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Funding: Data collection was largely funded by the UK Natural Environment Research Council (NERC) project TREMOR (NE/N004655/1) to D.G., E.G. and O.P., with further funds from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES, finance code 001) to J.V.T. and a University of Leeds Climate Research Bursary Fund to J.V.T. D.G., E.G. and O.P. acknowledge further support from a NERC-funded consortium award (ARBOLES, NE/S011811/1). This paper is an outcome of J.V.T.’s doctoral thesis, which was sponsored by CAPES (GDE 99999.001293/2015-00). J.V.T. was previously supported by the NERC-funded ARBOLES project (NE/S011811/1) and is supported at present by the Swedish Research Council Vetenskapsrådet (grant no. 2019-03758 to R.M.). E.G., O.P. and D.G. acknowledge support from NERC-funded BIORED grant (NE/N012542/1). O.P. acknowledges support from an ERC Advanced Grant and a Royal Society Wolfson Research Merit Award. R.S.O. was supported by a CNPq productivity scholarship, the São Paulo Research Foundation (FAPESP-Microsoft 11/52072-0) and the US Department of Energy, project GoAmazon (FAPESP 2013/50531-2). M.M. acknowledges support from MINECO FUN2FUN (CGL2013-46808-R) and DRESS (CGL2017-89149-C2-1-R). C.S.-M., F.B.V. and P.R.L.B. were financed by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES, finance code 001). C.S.-M. received a scholarship from the Brazilian National Council for Scientific and Technological Development (CNPq 140353/2017-8) and CAPES (science without borders 88881.135316/2016-01). Y.M. acknowledges the Gordon and Betty Moore Foundation and ERC Advanced Investigator Grant (GEM-TRAITS, 321131) for supporting the Global Ecosystems Monitoring (GEM) network (gem.tropicalforests.ox.ac.uk), within which some of the field sites (KEN, TAM and ALP) are nested. The authors thank Brazil–USA Collaborative Research GoAmazon DOE-FAPESP-FAPEAM (FAPESP 2013/50533-5 to L.A.) and National Science Foundation (award DEB-1753973 to L. Alves). They thank Serrapilheira Serra-1709-18983 (to M.H.) and CNPq-PELD/POPA-441443/2016-8 (to L.G.) (P.I. Albertina Lima). They thank all the colleagues and grants mentioned elsewhere [8,36] that established, identified and measured the Amazon forest plots in the RAINFOR network analysed here. The authors particularly thank J. Lyod, S. Almeida, F. Brown, B. Vicenti, N. Silva and L. Alves. This work is an outcome approved Research Project no. 19 from ForestPlots.net, a collaborative initiative developed at the University of Leeds that unites researchers and the monitoring of their permanent plots from the world’s tropical forests [61]. The authros thank A. Levesley, K. Melgaço Ladvocat and G. Pickavance for ForestPlots.net management. They thank Y. Wang and J. Baker, respectively, for their help with the map and with the climatic data. The authors acknowledge the invaluable help of M. Brum for kindly providing the comparison of vulnerability curves based on PAD and on PLC shown in this manuscript. They thank J. Martinez-Vilalta for his comments on an early version of this manuscript. The authors also thank V. Hilares and the Asociación para la Investigación y Desarrollo Integral (AIDER, Puerto Maldonado, Peru); V. Saldaña and Instituto de Investigaciones de la Amazonía Peruana (IIAP) for local field campaign support in Peru; E. Chavez and Noel Kempff Natural History Museum for local field campaign support in Bolivia; ICMBio, INPA/NAPPA/LBA COOMFLONA (Cooperativa mista da Flona Tapajós) and T. I. Bragança-Marituba for the research support. Tropical forests face increasing climate risk1,2, yet our ability to predict their response to climate change is limited by poor understanding of their resistance to water stress. Although xylem embolism resistance thresholds (for example, Ψ50) and hydraulic safety margins (for example, HSM50) are important predictors of drought-induced mortality risk3-5, little is known about how these vary across Earth's largest tropical forest. Here, we present a pan-Amazon, fully standardized hydraulic traits dataset and use it to assess regional variation in drought sensitivity and hydraulic trait ability to predict species distributions and long-term forest biomass accumulation. Parameters Ψ50 and HSM50 vary markedly across the Amazon and are related to average long-term rainfall characteristics. Both Ψ50 and HSM50 influence the biogeographical distribution of Amazon tree species. However, HSM50 was the only significant predictor of observed decadal-scale changes in forest biomass. Old-growth forests with wide HSM50 are gaining more biomass than are low HSM50 forests. We propose that this may be associated with a growth-mortality trade-off whereby trees in forests consisting of fast-growing species take greater hydraulic risks and face greater mortality risk. Moreover, in regions of more pronounced climatic change, we find evidence that forests are losing biomass, suggesting that species in these regions may be operating beyond their hydraulic limits. Continued climate change is likely to further reduce HSM50 in the Amazon6,7, with strong implications for the Amazon carbon sink. Publisher PDF

Dementia with Lewy bodies (DLB) is clinically defined by the presence of visual hallucinations, fluctuations, rapid eye movement (REM) sleep behavioral disorder, and parkinsonism. Neuropathologically, it is characterized by the presence of Lewy pathology. However, neuropathological studies have demonstrated the high prevalence of coexistent Alzheimer's disease, TAR DNA-binding protein 43 (TDP-43), and cerebrovascular pathologic cases. Due to their high prevalence and clinical impact on DLB individuals, clinical trials should account for these co-pathologies in their design and selection and the interpretation of biomarkers values and outcomes. Here we discuss the frequency of the different co-pathologies in DLB and their cross-sectional and longitudinal clinical impact. We then evaluate the utility and possible applications of disease-specific and disease-nonspecific biomarkers and how co-pathologies can impact these biomarkers. We propose a framework for integrating multi-modal biomarker fingerprints and step-wise selection and assessment of DLB individuals for clinical trials, monitoring target engagement, and interpreting outcomes in the setting of co-pathologies.

The Cuvette Centrale wetland area in the central Congo Basin is home to the most extensive peatland complex in the tropics, which covers an estimated 167,600 km2 and stores approximately 29.0 petagrams of carbon belowground (Crezee et al., 2022). However, relatively little is known about these peat swamp forests, which span both the Republic of the Congo (ROC) and the Democratic Republic of the Congo (DRC). In ROC, peatlands are mostly found in interfluvial basins, where they form wide but shallow peat domes (Davenport et al., 2020), which are largely rain-fed, have ombrotrophic (low-nutrient) status and are covered by distinct hardwood- or palm-dominated forest vegetation types (Dargie et al., 2017). In contrast, peatlands in DRC can be found in different hydro-geomorphological settings, including relatively narrow river valleys along the Congo River’s eastern tributaries.Here, we present insights from in situ measurements of water table depths, peat and water chemistry, and vegetation characteristics along three of these tributaries, the Ruki, Busira and Ikelemba Rivers. Peat deposits (≥ 30 cm of ≥ 65% organic matter) were found in seasonally inundated swamp forests close to rivers, which are characterised by large (>1 m) wet season inundations. This shows that peat formation in the central Congo Basin is not only confined to permanently waterlogged swamps with relatively stable water tables year-round, predominating in ROC’s interfluvial basins, but also occurs in swamp forests that experience greater water table seasonality. Seasonal inundations are due to riverbank overflow during the wet season, and potentially upland runoff from higher terra firme ground. Since the Congo River’s eastern tributaries are highly acidic (blackwater) rivers, the seasonally inundated, river-fed swamps are still of low nutrient status, allowing peat to form. Nonetheless, they are typically characterised by shallower peat deposits than permanently waterlogged swamp forests. Comparison of vegetation plot data identifies a distinct forest type in the seasonally inundated, river-fed peat swamps: a hardwood swamp forest dominated by Oubanguia africana and Guibourtia demeusei. This vegetation type was previously described by Evrard (1968), but was not known to overlie peat soils.Our findings identify distinct rain-fed and river-fed peatlands in the central Congo Basin. These two peatland types may face different threats to their integrity. While rain-fed peatlands will be susceptible to future climate change if rainfall levels decrease, those that are also maintained by riverbank overflow, may be susceptible to changes in upstream rainfall patterns. This, as well as infrastructure projects that affect river dynamics, will likely have larger impacts on peatland functioning than previously thought.

The Cuvette Centrale peatland complex is one of the world’s most important carbon stores, and spans the Republic of Congo and Democratic Republic of Congo, storing approximately 30.6 Pg C. However, despite significant carbon storage, the role of environmental controls over the production and emission of greenhouse gases including carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) remain poorly understood, and in situ flux measurements were only undertaken for the first time in 2019. This hampers our ability to understand the likely responses of emissions to future environmental change.We conducted an ex-situ incubation experiment to investigate the roles of inundation and oxygen availability (flooded aerobic, flooded anoxic, and mesic conditions), vegetation type (palm versus hardwood dominated peat swamp). We concurrently assessed the role of vegetation in regulating peat organic chemistry using a combination of Fourier Transformed Infrared Spectroscopy (FTIR) and Rock-Eval Pyrolysis, and used regression models to assess controls over potential greenhouse gas production.We found that CO2 fluxes were consistently highest across sites under mesic conditions, and flooded anoxic conditions were associated with lowest fluxes. CH4 production were highest under anoxic conditions, followed by the flooded oxic and the mesic treatments. Inundation and oxygen availability had more variable impacts on N2O production. CO2 fluxes were greatest from hardwood and mixed forest for the mesic and flooded oxic treatments, and the highest anoxic CO2 fluxes were from the mixed forest. The were no significant differences in CH4 fluxes among the three vegetation types for any of the treatments. N2O fluxes were greatest from the hardwood sites under the mesic treatment but there were no significant differences among forest types for the flooded aerobic and anoxic treatments.We used regression models to link a range of peat inorganic and organic chemical properties across flooding treatments to greenhouse gas production, highlighting important potential controls over emissions. We concurrently assessed changes in emissions with peat depth (0 – 1.7 m), identifying broad declines in potential production with peat depth, matched by concurrent changes in organic chemistry.Taken together our results indicate that the inundation represents a key control over emissions, alongside peat organic chemistry, which in turn is closely related to dominant vegetation type which controls inputs. Collectively these findings imply that any changes in peatland inundation through future climate change or alterations in land management (for example drainage) will have significant implications for greenhouse gas fluxes. Moreover, changes in dominant vegetation or ecosystem productivity will alter the balance of plant inputs into the peat, with subsequent implications for greenhouse gas dynamics.

One-dimensional semiconductor-metal heterostructures manifest improved charge separation capability, tunable band gap and increased surface area, and have been regarded as promising photocatalysts for solar-to-fuel conversion through water splitting. We herein review the synthetic strategies for the rational design and preparation of one-dimensional semiconductor-metal heterostructures with precise control in terms of size, shape, composition and function. Approaches that are capable of improving the photocatalytic performance of one-dimensional semiconductor-metal heterostructures have been proposed and analyzed The present work is expected to give the rational design of one-dimensional semiconductor-metal heterostructures and provide insights into accomplishing highly efficient photocatalysis based on such materials

In a 1683 sermon, Benjamin Calamy, an Anglican priest, claimed that the separation of Dissenters from the Church of England was unjustifiable. Thomas Delaune, a London Baptist schoolmaster, responded in A Plea for the Non-Conformists (1684), which compared seventeenth-century Dissenters to sixteenth-century Reformers who had escaped from the “Church of Rome.” The Restoration authorities judged the book to be a seditious libel, for which Delaune was arrested, tried, and imprisoned in Newgate, where he was soon joined by his poverty-stricken wife and two children. By 1685, the whole family had perished in Newgate. This tragic story guaranteed Delaune's status as a martyr for generations of Nonconformists. Indeed, the Plea achieved amongst Dissenters the reputation of an “unanswerable” text. Its enduring appeal transcended denominational and geographical boundaries. This paper explores the eighteenth- and nineteenth-century reception of the Plea, which Dissenters, both in England and America, repurposed for various politico-theological circumstances. Throughout the eighteenth century, Dissenters invoked the Plea against perceived cases of episcopal tyranny. By the pluralistic nineteenth century, however, this external, episcopal threat had largely been replaced with an internal one, prompting Dissenters to deploy the Plea against corruption and lethargy within their own denominations.

A multimodal analytical sequence in combination with chemometrics was applied to a blinded case simulation to showcase its suitability for use within the context of forensic casework involving arid, sandy soils low in clay and organic matter. Using microspectrophotometry, attenuated total reflectance Fourier-transform infrared spectroscopy and X-ray diffraction, in combination with principal component analysis and linear discriminant analysis, an unknown “recovered” sample was able to be associated with a single reference soil and discriminated from the other soils. The spectroscopic techniques employed produced varying results, however, these results offered complementary information that was able to be interpreted collectively to discriminate between the reference soils and identify the source of the “recovered” soil with greater confidence. The use of chemometric methods to interpret the data provided an objective, statistical measure of the similarities and/or variation between samples that could be presented as weighting for evidence in court. Hence, this approach was deemed suitable for incorporation into forensic casework to provide discrimination between similar sandy soil samples in an objective manner.