Classification of Land-Water Continuum Habitats Using Exclusively Airborne Topobathymetric Lidar Green Waveforms and Infrared Intensity Point Clouds

Coastal areas host highly valuable ecosystems that are increasingly exposed to the threats of global and local changes. Monitoring their evolution at a high temporal and spatial scale is therefore crucial and mostly possible through remote sensing. This article demonstrates the relevance of topobathymetric lidar data for coastal and estuarine habitat mapping by classifying bispectral data to produce 3D maps of 21 land and sea covers at very high resolution. Green lidar full waveforms are processed to retrieve tailored features corresponding to the signature of those habitats. These features, along with infrared intensities and elevations, are used as predictors for random forest classifications, and their respective contribution to the accuracy of the results is assessed. We find that green waveform features, infrared intensities, and elevations are complimentary and yield the best classification results when used in combination. With this configuration, a classification accuracy of 90.5% is achieved for the segmentation of our dual-wavelength lidar dataset. Eventually, we produce an original mapping of a coastal site under the form of a point cloud, paving the way for 3D classification and management of land and sea covers.

Frequency and Strategicness of Clock-Checking Explain Detrimental Age-Effects in Time-Based Prospective Memory

Previous studies report that checking a clock either frequently or strategically (immediately before a target-time) improves the likelihood of remembering to perform a planned intention at a specific time (time-based prospective memory, TBPM). To disentangle the respective contribution of frequent vs. strategic clock-checking to age-related decrease in TBPM performance, we propose a new, more fine-grained indicator of strategicness. Together, both aspects of clock-checking fully mediated the negative age effect on TBPM performance and explained 54.6% of the variance of TBPM performance in an adult lifespan sample (N=221, age-range = 19-86), thereby providing avenues of intervention for improving older adults’ TBPM.

The Predictive Power of Transition Matrices

When working with Markov chains, especially if they are of order greater than one, it is often necessary to evaluate the respective contribution of each lag of the variable under study on the present. This is particularly true when using the Mixture Transition Distribution model to approximate the true fully parameterized Markov chain. Even if it is possible to evaluate each transition matrix using a standard association measure, these measures do not allow taking into account all the available information. Therefore, in this paper, we introduce a new class of so-called "predictive power" measures for transition matrices. These measures address the shortcomings of traditional association measures, so as to allow better estimation of high-order models.

Drought and Wetness Variability and the Respective Contribution of Temperature and Precipitation in the Qinghai-Tibetan Plateau

Quantifying drought and wetness fluctuations is of great significance to the regional ecological environment and water resource security, especially in the fragile Qinghai-Tibetan Plateau (QTP). In this paper, the standardized precipitation evapotranspiration index (SPEI) was calculated based on the observed data and China Meteorological Forcing Dataset (CMFD) in the QTP for the period of 1979–2015, and the drought and wetness evolution based on the SPEI series and respective contribution of temperature and precipitation were also analyzed. Results indicated that meteorological stations are mainly concentrated in the eastern part of the plateau, which cannot reflect the drought and wetness trend of the whole QTP. The linear trend and Mann–Kendall test revealed that SPEI series calculated based on CMFD data at 1-, 3-, 6-, 9-, 12-, and 24-month time scales all showed significant upward trend p < 0.01 , indicating that the QTP as a whole tended to be wetter. Spatially, the regions with significant drying p < 0.1 and increased drought probability were mainly concentrated in the Qaidam Basin and the southern part of the QTP, and the mean contribution rates of temperature and precipitation variability to SPEI trend in these regions were 60% and −11%, respectively. The regions with significant wetting p < 0.1 and decreased drought probability were mainly concentrated in the northeast, central, and western parts of the plateau, and the mean contribution rates of temperature and precipitation variability to SPEI trend were −9% and 61% in these regions. From the statistics in different climatic regions, most of the arid and humid regions in the QTP tended to be drier, while the semiarid regions tended to be wetter.

Factors Driving DNA Methylation Variation in Human Blood

Epigenetic changes are required for normal development and health, and can also underlie disease states; yet, the nature and respective contribution of factors that drive epigenetic variation in humans remain to be fully characterized. Here, we assessed how the blood DNA methylome of 958 adults is affected by genetic variation, aging, sex and 139 diverse environmental exposures, and investigated whether these effects are direct or mediated by changes in cellular composition, measured by deep immunophenotyping. We show that cellular heterogeneity and DNA sequence variation are the strongest predictors of DNA methylation levels. We identify latent cytomegalovirus infection as a major driver of DNA methylation variation and delineate three distinct effects of aging on DNA methylation, including increased dispersion consistent with epigenetic drift. Our rich dataset provides a unique resource for the design and interpretation of epigenetic studies and highlight critical factors in medical epigenomics studies.

A Combined Arms Strategy

The culmination of the European Central Bank’s (ECB) policy evolution was the ‘combined arms strategy’ that started taking shape in 2014–2015. In this chapter, we review how four unconventional measures—negative interest rates, asset purchases, targeted lending operations, and forward guidance—were progressively combined into a unified policy package. We recount the sequence of ‘recalibrations’ of these tools that took place between December 2015 and June 2018 and the internal debates that informed them. We then conduct an impact analysis where we seek to isolate and examine the contribution of the policy package to financial conditions and macroeconomic outcomes. The novelty of our analysis lies both in its methodological approach and in its diagnostics, which allows us to disentangle the respective contribution of each instrument and assess counterfactual scenarios in which they were not combined. We end by considering some of the side effects of our unconventional policies with a focus on the banking sector.

Identification of potential end-members and their apportionment from downstream high-frequency chemical data

High-frequency chemical measurements in streamwater give detailed information on the different hydrochemical processes occurring in the catchment. They can provide clues about the end-members (water sources) whose mixing produces the ionic stream concentrations observed. To identify and quantify the end-members and their respective contribution to streamwater chemistry, we developed a new methodology, termed “IQEA” (Identification and Quantification of End-members and their Apportionment). It consists in the resolution by a minimization process of an objective function based on downstream high-frequency chemical data and the size of the shape of a pre-defined fixed number of three end-members. We applied the IQEA method on the high-frequency concentration dataset of nitrates and calcium from the ORACLE-Orgeval Observatory in France. The results were compared with field data obtained from various potential end-members. The IQEA methodology yielded robust and very satisfactory results, apart from an exceptional flood event that occurred during the 2 years of measurements used in this study. While the IQEA model treats concentration and discharge datasets independently, its results show a strong relationship between the dominant end-member computed and the hydrological features.