stages is a significant knowledge gap. Species distribution models were used to examine patterns in the relative abundance, individual biomass estimates and environmental niche associations of different life stages of three iconic West Australian fishes. Continuous predictive maps describing the spatial distribution of abundance and individual biomass of the study species were created as well predictive hotspot maps that identify possible areas for aggregation of individuals of similar life stages of multiple species (i.e. spawning grounds, fisheries refugia or nursery areas). The models and maps indicate that processes driving the abundance patterns could be different from the body size associated demographic processes throughout an individual's life cycle. Incorporating life-history in the spatially explicit management plans can ensure that critical habitat of the vulnerable stages (e.g. juvenile fish, spawning stock) is included within proposed protected areas and can enhance connectivity between various functional areas (e.g. nursery areas and adult populations) which, in turn, can improve the abundance of targeted species as well as other fish species relying on healthy ecosystem functioning

Cognitive Control Reflects Context Monitoring, Not Motoric Stopping, in Response Inhibition

The inhibition of unwanted behaviors is considered an effortful and controlled ability. However, inhibition also requires the detection of contexts indicating that old behaviors may be inappropriate – in other words, inhibition requires the ability to monitor context in the service of goals, which we refer to as context-monitoring. Using behavioral, neuroimaging, electrophysiological and computational approaches, we tested whether motoric stopping per se is the cognitively-controlled process supporting response inhibition, or whether context-monitoring may fill this role. Our results demonstrate that inhibition does not require control mechanisms beyond those involved in context-monitoring, and that such control mechanisms are the same regardless of stopping demands. These results challenge dominant accounts of inhibitory control, which posit that motoric stopping is the cognitively-controlled process of response inhibition, and clarify emerging debates on the frontal substrates of response inhibition by replacing the centrality of controlled mechanisms for motoric stopping with context-monitoring

Effects of acute tryptophan depletion on executive function in healthy male volunteers

BACKGROUND: Neurocognitive impairment is frequently described in a number of psychiatric disorders and may be a direct consequence of serotonergic dysfunction. As impairments in executive functions are some of the most frequently described, the purpose of this study was to examine the performance of normal volunteers on a range of executive tasks following a transient reduction of central serotonin (5-HT) levels using the method of acute tryptophan depletion (ATD). METHODS: Fifteen healthy male subjects participated in a within-subject, double-blind, counterbalanced crossover study. ATD was induced by ingestion of a 100 g amino-acid drink. Executive function was evaluated using the Wisconsin Card Sorting Test, Stroop, Verbal Fluency and Trail Making. Visual analogue scales were administered to assess mood. RESULTS: Plasma free and total tryptophan concentrations were significantly reduced by the depleting drink (P < 0.001). ATD selectively improved motor speed/ attention on the Trails A test (P = 0.027), with no effect on subjective ratings of mood. Interaction effects between drink and the order of drink administration were observed on most neurocognitive tests. CONCLUSIONS: The improvement in simple motor speed/ attention following ATD is in keeping with the ascribed role of 5-HT in the cortex, however performance on tests of executive function is not robustly altered. The presence of interaction effects on most tasks suggests that subtle changes may occur but are masked, possibly by simple learning effects, in the context of a crossover design. This has implications for the design of future studies, particularly those examining executive functions

Virulence in Murine Model Shows the Existence of Two Distinct Populations of Brazilian Vaccinia virus Strains

Brazilian Vaccinia virus had been isolated from sentinel mice, rodents and recently from humans, cows and calves during outbreaks on dairy farms in several rural areas in Brazil, leading to high economic and social impact. Some phylogenetic studies have demonstrated the existence of two different populations of Brazilian Vaccinia virus strains circulating in nature, but little is known about their biological characteristics. Therefore, our goal was to study the virulence pattern of seven Brazilian Vaccinia virus strains. Infected BALB/c mice were monitored for morbidity, mortality and viral replication in organs as trachea, lungs, heart, kidneys, liver, brain and spleen. Based on the virulence potential, the Brazilian Vaccinia virus strains were grouped into two groups. One group contained GP1V, VBH, SAV and BAV which caused disease and death in infected mice and the second one included ARAV, GP2V and PSTV which did not cause any clinical signals or death in infected BALB/c mice. The subdivision of Brazilian Vaccinia virus strains into two groups is in agreement with previous genetic studies. Those data reinforce the existence of different populations circulating in Brazil regarding the genetic and virulence characteristics

Models of marine fish biodiversity : assessing predictors from three habitat classification schemes

Prioritising biodiversity conservation requires knowledge of where biodiversity occurs. Such knowledge, however, is often lacking. New technologies for collecting biological and physical data coupled with advances in modelling techniques could help address these gaps and facilitate improved management outcomes. Here we examined the utility of environmental data, obtained using different methods, for developing models of both uni- and multivariate biodiversity metrics. We tested which biodiversity metrics could be predicted best and evaluated the performance of predictor variables generated from three types of habitat data: acoustic multibeam sonar imagery, predicted habitat classification, and direct observer habitat classification. We used boosted regression trees (BRT) to model metrics of fish species richness, abundance and biomass, and multivariate regression trees (MRT) to model biomass and abundance of fish functional groups. We compared model performance using different sets of predictors and estimated the relative influence of individual predictors. Models of total species richness and total abundance performed best; those developed for endemic species performed worst. Abundance models performed substantially better than corresponding biomass models. In general, BRT and MRTs developed using predicted habitat classifications performed less well than those using multibeam data. The most influential individual predictor was the abiotic categorical variable from direct observer habitat classification and models that incorporated predictors from direct observer habitat classification consistently outperformed those that did not. Our results show that while remotely sensed data can offer considerable utility for predictive modeling, the addition of direct observer habitat classification data can substantially improve model performance. Thus it appears that there are aspects of marine habitats that are important for modeling metrics of fish biodiversity that are not fully captured by remotely sensed data. As such, the use of remotely sensed data to model biodiversity represents a compromise between model performance and data availability