Dynamics of Small-scale topographic heterogeneity in European sandy salt marshes

Heterogeneity can boost biodiversity, as well as increase the resilience of an ecosystem to changing environmental conditions; therefore, it is important to understand how topographic heterogeneity in ecosystems is formed. Sandy tidal marshes have a repetitive pattern of higher elevated hummocks surrounded by lower elevated depressions, representing topographic heterogeneity at the scale of a few square meters. The aims of this study were to determine when this topographic heterogeneity forms, how it is structured, and whether it persists during marsh development. The soil topography of marshes consists of coarse-grained sediment formed before marsh vegetation development, with an overlaying fine-grained sediment layer formed after initial marsh development. To gain insight into the formation of topographic heterogeneity, we studied the underlying soil topography of four European sandy marshes, where topographic heterogeneity at a scale of a few square meters was present. The differences in elevation between hummocks and depressions can either be caused by heterogeneity in the coarse-grained sediment or by heterogeneity in the top layer containing the fine-grained sediment. Our results showed that the largest percentage of elevational differences between hummocks and depressions could be attributed to heterogeneity in the underlying coarse-grained substratum. Therefore, we conclude that the patterns in all four marshes were primarily formed before marsh development, before fine-grained sediment was deposited on top of the coarse-grained sediment. However, a smaller percentage of the elevational difference between hummocks and depressions can also be explained by the presence of thicker fine-grained sediment layers on top of hummocks compared with depressions. This implies that marsh accretion rates were higher on hummocks compared with depressions. However, this result was limited to very early stages of marsh development, as marsh accretion rates estimated on marshes ranging between 15- and 120-years-old showed that depressions actually accreted sediments at a significantly faster rate than hummocks. Eventually, the patterns of heterogeneity stabilized and we found similar marsh accretion rates on hummocks and in depressions in the 120-year-old marsh, which resulted in the persistency of these topographic patterns

Performance of magnetic resonance imaging-based prostate cancer risk calculators and decision strategies in two large European medical centres

Objectives: To compare the performance of currently available biopsy decision support tools incorporating magnetic resonance imaging (MRI) findings in predicting clinically significant prostate cancer (csPCa). Patients and Methods: We retrospectively included men who underwent prostate MRI and subsequent targeted and/or systematic prostate biopsies in two large European centres. Available decision support tools were identified by a PubMed search. Performance was assessed by calibration, discrimination, decision curve analysis (DCA) and numbers of biopsies avoided vs csPCa cases missed, before and after recalibration, at risk thresholds of 5%–20%. Results: A total of 940 men were included, 507 (54%) had csPCa. The median (interquartile range) age, prostate-specific antigen (PSA) level, and PSA density (PSAD) were 68 (63–72) years, 9 (7–15) ng/mL, and 0.20 (0.13–0.32) ng/mL2, respectively. In all, 18 multivariable risk calculators (MRI-RCs) and dichotomous biopsy decision strategies based on MRI findings and PSAD thresholds were assessed. The Van Leeuwen model and the Rotterdam Prostate Cancer Risk Calculator (RPCRC) had the best discriminative ability (area under the receiver operating characteristic curve 0.86) of the MRI-RCs that could be assessed in the whole cohort. DCA showed the highest clinical utility for the Van Leeuwen model, followed by the RPCRC. At the 10% threshold the Van Leeuwen model would avoid 22% of biopsies, missing 1.8% of csPCa, whilst the RPCRC would avoid 20% of biopsies, missing 2.6% of csPCas. These multivariable models outperformed all dichotomous decision strategies based only on MRI-findings and PSAD. Conclusions: Even in this high-risk cohort, biopsy decision support tools would avoid many prostate biopsies, whilst missing very few csPCa cases. The Van Leeuwen model had the highest clinical utility, followed by the RPCRC. These multivariable MRI-RCs outperformed and should be favoured over decision strategies based only on MRI and PSAD.</p

Data Sharing in Satellite Systems: Review of the Past and Opportunities in the Age of Large LEO Constellations

Since 1957, more than 14,000 satellites have been launched into space; 2022 marks a record year with the launch of 2,163 satellites [1]. The increased number of satellites in combination with technological advancements in satellite communications has enabled operators to collect vast amounts of science data and satellite telemetry. These large data sets can be utilized to ensure coexistence between the ever-increasing number of satellite systems, potentially reducing both the risk of harmful interference and in-orbit collisions. Additionally, they can act as decentralized information sources, improving our understanding of the space environment and increasing the reliability of satellites. Modern data sharing practices for space mission data can be categorized into either post-mission or real-time analysis. Post-mission analysis can lead to detecting anomalies that occurred during a mission by correlating data points from individual or different satellites. In contrast, real-time data sharing can also help avoid harmful communication interference events and in-orbit collisions. This paper provides a review of data collection and sharing practices across three types of satellite systems: university smallsat missions, federal government missions, and private sector/commercial missions. In this review and synthesis, the utility of those datasets is identified along with challenges associated with moving towards standard structures and stakeholder sharing practices

A large-scale field experiment on salt marsh construction

Salt marshes provide important natural habitats, mitigate effects of subsidence and sea level rise and help in coastal defence. Commissioned by the municipality of Delfzijl, the EcoShape consortium obtained the opportunity to carry out a large-scale field experiment on salt marsh construction as part of their Living Lab for MUD

Ecosystem engineering by large grazers enhances carbon stocks in a tidal salt marsh

Grazers can have a large impact on ecosystem processes and are known to change vegetation composition. However, knowledge of how the long-term presence of grazers affects soil carbon sequestration is limited. In this study, we estimated total accumulated organic carbon in soils of a back-barrier salt marsh and determined how this is affected by long-term grazing by both small and large grazers in relation to age of the ecosystem. In young marshes, where small grazers predominate, hare and geese have a limited effect on total accumulated organic carbon. In older, mature marshes, where large grazers predominate, cattle substantially enhanced carbon content in the marsh soil. We ascribe this to a shift in biomass distribution in the local vegetation towards the roots in combination with trampling effects on the soil chemistry. These large grazers thus act as ecosystem engineers: their known effect on soil compaction (based on a previous study) enhances anoxic conditions in the marsh soil, thereby reducing the oxygen available for organic carbon decomposition by the local microbial community. This study showed that the indirect effects of grazing can significantly enhance soil carbon storage through changing soil abiotic conditions. This process should be taken into account when estimating the role of ecosystems in reducing carbon dioxide concentration in the atmosphere. Ultimately, we propose a testable conceptual framework that includes 3 pathways by which grazers can alter carbon storage: (1) through above-ground biomass removal, (2) through alteration of biomass distribution towards the roots and/or (3) by changing soil abiotic conditions that affect decomposition.</p