High Density Threshold Research Articles

Improving coral cover using an integrated pest management framework.

Integrated pest management (IPM) leverages our understanding of ecological interactions to mitigate the impact of pest species on economically and/or ecologically important assets. It has primarily been applied in terrestrial settings (e.g., agriculture), but has rarely been attempted for marine ecosystems. The crown-of-thorns starfish (CoTS), Acanthaster spp., is a voracious coral predator throughout the Indo-Pacific where it undergoes large population increases (irruptions), termed outbreaks. During outbreaks CoTS act as a pest species and can result in substantial coral loss. Contemporary management of CoTS on the Great Barrier Reef (GBR) adopts facets of the IPM paradigm to manage these outbreaks through strategic use of direct manual control (culling) of individuals in response to ecologically based target thresholds. There has, however, been limited quantitative analysis of how to optimize the implementation of such thresholds. Here we use a multispecies modeling approach to assess the performance of alternative CoTS management scenarios for improving coral cover trajectories. The scenarios examined varied in terms of their ecological threshold target, the sensitivity of the threshold, and the level of management resourcing. Our approach illustrates how to quantify multidimensional trade-offs in resourcing constraints, concurrent CoTS and coral population dynamics, the stringency of target thresholds, and the geographical scale of management outcomes (number of sites). We found strategies with low target density thresholds for CoTS (≤0.03 CoTS min-1 ) could act as "Effort Sinks" and limit the number of sites that could be effectively controlled, particularly under CoTS population outbreaks. This was because a handful of sites took longer to control, which meant other sites were not controlled. Higher density thresholds (e.g., 0.04-0.08 CoTS min-1 ), tuned to levels of coral cover, diluted resources among sites but were more robust to resourcing constraints and pest population dynamics. Our study highlights trade-off decisions when using an IPM framework and informs the implementation of threshold-based strategies on the GBR.

Abstract 1306: Density-based mutation clustering in 3D space

Abstract Cancer driver mutation and gene discovery has been a major challenge in cancer research. Several computational tools focus on clustering mutations on 3D protein structures to identify cancer drivers, including HotSpot3D, CLUMPS, HotMAPS, 3DHotSpots.org and e-Driver. While other tools provide a single snapshot of mutation clusters on the 3D structure, HotSpot3D utilizes a unique density-based clustering module capable of providing a full dynamical profile of clusters with varying densities. The density module (DM) is capable of detecting subtle variation in the density of mutations in 3D structures with little computation time and complexity. DM gives users the ability to detect the bridging effect, where more dense subclusters form a less dense supercluster due to a small number of mutations in between the subclusters connecting them. In addition to clustering based on physical density of mutations, DM is capable of clustering by additional biologic properties, including mutation recurrence and pathogenicity. Moreover, the underlying OPTICS algorithm utilized in the DM is inherently a “fuzzy” clustering algorithm, allowing slight variation of clusters based on the start point of the clustering algorithm from one run to another. Therefore, the DM provides a cluster membership probability measure for each mutation, giving the user the ability to choose the preferred stringency. Additionally, DM allows users to visualize the density clusters using Pymol. Since the whole dynamical set of clusters is produced by a single run, the visualization is performed so that one can reveal other clusters with higher densities by zooming in and out. Using a curated set of experimentally validated oncogenic mutations, we evaluated the performance of DM in detecting functionally activating mutations; our tool performed well in identifying driver mutations at high density thresholds. Moreover, the DM was able to identify mutations clustering at high density in BRAF, PIK3CA and KEAP1, which were not detected by other 3D clustering tools and sequence-based tools (SIFT, PolyPhen2, CHASM, etc.). The DM was also better at detecting clusters along the interface of protein-protein complexes (e.g., BRAF-KEAP1) compared to other 3D tools. In summary, HotSpot3D-DM allows for dynamical clustering, improved visualization, and identifies novel driver mutations missed by previous tools. Citation Format: Amila Weerasinghe, Sohini Sengupta, Adam D. Scott, Maththew H. Bailey, Michael C. Wendl, Ken Chen, Gordon Mills, Li Ding. Density-based mutation clustering in 3D space [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1306.

The fertile physics of chemical gardens

Many a child has enjoyed watching the gardens grow; many a physicist has puzzled over the transformation of self-organized, nonequilibrium patterns into permanent structures.

Constraining the halo bispectrum in real and redshift space from perturbation theory and non-linear stochastic bias

We present a method to produce mock galaxy catalogues with efficient perturbation theory schemes, which match the number density, power spectra and bispectra in real and in redshift space from N-body simulations. The essential contribution of this work is the way in which we constrain the bias parameters in the PATCHY-code. In addition of aiming at reproducing the two-point statistics, we seek the set of bias parameters, which constrain the univariate halo probability distribution function (PDF) encoding higher-order correlation functions. We demonstrate that halo catalogues based on the same underlying dark matter field with a fix halo number density, and accurately matching the power spectrum (within 2%), can lead to very different bispectra depending on the adopted halo bias model. A model ignoring the shape of the halo PDF can lead to deviations up to factors of 2. The catalogues obtained additionally constraining the shape of the halo PDF can significantly lower the discrepancy in the three-point statistics, yielding closely unbiased bispectra both in real and in redshift space; which are in general compatible with those corresponding to an N-body simulation within 10% (deviating at most up to 20%). Our calculations show that the constant linear bias of ~2 for Luminous Red Galaxy (LRG) like galaxies seen in the power spectrum, mainly comes from sampling halos in high density peaks, choosing a high density threshold rather than from a factor multiplying the dark matter density field. Our method contributes towards an efficient modelling of the halo/galaxy distribution required to estimate uncertainties in the clustering measurements from galaxy redshift surveys. We have also demonstrated that it represents a powerful tool to test various bias models.

The formation of disc galaxies in high-resolution moving-mesh cosmological simulations

We present cosmological hydrodynamical simulations of eight Milky Way-sized haloes that have been previously studied with dark matter only in the Aquarius project. For the first time, we employ the moving-mesh code AREPO in zoom simulations combined with a comprehensive model for galaxy formation physics designed for large0 cosmological simulations. Our simulations form in most of the eight haloes strongly disc-dominated systems with realistic rotation curves, close to exponential surface density profiles, a stellar-mass to halo-mass ratio that matches expectations from abundance matching techniques, and galaxy sizes and ages consistent with expectations from large galaxy surveys in the local Universe. There is no evidence for any dark matter core formation in our simulations, even so they include repeated baryonic outflows by supernova-driven winds and black hole quasar feedback. For one of our haloes, the object studied in the recent `Aquila' code comparison project, we carried out a resolution study with our techniques, covering a dynamic range of 64 in mass resolution. Without any change in our feedback parameters, the final galaxy properties are reassuringly similar, in contrast to other modelling techniques used in the field that are inherently resolution dependent. This success in producing realistic disc galaxies is reached, in the context of our interstellar medium treatment, without resorting to a high density threshold for star formation, a low star formation efficiency, or early stellar feedback, factors deemed crucial for disc formation by other recent numerical studies.

Effect of Insect Density and Host Plant Quality on Wing-Form inMegamelus scutellaris(Hemiptera: Delphacidae)

Megamelus scutellaris Berg (Hemiptera: Delphacidae) is a South American species that feeds on waterhyacinth, Eichhornia crassipes Mart. (Solms). This species exhibits significant wing dimorphism whereby fully winged adults (macropters) are capable of flight while those with reduced wings (brachtypters) are not. The wing form is determined by a developmental switch triggered by environmental factors including crowding, host plant quality, temperature, and photoperiod. This study examined the influences of insect density and host plant quality on M. scutellaris wing dimorphism, development, and biomass as well as their effects on E. crassipes. Two experiments exposed a single generation of M. scutellaris to lower and higher densities of conspecifics on low and high quality plants. The first experiment involved transferring second instars to test plants at loads of 50, 5, or 1 g of fresh weight plant biomass per nymph, which resulted in mean densities of 2, 15, and 69 nymphs, respectively, on both low and high quality plants. A second experiment exposed test plants to 2, 4, or 20 M. scutellaris adults for 7 days and allowed their progeny to develop into adults which ultimately produced densities of 0, 56, and 352 F1 adults, respectively, per low and high quality plants. No macropterous adults were produced in any treatment combination in either experiment. Several plant variables were affected by insect densities and plant quality including the mean relative growth rate, the change in leaf number, and the percentage of dead leaves on a plant. Megamelus scutellaris appeared to have a relatively high density threshold for macroptery within the range of host quality used in these studies. This may promote more brachyptery which, in turn, may increase the chances of this insect reaching damaging densities in field populations of E. crassipes.

A UNIVERSAL, LOCAL STAR FORMATION LAW IN GALACTIC CLOUDS, NEARBY GALAXIES, HIGH-REDSHIFT DISKS, AND STARBURSTS

[abridged] While observations of Local Group galaxies show a very simple, local star formation law in which the star formation rate per unit area in each patch of a galaxy scales linearly with the molecular gas surface density, recent observations of both Milky Way molecular clouds and high redshift galaxies apparently show a more complicated relationship, in which regions of equal surface density can form stars at quite different rates. These data have been interpreted as implying either that different star formation laws apply in different circumstances, that the star formation law is sensitive to large-scale galaxy properties rather than local properties, or that there are high density thresholds for star formation. Here we collate resolved observations of Milky Way molecular clouds, kpc-scale observations of Local Group galaxies, and unresolved observations of both disk and starburst galaxies in the local universe and at high redshift. We show that all of these data are in fact consistent with a simple, local, volumetric star formation law. The apparent variations stem from the fact that the observed objects have a wide variety of 3D size scales and degrees of internal clumping, so even at fixed gas column density the regions being observed can have wildly varying volume densities. We provide a simple theoretical framework to remove this projection effect, and we show that all the data, from small Solar neighborhood clouds with masses ~10^3 Msun to sub-mm galaxies with masses ~10^11 Msun, fall on a single star formation law in which the SFR is simply ~1% of the molecular gas mass per local free-fall time. In contrast, proposed star formation laws in which the star formation timescale is set by the galactic rotation period or the SFR is linearly proportional to the gas mass above some density threshold fail to match at least some of the data.

Core Mass Function: The Role of Gravity

We analyze the mass distribution of cores formed in an isothermal, magnetized, turbulent, and self-gravitating nearly critical molecular cloud model. Cores are identified at two density threshold levels. Our main results are that the presence of self-gravity modifies the slopes of the core mass function (CMF) at the high-mass end. At low thresholds, the slope is shallower than the one predicted by pure turbulent fragmentation. The shallowness of the slope is due to the effects of core coalescence and gas accretion. Most importantly, the slope of the CMF at the high-mass end steepens when cores are selected at higher density thresholds, or alternatively, if the CMF is fitted with a lognormal function, the width of the lognormal distribution decreases with increasing threshold. This is due to the fact that gravity plays a more important role in denser structures selected at higher density threshold and leads to the conclusion that the role of gravity is essential in generating a CMF that bears more resemblance to the IMF when cores are selected with an increasing density threshold in the observations.

Two-dimensional multi-criterion segmentation of pulmonary nodules on helical CT images.

A multi-criterion algorithm for automatic delineation of small pulmonary nodules on helical CT images has been developed. In a slice-by-slice manner, the algorithm uses density, gradient strength, and a shape constraint of the nodule to automatically control segmentation process. The multiple criteria applied to separation of the nodule from its surrounding structures in lung are based on the fact that typical small pulmonary nodules on CT images have high densities, show a distinct difference in density at the boundary, and tend to be compact in shape. Prior to the segmentation, a region-of-interest containing the nodule is manually selected on the CT images. Then the segmentation process begins with a high density threshold that is decreased stepwise, resulting in expansion of the area of nodule candidates. This progressive region growing approach is terminated when subsequent thresholds provide either a diminished gradient strength of the nodule contour or significant changes of nodule shape from the compact form. The shape criterion added to the algorithm can effectively prevent the high density surrounding structures (e.g., blood vessels) from being falsely segmented as nodule, which occurs frequently when only the gradient strength criterion is applied. This has been demonstrated by examples given in the Results section. The algorithm's accuracy has been compared with that of radiologist's manual segmentation, and no statistically significant difference has been found between the nodule areas delineated by radiologist and those obtained by the multi-criterion algorithm. The improved nodule boundary allows for more accurate assessment of nodule size and hence nodule growth over a short time period, and for better characterization of nodule edges. This information is useful in determining malignancy status of a nodule at an early stage and thus provides significant guidance for further clinical management.

Pfair scheduling of generalized pinwheel task systems

The scheduling of generalized pinwheel task systems is considered. It is shown that pinwheel scheduling is closely related to the fair scheduling of periodic task systems. This relationship is exploited to obtain new scheduling algorithms for generalized pinwheel task systems. When compared to traditional pinwheel scheduling algorithms, these new algorithms are both more efficient from a run-time complexity point of view, and have a higher density threshold, on a very large subclass of generalized pinwheel task systems.