Mapping mean total annual precipitation in Belgium, by investigating the scale of topographic control at the regional scale

Accurate precipitation maps are essential for ecological, environmental, element cycle and hydrological models that have a spatial output component. It is well known that topography has a major influence on the spatial distribution of precipitation and that increasing topographical complexity is associated with increased spatial heterogeneity in precipitation. This means that when mapping precipitation using classical interpolation techniques (e.g. regression, kriging, spline, inverse distance weighting, etc.), a climate measuring network with higher spatial density is needed in mountainous areas in order to obtain the same level of accuracy as compared to flatter regions. In this study, we present a mean total annual precipitation mapping technique that combines topographical information (i.e. elevation and slope orientation) with average total annual rain gauge data in order to overcome this problem. A unique feature of this paper is the identification of the scale at which topography influences the precipitation pattern as well as the direction of the dominant weather circulation. This method was applied for Belgium and surroundings and shows that the identification of the appropriate scale at which topographical obstacles impact precipitation is crucial in order to obtain reliable mean total annual precipitation maps. The dominant weather circulation is determined at 260°. Hence, this approach allows accurate mapping of mean annual precipitation patterns in regions characterized by rather high topographical complexity using a climate data network with a relatively low density and/or when more advanced precipitation measurement techniques, such as radar, aren't available, for example in the case of historical data

Tracing of particulate organic C sources across the terrestrial-aquatic continuum, a case study at the catchment scale (Carminowe Creek, southwest England)

Soils deliver crucial ecosystem services, such as climate regulation through carbon (C) storage and food security, both of which are threatened by climate and land use change. While soils are important stores of terrestrial C, anthropogenic impact on the lateral fluxes of C from land to water remains poorly quantified and not well represented in Earth system models. In this study, we tested a novel framework for tracing and quantifying lateral C fluxes from the terrestrial to the aquatic environment at a catchment scale. The combined use of conservative plant-derived geochemical biomarkers n-alkanes and bulk stable δ13C and δ15N isotopes of soils and sediments allowed us to distinguish between particulate organic C sources from different land uses (i.e. arable and temporary grassland vs. permanent grassland vs. riparian woodland vs. river bed sediments) (p < 0.001), showing an enhanced ability to distinguish between land use sources as compared to using just n-alkanes alone. The terrestrial-aquatic proxy (TAR) ratio derived from n-alkane signatures indicated an increased input of terrestrial-derived organic matter (OM) to lake sediments over the past 60 years, with an increasing contribution of woody vegetation shown by the C27/C31 ratio. This may be related to agricultural intensification, leading to enhanced soil erosion, but also an increase in riparian woodland that may disconnect OM inputs from arable land uses in the upper parts of the study catchment. Spatial variability of geochemical proxies showed a close coupling between OM provenance and riparian land use, supporting the new conceptualization of river corridors (active river channel and riparian zone) as critical zones linking the terrestrial and aquatic C fluxes. Further testing of this novel tracing technique shows promise in terms of quantification of lateral C fluxes as well as targeting of effective land management measures to reduce soil erosion and promote OM conservation in river catchments

Global change pressures on soils from land use and management

Soils are subject to varying degrees of direct or indirect human disturbance, constituting a major global change driver. Factoring out natural from direct and indirect human influence is not always straightforward, but some human activities have clear impacts. These include land-use change, land management and land degradation (erosion, compaction, sealing and salinization). The intensity of land use also exerts a great impact on soils, and soils are also subject to indirect impacts arising from human activity, such as acid deposition (sulphur and nitrogen) and heavy metal pollution. In this critical review, we report the state-of-the-art understanding of these global change pressures on soils, identify knowledge gaps and research challenges and highlight actions and policies to minimize adverse environmental impacts arising from these global change drivers. Soils are central to considerations of what constitutes sustainable intensification. Therefore, ensuring that vulnerable and high environmental value soils are considered when protecting important habitats and ecosystems, will help to reduce the pressure on land from global change drivers. To ensure that soils are protected as part of wider environmental efforts, a global soil resilience programme should be considered, to monitor, recover or sustain soil fertility and function, and to enhance the ecosystem services provided by soils. Soils cannot, and should not, be considered in isolation of the ecosystems that they underpin and vice versa. The role of soils in supporting ecosystems and natural capital needs greater recognition. The lasting legacy of the International Year of Soils in 2015 should be to put soils at the centre of policy supporting environmental protection and sustainable development

Discovery and validation of plasma proteomic biomarkers relating to brain amyloid burden by SOMAscan assay.

Plasma proteins have been widely studied as candidate biomarkers to predict brain amyloid deposition to increase recruitment efficiency in secondary prevention clinical trials for Alzheimer's disease. Most such biomarker studies are targeted to specific proteins or are biased toward high abundant proteins. 4001 plasma proteins were measured in two groups of participants (discovery group = 516, replication group = 365) selected from the European Medical Information Framework for Alzheimer's disease Multimodal Biomarker Discovery study, all of whom had measures of amyloid. A panel of proteins (n = 44), along with age and apolipoprotein E (APOE) ε4, predicted brain amyloid deposition with good performance in both the discovery group (area under the curve = 0.78) and the replication group (area under the curve = 0.68). Furthermore, a causal relationship between amyloid and tau was confirmed by Mendelian randomization. The results suggest that high-dimensional plasma protein testing could be a useful and reproducible approach for measuring brain amyloid deposition

Dickkopf-1 Overexpression in vitro Nominates Candidate Blood Biomarkers Relating to Alzheimer's Disease Pathology

BACKGROUND: Previous studies suggest that Dickkopf-1 (DKK1), an inhibitor of Wnt signaling, plays a role in amyloid-induced toxicity and hence Alzheimer's disease (AD). However, the effect of DKK1 expression on protein expression, and whether such proteins are altered in disease, is unknown. OBJECTIVE: We aim to test whether DKK1 induced protein signature obtained in vitro were associated with markers of AD pathology as used in the amyloid/tau/neurodegeneration (ATN) framework as well as with clinical outcomes. METHODS: We first overexpressed DKK1 in HEK293A cells and quantified 1,128 proteins in cell lysates using aptamer capture arrays (SomaScan) to obtain a protein signature induced by DKK1. We then used the same assay to measure the DKK1-signature proteins in human plasma in two large cohorts, EMIF (n = 785) and ANM (n = 677). RESULTS: We identified a 100-protein signature induced by DKK1 in vitro. Subsets of proteins, along with age and apolipoprotein E ɛ4 genotype distinguished amyloid pathology (A + T-N-, A+T+N-, A+T-N+, and A+T+N+) from no AD pathology (A-T-N-) with an area under the curve of 0.72, 0.81, 0.88, and 0.85, respectively. Furthermore, we found that some signature proteins (e.g., Complement C3 and albumin) were associated with cognitive score and AD diagnosis in both cohorts. CONCLUSIONS: Our results add further evidence for a role of DKK regulation of Wnt signaling in AD and suggest that DKK1 induced signature proteins obtained in vitro could reflect theATNframework as well as predict disease severity and progression in vivo

Inflammatory biomarkers in Alzheimer&apos;s disease plasma

Introduction: Plasma biomarkers for Alzheimer's disease (AD) diagnosis/stratification are a \u201cHoly Grail\u201d of AD research and intensively sought; however, there are no well-established plasma markers. Methods: A hypothesis-led plasma biomarker search was conducted in the context of international multicenter studies. The discovery phase measured 53 inflammatory proteins in elderly control (CTL; 259), mild cognitive impairment (MCI; 199), and AD (262) subjects from AddNeuroMed. Results: Ten analytes showed significant intergroup differences. Logistic regression identified five (FB, FH, sCR1, MCP-1, eotaxin-1) that, age/APO\u3b54 adjusted, optimally differentiated AD and CTL (AUC: 0.79), and three (sCR1, MCP-1, eotaxin-1) that optimally differentiated AD and MCI (AUC: 0.74). These models replicated in an independent cohort (EMIF; AUC 0.81 and 0.67). Two analytes (FB, FH) plus age predicted MCI progression to AD (AUC: 0.71). Discussion: Plasma markers of inflammation and complement dysregulation support diagnosis and outcome prediction in AD and MCI. Further replication is needed before clinical translation

Inflammatory biomarkers in Alzheimer's disease plasma.

Plasma biomarkers for Alzheimer's disease (AD) diagnosis/stratification are a "Holy Grail" of AD research and intensively sought; however, there are no well-established plasma markers. A hypothesis-led plasma biomarker search was conducted in the context of international multicenter studies. The discovery phase measured 53 inflammatory proteins in elderly control (CTL; 259), mild cognitive impairment (MCI; 199), and AD (262) subjects from AddNeuroMed. Ten analytes showed significant intergroup differences. Logistic regression identified five (FB, FH, sCR1, MCP-1, eotaxin-1) that, age/APOε4 adjusted, optimally differentiated AD and CTL (AUC: 0.79), and three (sCR1, MCP-1, eotaxin-1) that optimally differentiated AD and MCI (AUC: 0.74). These models replicated in an independent cohort (EMIF; AUC 0.81 and 0.67). Two analytes (FB, FH) plus age predicted MCI progression to AD (AUC: 0.71). Plasma markers of inflammation and complement dysregulation support diagnosis and outcome prediction in AD and MCI. Further replication is needed before clinical translation

Inflammatory biomarkers in Alzheimer's disease plasma

Introduction: Plasma biomarkers for Alzheimer's disease (AD)diagnosis/stratification are a “Holy Grail” of AD research and intensively sought; however, there are no well-established plasma markers. Methods: A hypothesis-led plasma biomarker search was conducted in the context of international multicenter studies. The discovery phase measured 53 inflammatory proteins in elderly control (CTL; 259), mild cognitive impairment (MCI; 199), and AD (262)subjects from AddNeuroMed. Results: Ten analytes showed significant intergroup differences. Logistic regression identified five (FB, FH, sCR1, MCP-1, eotaxin-1)that, age/APOε4 adjusted, optimally differentiated AD and CTL (AUC: 0.79), and three (sCR1, MCP-1, eotaxin-1)that optimally differentiated AD and MCI (AUC: 0.74). These models replicated in an independent cohort (EMIF; AUC 0.81 and 0.67). Two analytes (FB, FH)plus age predicted MCI progression to AD (AUC: 0.71). Discussion: Plasma markers of inflammation and complement dysregulation support diagnosis and outcome prediction in AD and MCI. Further replication is needed before clinical translation

Spatial variability and change in soil organic carbon stocks in response to recovery following land abandonment and erosion in mountainous drylands

This research investigates the impact of human activities on carbon (C) dynamics in a mountainous and semi-arid environment. Despite the low C status of drylands, soil organic carbon (SOC) is the largest C pool in these systems and therefore may offer significant C sequestration potential in systems recovering from degradation. Nevertheless, quantification of this potential is limited by lack of knowledge concerning the magnitude of and controls on regional SOC stocks. Therefore, this study aimed to (i) investigate the variability of soil organic carbon in relation to recovery period and key soil and topographical variables, and (ii) quantify the effects of recovery period following abandonment on SOC stocks. Soil profiles were sampled in the Sierra de los Filabres (southeast Spain) in different land units along geomorphic and degradation gradients. SOC contents were modelled using recovery period and soil and topographical variables. Sample depth, topographic position, altitude, recovery period and stone content were identified as the main factors for predicting SOC concentrations. SOC stocks in 1 m depth of soil varied between 3.16 and 76.44 t/ha. Recovery period (years since abandonment), topographic position and altitude were used to predict and map SOC stocks in the top 0.2 m. The results show that C accumulates rapidly during the first 10-50 yr following abandonment; thereafter, the stocks evolve towards a steady-state level. The erosion zones in the study area demonstrate greater potential to increase their SOC stocks when abandoned. Deposition zones have greater SOC values, although their C accumulation rate is lower compared with erosional landscapes in the first 10-50 yr following abandonment. Therefore, full understanding of the C sequestration potential of land use change in areas of complex topography requires knowledge of spatial variability in soil properties and in particular SOC. © 2012 The Authors. Journal compilation © 2012 British Society of Soil Science

Lignin signature as a function of land abandonment and erosion in dry luvisols of SE Spain

This study addressed long-term land degradation and regeneration effects on soil organic carbon (SOC) composition. Thiswas done in a context of secondary succession following land abandonment in theMediterranean region of SE Spain. The effects of land use change and soil erosion on SOC composition were studied by using lignin as a biomarker. To get insight into the evolution of SOC composition along a land use and topographical gradient, differences in lignin contribution to SOC were determined at different soil depths (0–0.1m, 0.1–0.2 m, 0.2–0.3m). Three deposition locations, three positions on the hillslope and three zones on top of the hillslope (shoulder) were selected on croplands and fields that were abandoned since 10 and 50 years, respectively. Land use change was identified as a driver for the observed gradients in lignin, SOC and N in these semi-arid ecosystems. Abandoned sites were highest in soil lignin, which could be related to the higher lignin input. For deposition and shoulder positions lignin was less degraded at abandoned sites compared to cultivated sites. On croplands lignin was more degraded at hillslope locations compared to deposition zones. Observed differences in soil lignin quantity were highest for the topsoil (0–0.1 m). For deeper soil, differences are less pronounced. However, no differences were evident for lignin contribution to SOC (mg lignin phenols/g SOC). As modern soil erosion rates are very low in the study area, SOC composition on abandoned fields may be more influenced by present day vegetation and its degradation than by soil erosion. Surprisingly, lignin contribution to SOC was not favored by vegetation recovery either. The higher soil N contents for abandoned fields compared to croplands might explain why lignin is not preferentially preserved on recovered sites