Man Camps and Bad Men: Litigating Violence Against American Indian Women

The crisis of sexual violence plaguing Indian Country is made drastically worse by oil-pipeline construction, which often occurs near reservations. The “man camps” constructed to house pipeline workers are hotbeds of rape, domestic violence, and sex trafficking, and American Indian women are frequently targeted due to a perception that men will not be prosecuted for assaulting them. Victims have little recourse, facing underfunded police departments, indifferent prosecutors, and a federal government all too willing to turn a blind eye to the ongoing violence. This Note proposes a litigation strategy for tribes to address the crisis and compel federal action. Litigation would rely upon the “Bad Men” clauses in 1867 and 1868 tribal–federal treaties, which mandate government action when “bad men among the Whites” commit crimes against tribal members. Indian law canons of construction urge that these treaties be construed in favor of the tribes and interpreted in the manner in which historical tribal signatories would have understood them. Under the doctrine of parens patriae, tribes could bring Bad Men lawsuits on behalf of tribal members who have been harmed. Because Indian signatories to the Bad Men treaties would have understood them to impose a positive and prospective obligation to protect, tribes ought to be able to use such litigation to compel federal protection for the women victimized as a result of pipeline construction

Tratamiento Quimico Electroquímico para degradar compuestos emergentes en Lodos Residuales Industriales y Municipales.

Los lodos residuales son un residuos sólido insoluble generado en las plantas tratadoras de agua residual (PTAR), al ser debidamente tratado se denomina "biosólido". En todo el mundo la generación de estos lodos está aumentando como resultado del incremento en el número de plantas. El tratamiento de lodos residuales representa más del 50% de los costos de operación y mantenimiento en las (PTAR)

An empirical mixed model to quantify climate influence on the growth of Pinus halepensis Mill. stands in South-Eastern Spain

The influence of climate on forest stand composition, development and growth is undeniable. Many studies have tried to quantify the effect of climatic variables on forest growth and yield. These works become especially important because there is a need to predict the effects of climate change on the development of forest ecosystems. One of the ways of facing this problem is the inclusion of climatic variables into the classic empirical growth models. The work has a double objective: (i) to identify the indicators which best describe the effect of climate on Pinus halepensis growth and (ii) to quantify such effect in several scenarios of rainfall decrease which are likely to occur in the Mediterranean area. A growth mixed model for P. halepensis including climatic variables is presented in this work. Growth estimates are based on data from the Spanish National Forest Inventory (SNFI). The best results are obtained for the indices including rainfall, or rainfall and temperature together, with annual precipitation, precipitation effectiveness, Emberger?s index or free bioclimatic intensity standing out among them. The final model includes Emberger?s index, free bioclimatic intensity and interactions between competition and climate indices. The results obtained show that a rainfall decrease about 5% leads to a decrease in volume growth of 5.5?7.5% depending on site quality

研究者紹介 / 奥付

Copia digital. Madrid : Ministerio de Cultura. Subdirección General de Coordinación Bibliotecaria, 200

黒田忠史教授 年譜

Copia digital. Madrid : Ministerio de Cultura. Subdirección General de Coordinación Bibliotecaria, 200

執筆者紹介

Copia digital. Madrid : Ministerio de Cultura. Subdirección General de Coordinación Bibliotecaria, 200

Mixing effect on volume growth of Fagus sylvatica and Pinus sylvestris is modulated by stand density

Despite the increasing relevance of mixed stands due to their potential benefits; little information is available with regard to the effect of mixtures on yield in forest systems. Hence, it is necessary to study inter-specific relationships, and the resulting yield in mixed stands, which may vary with stand development, site or stand density, etc. In Spain, the province of Navarra is considered one of the biodiversity reservoirs; however, mixed forests occupy only a small area, probably as a consequence of management plans, in which there is an excessive focus on the productivity aspect, favoring the presence of pure stands of the most marketable species. The aim of this paper is to study how growth efficiencies of beech (Fagus sylvatica) and pine (Pinus sylvestris) are modified by the admixture of the other species and to determine whether stand density modifies interspecific relationships and to what extent. Two models were fitted from Spanish National Forest Inventory data, for P. sylvestris and F. sylvatica respectively, which relate the growth efficiency of the species, i.e. the volume increment of the species divided by the species proportion by area, with dominant height, quadratic mean diameter, stocking degree, and the species proportions by area of each species. Growth efficiency of pine increased with the admixture of beech, decreasing this positive effect when stocking degree increased. However, the positive effect of pine admixture on beech growth was greater at higher stocking degrees. Growth efficiency of beech was also dependent on stand dominant height, resulting in a net negative mixing effect when stand dominant heights and stocking degrees were simultaneously low. There is a relatively large range of species proportions and stocking degrees which results in transgressive overyielding: higher volume increments in mixed stands than that of the most productive pure pine stands. We concluded that stocking degree is a key factor in between-species interactions, being the effects of mixing not always greater at higher stand densities, but it depends on species composition

Etiquetado automático de los colores de una imagen con redes neuronales

En este proyecto se propone una herramienta de clasificación automática de los colores en imágenes basada en redes neuronales. El objetivo es obtener una clasificación que permita identificar los diferentes colores que aparecen en una imagen. Para realizar dicho clasificador se han analizado la precisión de las múltiples arquitecturas de redes neuronales simples. Posteriormente se ha desarrollado un conjunto de funciones y una interfaz gráfica para poder aplicar el clasificador entrenado y se han realizado pruebas de clasificación para evaluar el rendimiento. Las redes neuronales entrenadas durante el proyecto permiten realizar clasificación de los colores en imágenes con unos resultados favorables en un tiempo aceptable, aunque todavía existe margen para poder mejorar.En aquest projecte es proposa una eina de classificació automàtica dels colors en imatges basada en xarxes neuronals. L'objectiu principal és obtenir una classificació que pugui identificar els diferents colors que poden aparèixer en una imatge. Per poder desenvolupar aquest classificador s'ha analitzat la precisió de diverses arquitectures de xarxes neuronals simples. Posteriorment s'ha desenvolupat un conjunt de funcions i una interfície gràfica per poder aplicar el classificador ja entrenat i s'han realitzat proves de classificació per avaluar el rendiment. Les xarxes neuronals entrenades durant el projecte permeten realitzar classificació dels colors en imatges amb uns resultats favorables en un temps acceptable, tot i que encara hi ha possibilitat d'obtenir millores.In this project we developed an automated color classification tool for images using neural networks. The main objective is to obtain a classification model good enough to allow identifying different colors inside natural images. To accomplish this, we analyzed the accuracy of the training in multiple simple neural network architectures. We followed with the development of a library of functions and a graphic user interface that allows applying the trained classification model to user provided images and performed multiple tests to evaluate the performance. The obtained performance from the trained neural networks during this project is satisfactory with an acceptable time, but there's always room for improvement

A new method for the identification of old-growth trees in National Forest Inventories: Application to Pinus halepensis Mill. stands in Spain

Old-growth trees play a very important role in the maintenance of biodiversity in forests. However, no clear definition is yet available to help identify them since tree age is usually not recorded in National Forest Inventories. To develop and test a new method to identify old-growth trees using a species-specific threshold for tree diameter in National Forest Inventories. Different nonlinear mixed models for diameter ? age were generated using data from the Spanish Forest Inventory in order to identify the most appropriate one for Aleppo pine in its South-western distribution area. The asymptote of the optimal model indicates the threshold diameter for defining an old-growth tree. Additionally, five site index curves were examined to analyze the influence of site quality on these models

Effect of species proportion definition on the evaluation of growth in pure vs. mixed stands

Aim of study: The aim of this paper is to compare differences in growth per hectare of species in pure and mixed stands as they result from different definitions of species proportions.Area of Study: We used the data of the Spanish National Forest Inventory for Scots pine and beech mixtures in the province of Navarra and for Scots pine and Pyrenean oak mixtures in the Central mountain range and the North Iberic mountain range.Material and Methods: Growth models were parameterized with the species growth related to its proportion as dependent variable, and dominant height, quadratic mean diameter density, and species proportion as independent variables. As proportions we use once proportions by basal area or by stand density index and once these proportions considering the species specific maximum densities.Main Results: In the pine – beech mixtures, where the maximum densities do not differ very much between species, the mixing effects are very similar, independent of species proportion definitions. In the pine – oak mixture, where the maximum densities in terms of basal area are very different, the equations using the proportions calculated without reference to the maximum densities, result in a distinct overestimation of the mixing effects on growth.Research highlights: When comparing growth per hectare of a species in a mixed stand with that of a pure stand, the species proportion must be described as a proportion by area considering the maximum density for the given species, wrong mixing effects could be introduced by inappropriate species proportion definitions.Keywords: Mixing effects; proportion by area; Stand Density Index; overyielding; Pinus sylvestris L.; Fagus sylvatica L.; Quercus pyrenaica Willd.