pyveg: A Python package for analysing the time evolution of patterned vegetation using Google Earth Engine

Periodic vegetation patterns (PVP) arise from the interplay between forces that drive the growth and mortality of plants. Inter-plant competition for resources, in particular water, can lead to the formation of PVP. Arid and semi-arid ecosystems may be under threat due to changing precipitation dynamics driven by macroscopic changes in climate. These regions display some noteable examples of PVP, for example the “tiger bush” patterns found in West Africa. The morphology of the periodic pattern has been suggested to be linked to the resilience of the ecosystem (Mander et al., 2017; Trichon et al., 2018). Using remote sensing techniques, vegetation patterns in these regions can be studied, and an analysis of the resilience of the ecosystem can be performed. The pyveg package implements functionality to download and process data from Google Earth Engine (GEE), and to subsequently perform a resilience analysis on the aquired data. PVP images are quantified using network centrality metrics. The results of the analysis can be used to search for typical early warning signals of an ecological collapse (Dakos et al., 2008). Google Earth Engine Editor scripts are also provided to help researchers discover locations of ecosystems which may be in decline. pyveg is being developed as part of a research project looking for evidence of early warning signals of ecosystem collapse using remote sensing data. pyveg allows such research to be carried out at scale, and hence can be an important tool in understanding changing arid and semi-arid ecosystem dynamics. An evolving list of PVP locations, obtained through both literature and manual searches, is included in the package at pyveg/coordinates.py. The structure of the package is outlined in Figure 1, and is discussed in more detail in the following sections

Quantitatively monitoring the resilience of patterned vegetation in the Sahel

Patterning of vegetation in drylands is a consequence of localized feedback mechanisms. Such feedbacks also determine ecosystem resilience—i.e. the ability to recover from perturbation. Hence, the patterning of vegetation has been hypothesized to be an indicator of resilience, that is, spots are less resilient than labyrinths. Previous studies have made this qualitative link and used models to quantitatively explore it, but few have quantitatively analysed available data to test the hypothesis. Here we provide methods for quantitatively monitoring the resilience of patterned vegetation, applied to 40 sites in the Sahel (a mix of previously identified and new ones). We show that an existing quantification of vegetation patterns in terms of a feature vector metric can effectively distinguish gaps, labyrinths, spots, and a novel category of spot–labyrinths at their maximum extent, whereas NDVI does not. The feature vector pattern metric correlates with mean precipitation. We then explored two approaches to measuring resilience. First we treated the rainy season as a perturbation and examined the subsequent rate of decay of patterns and NDVI as possible measures of resilience. This showed faster decay rates—conventionally interpreted as greater resilience—associated with wetter, more vegetated sites. Second we detrended the seasonal cycle and examined temporal autocorrelation and variance of the residuals as possible measures of resilience. Autocorrelation and variance of our pattern metric increase with declining mean precipitation, consistent with loss of resilience. Thus, drier sites appear less resilient, but we find no significant correlation between the mean or maximum value of the pattern metric (and associated morphological pattern types) and either of our measures of resilience

Signatures of pressure-enhanced helimagnetic order in van der Waals multiferroic NiI2_2

The van der Waals (vdW) type-II multiferroic NiI$_2$ has emerged as a candidate for exploring non-collinear magnetism and magnetoelectric effects in the 2D limit. Frustrated intralayer exchange interactions on a triangular lattice result in a helimagnetic ground state, with spin-induced improper ferroelectricity stabilized by the interlayer interactions. Here we investigate the magnetic and structural phase transitions in bulk NiI$_2$, using high-pressure Raman spectroscopy, optical linear dichroism, and x-ray diffraction. We obtain evidence for a significant pressure enhancement of the antiferromagnetic and helimagnetic transition temperatures, at rates of $\sim15.3/14.4$ K/GPa, respectively. These enhancements are attributed to a cooperative effect of pressure-enhanced interlayer and third-nearest-neighbor intralayer exchange. These results reveal a general path for obtaining high-temperature type-II multiferroicity via high pressures in vdW materials

A claudin-based molecular signature identifies high-risk, chemoresistant colorectal cancer patients

Identifying molecular characteristics that are associated with aggressive cancer phenotypes through gene expression profiling can help predict treatment responses and clinical outcomes. Claudins are deregulated in colorectal cancer (CRC). In CRC, increased claudin-1 expression results in epithelial-to-mesenchymal transition and metastasis, while claudin-7 functions as a tumor suppressor. In this study, we have developed a molecular signature based on claudin-1 and claudin-7 associated with poor patient survival and chemoresistance. This signature was validated using an integrated approach including publicly available datasets and CRC samples from patients who either responded or did not respond to standard-of-care treatment, CRC cell lines, and patient-derived rectal and colon tumoroids. Transcriptomic analysis from a patient dataset initially yielded 23 genes that were differentially expressed along with higher claudin-1 and decreased claudin-7. From this analysis, we selected a claudins-associated molecular signature including PIK3CA, SLC6A6, TMEM43, and ASAP-1 based on their importance in CRC. The upregulation of these genes and their protein products was validated using multiple CRC patient datasets, in vitro chemoresistant cell lines, and patient-derived tumoroid models. Additionally, blocking these genes improved 5-FU sensitivity in chemoresistant CRC cells. Our findings propose a new claudin-based molecular signature that associates with poor prognosis as well as characteristics of treatment-resistant CRC including chemoresistance, metastasis, and relapse

Effects of pressure on the electronic and magnetic properties of bulk NiI2

Transition metal dihalides have recently garnered interest in the context of two-dimensional van der Waals magnets as their underlying geometrically frustrated triangular lattice leads to interesting competing exchange interactions. In particular, NiI2 is a magnetic semiconductor that has been long known for its exotic helimagnetism in the bulk. Recent experiments have shown that the helimagnetic state survives down to the monolayer limit with a layer-dependent magnetic transition temperature that suggests a relevant role of the interlayer coupling. Here, we explore the effects of hydrostatic pressure as a means to enhance this interlayer exchange and ultimately tune the electronic and magnetic response of NiI2. We study first the evolution of the structural parameters as a function of external pressure using first-principles calculations combined with x-ray diffraction measurements. We then examine the evolution of the electronic structure and magnetic exchange interactions via first-principles calculations and Monte Carlo simulations. We find that the leading interlayer coupling is an antiferromagnetic second-nearest-neighbor interaction that increases monotonically with pressure. The ratio between isotropic third- and first-nearest-neighbor intralayer exchanges, which controls the magnetic frustration and determines the magnetic propagation vector q of the helimagnetic ground state, is also enhanced by pressure. As a consequence, our Monte Carlo simulations show a monotonic increase in the magnetic transition temperature, indicating that pressure is an effective means to tune the magnetic response of NiI2

The most luminous, merger-free AGN show only marginal correlation with bar presence

The role of large-scale bars in the fuelling of active galactic nuclei (AGN) is still debated, even as evidence mounts that black hole growth in the absence of galaxy mergers cumulatively dominated and may substantially influence disc (i.e., merger-free) galaxy evolution. We investigate whether large-scale galactic bars are a good candidate for merger-free AGN fuelling. Specifically, we combine slit spectroscopy and Hubble Space Telescope imagery to characterise star formation rates (SFRs) and stellar masses of the unambiguously disc-dominated host galaxies of a sample of luminous, Type-1 AGN with 0.02 < z 0.024. After carefully correcting for AGN signal, we find no clear difference in SFR between AGN hosts and a stellar mass-matched sample of galaxies lacking an AGN (0.013 < z < 0.19), although this could be due to a small sample size (n_AGN = 34). We correct for SFR and stellar mass to minimise selection biases, and compare the bar fraction in the two samples. We find that AGN are marginally (1.7$\sigma$) more likely to host a bar than inactive galaxies, with AGN hosts having a bar fraction, fbar = 0.59^{+0.08}_{-0.09} and inactive galaxies having a bar fraction fbar = 0.44^{+0.08}_{-0.09}. However, we find no further differences between SFR- and mass-matched AGN and inactive samples. While bars could potentially trigger AGN activity, they appear to have no further, unique effect on a galaxy's stellar mass or SFR.Comment: 15 pages (9 figures). Accepted for publication in MNRA

An Open, Large-Scale, Collaborative Effort to Estimate the Reproducibility of Psychological Science

Reproducibility is a defining feature of science. However, because of strong incentives for innovation and weak incentives for confirmation, direct replication is rarely practiced or published. The Reproducibility Project is an open, large-scale, collaborative effort to systematically examine the rate and predictors of reproducibility in psychological science. So far, 72 volunteer researchers from 41 institutions have organized to openly and transparently replicate studies published in three prominent psychological journals in 2008. Multiple methods will be used to evaluate the findings, calculate an empirical rate of replication, and investigate factors that predict reproducibility. Whatever the result, a better understanding of reproducibility will ultimately improve confidence in scientific methodology and findings