Low-dose alum application trialled as a management tool for internal nutrient loads in Lake Okaro, New Zealand

Aluminium sulfate (alum) was applied to Lake Okaro, a eutrophic New Zealand lake with recurrent cyanobacterial blooms, to evaluate its suitability for reducing trophic status and bloom frequency. The dose yielded 0.6 g aluminium m–3 in the epilimnion. Before dosing, pH exceeded 8 in epilimnetic waters but was optimal for flocculation (6–8) below 4 m depth. After dosing, there was no significant change in water clarity, hypolimnetic pH decreased to 5.5, and soluble aluminium exceeded recommended guidelines for protection of freshwater organisms. Epilimnetic phosphate concentrations decreased from 40 to 5 mg m–3 and total nitrogen (TN):total phosphorus (TP) mass ratios increased from 7:1 to 37:1. The dominant phytoplankton species changed from Anabaena spp. before dosing, to Ceratium hirudinella , then Staurastrum sp. after dosing. Detection of effectiveness of dosing may have been limited by sampling duration and design, as well as the low alum dose. The decrease in hypolimnetic pH and epilimnetic TP, and increase in Al3+ and chlorophyll a, are attributed to the low alkalinity lake water and coincidence of alum dosing with a cyanobacterial bloom and high pH

Linear Redshift Distortions and Power in the PSCz Survey

We present a state-of-the-art linear redshift distortion analysis of the recently published IRAS Point Source Catalog Redshift Survey (PSCz). The procedure involves linear compression into 4096 Karhunen-Loeve modes culled from a potential pool of about 3 x 10^5 modes, followed by quadratic compression into three separate power spectra, the galaxy-galaxy, galaxy-velocity, and velocity-velocity power spectra. Least squares fitting to the decorrelated power spectra yields a linear redshift distortion parameter beta = Omega_m^0.6/b = 0.41(+0.13,-0.12).Comment: Minor changes to agree with accepted version. Slight changes to power spectrum, including one more point added at large scales, from binning points formerly discarded as too noisy. 5 pages, including 4 embedded PostScript figures. Accepted for publication in MNRAS Letters (pink pages). Power spectrum data available at http://casa.colorado.edu/~ajsh/pscz

Matching the Scales of Planning and Environmental Risk: an Evaluation of Community Wildfire Protection Plans in the Western US

Theory predicts that effective environmental governance requires that the scales of management account for the scales of environmental processes. A good example is community wildfire protection planning. Plan boundaries that are too narrowly defined may miss sources of wildfire risk originating at larger geographic scales whereas boundaries that are too broadly defined dilute resources. Although the concept of scale (mis)matches is widely discussed in literature on risk mitigation as well as environmental governance more generally, rarely has the concept been rigorously quantified. We introduce methods to address this limitation, and we apply our approach to assess scale matching among Community Wildfire Protection Plans (CWPPs) in the western US. Our approach compares two metrics: (1) the proportion of risk sources encompassed by planning jurisdictions (sensitivity) and (2) the proportion of area in planning jurisdictions in which risk can originate (precision). Using data from 852 CWPPs and a published library of 54 million simulated wildfires, we demonstrate a trade-off between sensitivity and precision. Our analysis reveals that spatial scale match—the product of sensitivity and precision—has an n-shaped relationship with jurisdiction size and is maximal at approximately 500 km2. Bayesian multilevel models further suggest that functional scale match—via neighboring, nested, and overlapping planning jurisdictions—may compensate for low sensitivity. This study provides a rare instance of a quantitative framework to measure scale match in environmental planning and has broad implications for risk mitigation as well as in other environmental governance settings

Programa FORMO para mejorar la lectura de textos en estudiantes de primaria, Institución Educativa San Juan, San Juan de Miraflores, 2016

El objetivo de la presente investigación fue determinar el efecto de la ejecución del Programa FORMO para mejorar la lectura de textos, en estudiantes de primaria, Institución Educativa San Juan, San Juan de Miraflores, 2016‖, la población estuvo constituida por 139 niños y niñas que cursaban el III ciclo de educación Primaria, tercer grado, turno mañana, la muestra no probabilística intencional consideró 58 estudiantes; en los cuales se ha empleado la variable: Programa FORMO: Fortaleciendo la Memoria Operativa El método empleado en la investigación fue el hipotético deductivo, esta investigación utilizó para su propósito el diseño experimental de nivel explicativo, de clase cuasi experimental, que recogió la información en un período específico, que se desarrolló al aplicar el instrumento: Prueba de Comprensión Lectora de Complejidad Lingüística Progresiva (CPL) 3º Nivel A, cuyos resultados se presentan gráfica y textualmente. La investigación concluye que no existe evidencia significativa para afirmar que: La aplicación del programa ―FORMO‖ mejora significativamente la lectura de textos en estudiantes del tercer grado de primaria de la Institución Educativa San Juan, San Juan de Miraflores, 2016

OASIS: A Large-Scale Dataset for Single Image 3D in the Wild

Single-view 3D is the task of recovering 3D properties such as depth and surface normals from a single image. We hypothesize that a major obstacle to single-image 3D is data. We address this issue by presenting Open Annotations of Single Image Surfaces (OASIS), a dataset for single-image 3D in the wild consisting of annotations of detailed 3D geometry for 140,000 images. We train and evaluate leading models on a variety of single-image 3D tasks. We expect OASIS to be a useful resource for 3D vision research. Project site: https://pvl.cs.princeton.edu/OASIS.Comment: Accepted to CVPR 202

Methods for Rapidly Processing Angular Masks of Next-Generation Galaxy Surveys

As galaxy surveys become larger and more complex, keeping track of the completeness, magnitude limit, and other survey parameters as a function of direction on the sky becomes an increasingly challenging computational task. For example, typical angular masks of the Sloan Digital Sky Survey contain about N=300,000 distinct spherical polygons. Managing masks with such large numbers of polygons becomes intractably slow, particularly for tasks that run in time O(N^2) with a naive algorithm, such as finding which polygons overlap each other. Here we present a "divide-and-conquer" solution to this challenge: we first split the angular mask into predefined regions called "pixels," such that each polygon is in only one pixel, and then perform further computations, such as checking for overlap, on the polygons within each pixel separately. This reduces O(N^2) tasks to O(N), and also reduces the important task of determining in which polygon(s) a point on the sky lies from O(N) to O(1), resulting in significant computational speedup. Additionally, we present a method to efficiently convert any angular mask to and from the popular HEALPix format. This method can be generically applied to convert to and from any desired spherical pixelization. We have implemented these techniques in a new version of the mangle software package, which is freely available at http://space.mit.edu/home/tegmark/mangle/, along with complete documentation and example applications. These new methods should prove quite useful to the astronomical community, and since mangle is a generic tool for managing angular masks on a sphere, it has the potential to benefit terrestrial mapmaking applications as well.Comment: New version 2.1 of the mangle software now available at http://space.mit.edu/home/tegmark/mangle/ - includes galaxy survey masks and galaxy lists for the latest SDSS data release and the 2dFGRS final data release as well as extensive documentation and examples. 14 pages, 9 figures, matches version accepted by MNRA

Karhunen-Loeve eigenvalue problems in cosmology: how should we tackle large data sets?

Since cosmology is no longer "the data-starved science", the problem of how to best analyze large data sets has recently received considerable attention, and Karhunen-Loeve eigenvalue methods have been applied to both galaxy redshift surveys and Cosmic Microwave Background (CMB) maps. We present a comprehensive discussion of methods for estimating cosmological parameters from large data sets, which includes the previously published techniques as special cases. We show that both the problem of estimating several parameters jointly and the problem of not knowing the parameters a priori can be readily solved by adding an extra singular value decomposition step. It has recently been argued that the information content in a sky map from a next generation CMB satellite is sufficient to measure key cosmological parameters (h, Omega, Lambda, etc) to an accuracy of a few percent or better - in principle. In practice, the data set is so large that both a brute force likelihood analysis and a direct expansion in signal-to-noise eigenmodes will be computationally unfeasible. We argue that it is likely that a Karhunen-Loeve approach can nonetheless measure the parameters with close to maximal accuracy, if preceded by an appropriate form of quadratic "pre-compression". We also discuss practical issues regarding parameter estimation from present and future galaxy redshift surveys, and illustrate this with a generalized eigenmode analysis of the IRAS 1.2 Jy survey optimized for measuring beta=Omega^{0.6}/b using redshift space distortions.Comment: 15 pages, with 5 figures included. Substantially expanded with worked COBE examples for e.g. the multiparameter case. Available from http://www.sns.ias.edu/~max/karhunen.html (faster from the US), from http://www.mpa-garching.mpg.de/~max/karhunen.html (faster from Europe) or from [email protected]