Predicting Crappie Recruitment in Ohio Reservoirs with Spawning Stock Size, Larval Density, and Chlorophyll Concentrations

Stock-recruit models typically use only spawning stock size as a predictor of recruitment to a fishery. In this paper, however, we used spawning stock size as well as larval density and key environmental variables to predict recruitment of white crappies Pomoxis annularis and black crappies P. nigromaculatus, a genus notorious for variable recruitment. We sampled adults and recruits from 11 Ohio reservoirs and larvae from 9 reservoirs during 1998-2001. We sampled chlorophyll as an index of reservoir productivity and obtained daily estimates of water elevation to determine the impact of hydrology on recruitment. Akaike's information criterion (AIC) revealed that Ricker and Beverton-Holt stock-recruit models that included chlorophyll best explained the variation in larval density and age-2 recruits. Specifically, spawning stock catch per effort (CPE) and chlorophyll explained 63-64% of the variation in larval density. In turn, larval density and chlorophyll explained 43-49% of the variation in age-2 recruit CPE. Finally, spawning stock CPE and chlorophyll were the best predictors of recruit CPE (i.e., 74-86%). Although larval density and recruitment increased with chlorophyll, neither was related to seasonal water elevation. Also, the AIC generally did not distinguish between Ricker and Beverton-Holt models. From these relationships, we concluded that crappie recruitment can be limited by spawning stock CPE and larval production when spawning stock sizes are low (i.e., CPE , 5 crappies/net-night). At higher levels of spawning stock sizes, spawning stock CPE and recruitment were less clearly related. To predict recruitment in Ohio reservoirs, managers should assess spawning stock CPE with trap nets and estimate chlorophyll concentrations. To increase crappie recruitment in reservoirs where recruitment is consistently poor, managers should use regulations to increase spawning stock size, which, in turn, should increase larval production and recruits to the fishery.This research was funded by Federal Aid in Sport Fish Restoration Project F-69-P, administered jointly by the U.S. Fish and Wildlife Service and Ohio Department of Natural Resources, Division of Wildlife, and the Department of Evolution, Ecology, and Organismal Biology at Ohio State University

p73 Regulates Neurodegeneration and Phospho-Tau Accumulation during Aging and Alzheimer's Disease

SummaryThe genetic mechanisms that regulate neurodegeneration are only poorly understood. We show that the loss of one allele of the p53 family member, p73, makes mice susceptible to neurodegeneration as a consequence of aging or Alzheimer's disease (AD). Behavioral analyses demonstrated that old, but not young, p73+/− mice displayed reduced motor and cognitive function, CNS atrophy, and neuronal degeneration. Unexpectedly, brains of aged p73+/− mice demonstrated dramatic accumulations of phospho-tau (P-tau)-positive filaments. Moreover, when crossed to a mouse model of AD expressing a mutant amyloid precursor protein, brains of these mice showed neuronal degeneration and early and robust formation of tangle-like structures containing P-tau. The increase in P-tau was likely mediated by JNK; in p73+/− neurons, the activity of the p73 target JNK was enhanced, and JNK regulated P-tau levels. Thus, p73 is essential for preventing neurodegeneration, and haploinsufficiency for p73 may be a susceptibility factor for AD and other neurodegenerative disorders

The clustering of galaxies at z~0.5 in the SDSS-III Data Release 9 BOSS-CMASS sample: a test for the LCDM cosmology

We present results on the clustering of 282,068 galaxies in the Baryon Oscillation Spectroscopic Survey (BOSS) sample of massive galaxies with redshifts 0.4<z<0.7 which is part of the Sloan Digital Sky Survey III project. Our results cover a large range of scales from ~0.5 to ~90 Mpc/h. We compare these estimates with the expectations of the flat LCDM cosmological model with parameters compatible with WMAP7 data. We use the MultiDark cosmological simulation together with a simple halo abundance matching technique, to estimate galaxy correlation functions, power spectra, abundance of subhaloes and galaxy biases. We find that the LCDM model gives a reasonable description to the observed correlation functions at z~0.5, which is a remarkably good agreement considering that the model, once matched to the observed abundance of BOSS galaxies, does not have any free parameters. However, we find a deviation (>~10%) in the correlation functions for scales less than ~1 Mpc/h and ~10-40 Mpc/h. A more realistic abundance matching model and better statistics from upcoming observations are needed to clarify the situation. We also estimate that about 12% of the "galaxies" in the abundance-matched sample are satellites inhabiting central haloes with mass M>~1e14 M_sun/h. Using the MultiDark simulation we also study the real space halo bias b(r) of the matched catalogue finding that b=2.00+/-0.07 at large scales, consistent with the one obtained using the measured BOSS projected correlation function. Furthermore, the linear large-scale bias depends on the number density n of the abundance-matched sample as b=-0.048-(0.594+/-0.02)*log(n/(h/Mpc)^3). Extrapolating these results to BAO scales we measure a scale-dependent damping of the acoustic signal produced by non-linear evolution that leads to ~2-4% dips at ~3 sigma level for wavenumbers k>~0.1 h/Mpc in the linear large-scale bias.Comment: Replaced to match published version. Typos corrected; 25 pages, 17 figures, 9 tables. To appear in MNRAS. Correlation functions (projected and redshift-space) and correlation matrices of CMASS presented in Appendix B. Correlation and covariance data for the combined CMASS sample can be downloaded from http://www.sdss3.org/science/boss_publications.ph

Understanding Dwarf Galaxies in order to Understand Dark Matter

Much progress has been made in recent years by the galaxy simulation community in making realistic galaxies, mostly by more accurately capturing the effects of baryons on the structural evolution of dark matter halos at high resolutions. This progress has altered theoretical expectations for galaxy evolution within a Cold Dark Matter (CDM) model, reconciling many earlier discrepancies between theory and observations. Despite this reconciliation, CDM may not be an accurate model for our Universe. Much more work must be done to understand the predictions for galaxy formation within alternative dark matter models.Comment: Refereed contribution to the Proceedings of the Simons Symposium on Illuminating Dark Matter, to be published by Springe

Reconciliation of essential process parameters for an enhanced predictability of Arctic stratospheric ozone loss and its climate interactions

Significant reductions in stratospheric ozone occur inside the polar vortices each spring when chlorine radicals produced by heterogeneous reactions on cold particle surfaces in winter destroy ozone mainly in two catalytic cycles, the ClO dimer cycle and the ClO/BrO cycle. Chlorofluorocarbons (CFCs), which are responsible for most of the chlorine currently present in the stratosphere, have been banned by the Montreal Protocol and its amendments, and the ozone layer is predicted to recover to 1980 levels within the next few decades. During the same period, however, climate change is expected to alter the temperature, circulation patterns and chemical composition in the stratosphere, and possible geo-engineering ventures to mitigate climate change may lead to additional changes. To realistically predict the response of the ozone layer to such influences requires the correct representation of all relevant processes. The European project RECONCILE has comprehensively addressed remaining questions in the context of polar ozone depletion, with the objective to quantify the rates of some of the most relevant, yet still uncertain physical and chemical processes. To this end RECONCILE used a broad approach of laboratory experiments, two field missions in the Arctic winter 2009/10 employing the high altitude research aircraft M55-Geophysica and an extensive match ozone sonde campaign, as well as microphysical and chemical transport modelling and data assimilation. Some of the main outcomes of RECONCILE are as follows: (1) vortex meteorology: the 2009/10 Arctic winter was unusually cold at stratospheric levels during the six-week period from mid-December 2009 until the end of January 2010, with reduced transport and mixing across the polar vortex edge; polar vortex stability and how it is influenced by dynamic processes in the troposphere has led to unprecedented, synoptic-scale stratospheric regions with temperatures below the frost point; in these regions stratospheric ice clouds have been observed, extending over >106km2 during more than 3 weeks. (2) Particle microphysics: heterogeneous nucleation of nitric acid trihydrate (NAT) particles in the absence of ice has been unambiguously demonstrated; conversely, the synoptic scale ice clouds also appear to nucleate heterogeneously; a variety of possible heterogeneous nuclei has been characterised by chemical analysis of the non-volatile fraction of the background aerosol; substantial formation of solid particles and denitrification via their sedimentation has been observed and model parameterizations have been improved. (3) Chemistry: strong evidence has been found for significant chlorine activation not only on polar stratospheric clouds (PSCs) but also on cold binary aerosol; laboratory experiments and field data on the ClOOCl photolysis rate and other kinetic parameters have been shown to be consistent with an adequate degree of certainty; no evidence has been found that would support the existence of yet unknown chemical mechanisms making a significant contribution to polar ozone loss. (4) Global modelling: results from process studies have been implemented in a prognostic chemistry climate model (CCM); simulations with improved parameterisations of processes relevant for polar ozone depletion are evaluated against satellite data and other long term records using data assimilation and detrended fluctuation analysis. Finally, measurements and process studies within RECONCILE were also applied to the winter 2010/11, when special meteorological conditions led to the highest chemical ozone loss ever observed in the Arctic. In addition to quantifying the 2010/11 ozone loss and to understand its causes including possible connections to climate change, its impacts were addressed, such as changes in surface ultraviolet (UV) radiation in the densely populated northern mid-latitudes

The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: the low-redshift sample

We report on the small-scale (0.5 r h−1 Mpc) clustering of 78 895 massive (M* ~ 1011.3 M⊙) galaxies at 0.2 z 13 h−1 M⊙, a large-scale bias of ~2.0 and a satellite fraction of 12 ± 2 per cent. Thus, these galaxies occupy haloes with average masses in between those of the higher redshift BOSS CMASS sample and the original SDSS I/II luminous red galaxy sample

The Astropy Problem

The Astropy Project (http://astropy.org) is, in its own words, "a community effort to develop a single core package for Astronomy in Python and foster interoperability between Python astronomy packages." For five years this project has been managed, written, and operated as a grassroots, self-organized, almost entirely volunteer effort while the software is used by the majority of the astronomical community. Despite this, the project has always been and remains to this day effectively unfunded. Further, contributors receive little or no formal recognition for creating and supporting what is now critical software. This paper explores the problem in detail, outlines possible solutions to correct this, and presents a few suggestions on how to address the sustainability of general purpose astronomical software

Reconciliation of essential process parameters for an enhanced predictability of Arctic stratospheric ozone loss and its climate interactions : (RECONCILE) ; activities and results

The international research project RECONCILE has addressed central questions regarding polar ozone depletion, with the objective to quantify some of the most relevant yet still uncertain physical and chemical processes and thereby improve prognostic modelling capabilities to realistically predict the response of the ozone layer to climate change. This overview paper outlines the scope and the general approach of RECONCILE, and it provides a summary of observations and modelling in 2010 and 2011 that have generated an in many respects unprecedented dataset to study processes in the Arctic winter stratosphere. Principally, it summarises important outcomes of RECONCILE including (i) better constraints and enhanced consistency on the set of parameters governing catalytic ozone destruction cycles, (ii) a better understanding of the role of cold binary aerosols in heterogeneous chlorine activation, (iii) an improved scheme of polar stratospheric cloud (PSC) processes that includes heterogeneous nucleation of nitric acid trihydrate (NAT) and ice on non-volatile background aerosol leading to better model parameterisations with respect to denitrification, and (iv) long transient simulations with a chemistry-climate model (CCM) updated based on the results of RECONCILE that better reproduce past ozone trends in Antarctica and are deemed to produce more reliable predictions of future ozone trends. The process studies and the global simulations conducted in RECONCILE show that in the Arctic, ozone depletion uncertainties in the chemical and microphysical processes are now clearly smaller than the sensitivity to dynamic variability

Blueprints of Effective Biodiversity and Conservation Knowledge Products That Support Marine Policy

Biodiversity and conservation data are generally costly to collect, particularly in the marine realm. Hence, data collected for a given—often scientific—purpose are occasionally contributed toward secondary needs, such as policy implementation or other types of decision-making. However, while the quality and accessibility of marine biodiversity and conservation data have improved over the past decade, the ways in which these data can be used to develop and implement relevant management and conservation measures and actions are not always explicit. For this reason, there are a number of scientifically-sound datasets that are not used systematically to inform policy and decisions. Transforming these marine biodiversity and conservation datasets into knowledge products that convey the information required by policy- and decision-makers is an important step in strengthening knowledge exchange across the science-policy interface. Here, we identify seven characteristics of a selection of online biodiversity and conservation knowledge products that contribute to their ability to support policy- and decision-making in the marine realm (as measured by e.g., mentions in policy resolutions/decisions, or use for reporting under selected policy instruments; use in high-level screening for areas of biodiversity importance). These characteristics include: a clear policy mandate; established networks of collaborators; iterative co-design of a user-friendly interface; standardized, comprehensive and documented methods with quality assurance; consistent capacity and succession planning; accessible data and value-added products that are fit-for-purpose; and metrics of use collated and reported. The outcomes of this review are intended to: (a) support data creators/owners/providers in designing and curating biodiversity and conservation knowledge products that have greater influence, and hence impact, in policy- and decision-making, and (b) provide recommendations for how decision- and policy-makers can support the development, implementation, and sustainability of robust biodiversity and conservation knowledge products through the framing of marine policy and decision-making frameworks.This is a contribution to the “Building the European Biodiversity Observation Network” (EU BON) project (www.eubon.eu), a 7th Framework Programme funded by the European Union under grant agreement No. 308454. The authors would also like to acknowledge the Proteus Partnership, the European Commission, the CITES Secretariat, UN Environment, the World Conservation Monitoring Centre, the International Union for Conservation of Nature and the national agencies contributing to GBIF core funds for their financial contributions toward developing and maintaining these knowledge products