Estudios sobre la dieta en piqueros como indicadores de la estructura por tallas de los stocks de Anchoveta en el mar peruano

Las tallas de anchoveta consumida por el piquero Sula variegata fueron comparadas con aquéllas capturadas por la pesquería industrial, tanto a partir de datos generales como son los desembarques en los puertos, como a partir de datos precisos como son la captura en embarcaciones que trabajan en áreas cercanas a las islas de estudio. El presente trabajo busca demostrar que la información que se obtiene por intermedio de la dieta de los piqueros puede suplir la carencia de datos provenientes de la pesquería. No se encontraron diferencias significativas al comparar las tallas de anchoveta consumida por piqueros y la capturada por la pesquería en la mayoría de los casos (92,86% con puertos y el 85,71 % con embarcaciones). Los índices de similitud fueron elevados (>0,60) en el 78,57% de las comparaciones con puertos (n=28) y el 85,71 % con embarcaciones (n=7). Correlaciones superiores a 0,70 resultaron del 75% de las relaciones con puer­tos y del 71,43% con embarcaciones; valores de 0,70 equivalen a coeficientes de determinación de 0,50, que indican un 50% de variaciones debido a factores inherentes al piquero o la pesquería. Hay que considerar que existe un rango de profundidades en el cual la pesquería puede capturar parte del recurso no disponible para los piqueros y que los piqueros pueden alimentarse de cardúmenes de anchoveta de menor tamaño que podrían no ser de interés para la pesquería, estos serían en todo caso los factores responsables. Los resultados obtenidos muestran que los estudios sobre la dieta de piqueros pueden ser útiles en el monitoreo de la estructura por tallas del stock de anchoveta, sobre todo en períodos de veda, ante la ausencia de información oportuna proveniente de los desembarques.

Margin requirements and volatility : evidence from Canadian stocks

Margin policy is used by regulators for the purpose of inhibiting exceSSIve volatility and stabilizing the stock market in the long run. The effect of this policy on the stock market is widely tested empirically. However, most prior studies are limited in the sense that they investigate the margin requirement for the overall stock market rather than for individual stocks, and the time periods examined are confined to the pre-1974 period as no change in the margin requirement occurred post-1974 in the U.S. This thesis intends to address the above limitations by providing a direct examination of the effect of margin requirement on return, volume, and volatility of individual companies and by using more recent data in the Canadian stock market. Using the methodologies of variance ratio test and event study with conditional volatility (EGARCH) model, we find no convincing evidence that change in margin requirement affects subsequent stock return volatility. We also find similar results for returns and trading volume. These empirical findings lead us to conclude that the use of margin policy by regulators fails to achieve the goal of inhibiting speculating activities and stabilizing volatility.

Diseño de software para una enseñanza interactiva de modelos de optimación en la gestión de stocks.

El proyecto se realiza en la Universidad de Valladolid, en los Departamentos de Estadística e Investigación Operativa (con la participación de un profesor) y Matemática Aplicada a la Técnica (tres profesores). Los objetivos son: 1. Diseño de un material informático que, manejado por el profesor, permita la enseñanza interactiva de los modelos de optimación en el aula, y que a su vez, proporcione al alumno un material docente complementario a sus apuntes para el estudio progresivo de la asignatura. 2. Aportar un software de optimación básicamente educativo que permita al alumno enfrentarse y resolver muchos de los problemas con los que se encontrará en el mundo empresarial. Las materias tratadas corresponden a diferentes asignaturas de Investigación Operativa que aparecen en los planes de estudio de las titulaciones de Diplomado en Estadistica, Ingeniero Técnico en Informática de Sistemas e Ingenieros Técnico en Informática de Gestión de la Universidad de Valladolid. El sistema de trabajo consistió en reuniones periodicas en las que todo el equipo debatía sobre las propuetas de diseño elaboradas por uno o dos miembros del mismo, teniendo en cuenta, entre otros aspectos, lo observado en las clases de laboratorio y tutorías con los alumnos. El desarrollo del proceso se llevó a cabo en los ámbitos de los estudios de la Diplomatura en Estadística (Facultad de Ciencias de Valladolid) y de los estudios de Ingeniería Técnica en Informática de Sistemas y de Ingeniería Técnica en Informática de Gestión (Escuela Técnica Superior de Ingeniería Informática de Valladolid). Resultados: Aunque por falta de tiempo no se ha llevado acabo una evaluación formalmente explícita, sí que se han constatado palpablemente las ventajas que, para favorecer el aprendizaje de los alumnos, la motivación de los estudios, la potenciación de la eficacia de las prácticas y el fomento del trabajo en equipo, ha tenido el trabajo realizado. Se han desarrollado ocho módulos de trabajo sobre modelos de optimización en la gestión de stocks (cinco para casos determinísticos y tres para casos estocásticos). Para cada módulo se ha diseñado el correspondiente software usando los paquetes EXCEL Y LINGO. Todo ello se incluye en un CD. Los materiales utilizados en el proyecto son: libros de Teoría de Inventarios para los fundamentos teóricos, libros de técnicas de diseño de software para la parte práctica y ordenadores para la elaboración de software. El material elaborado no está publicado.

Predicted soil organic carbon stocks and changes in Jordan between 2000 and 2030 made using the GEFSOC modelling system

Estimates of soil organic carbon (SOC) stocks and changes under different land use systems can help determine vulnerability to land degradation. Such information is important for countries in and areas with high susceptibility to desertification. SOC stocks, and predicted changes between 2000 and 2030, were determined at the national scale for Jordan using The Global Environment Facility Soil Organic Carbon (GEFSOC) Modelling System. For the purpose of this study, Jordan was divided into three natural regions (The Jordan Valley, the Uplands and the Badia) and three developmental regions (North, Middle and South). Based on this division, Jordan was divided into five zones (based on the dominant land use): the Jordan Valley, the North Uplands, the Middle Uplands, the South Uplands and the Badia. This information was merged using GIS, along with a map of rainfall isohyets, to produce a map with 498 polygons. Each of these was given a unique ID, a land management unit identifier and was characterized in terms of its dominant soil type. Historical land use data, current land use and future land use change scenarios were also assembled, forming major inputs of the modelling system. The GEFSOC Modelling System was then run to produce C stocks in Jordan for the years 1990, 2000 and 2030. The results were compared with conventional methods of estimating carbon stocks, such as the mapping based SOTER method. The results of these comparisons showed that the model runs are acceptable, taking into consideration the limited availability of long-term experimental soil data that can be used to validate them. The main findings of this research show that between 2000 and 2030, SOC may increase in heavily used areas under irrigation and will likely decrease in grazed rangelands that cover most of Jordan giving an overall decrease in total SOC over time if the land is indeed used under the estimated forms of land use. (C) 2007 Elsevier B.V. All rights reserved.

Modelled soil organic carbon stocks and changes in the Indo-Gangetic Plains, India from 1980 to 2030

The Global Environment Facility co-financed Soil Organic Carbon (GEFSOC) Project developed a comprehensive modelling system for predicting soil organic carbon (SOC) stocks and changes over time. This research is an effort to predict SOC stocks and changes for the Indian, Indo-Gangetic Plains (IGP), an area with a predominantly rice (Oryza sativa) - wheat (Triticum aestivum) cropping system, using the GEFSOC Modelling System and to compare output with stocks generated using mapping approaches based on soil survey data. The GEFSOC Modelling System predicts an estimated SOC stock for the IGP, India of 1.27, 1.32 and 1.27 Pg for 1990, 2000 and 2030, respectively, in the top 20 cm of soil. The SOC stock using a mapping approach based on soil survey data was 0.66 and 0.88 Pg for 1980 and 2000, respectively. The SOC stock estimated using the GEFSOC Modelling System is higher than the stock estimated using the mapping approach. This is due to the fact that while the GEFSOC System accounts for variation in crop input data (crop management), the soil mapping approach only considers regional variation in soil texture and wetness. The trend of overall change in the modelled SOC stock estimates shows that the IGP, India may have reached an equilibrium following 30-40 years of the Green Revolution. This can be seen in the SOC stock change rates. Various different estimation methods show SOC stocks of 0.57-1.44 Pg C for the study area. The trend of overall change in C stock assessed from the soil survey data indicates that the soils of the IGP, India may store a projected 1.1 Pg of C in 2030. (C) 2007 Elsevier B.V. All rights reserved.

Predicted soil organic carbon stocks and changes in the Brazilian Amazon between 2000 and 2030

Currently we have little understanding of the impacts of land use change on soil C stocks in the Brazilian Amazon. Such information is needed to determine impacts'6n the global C cycle and the sustainability of agricultural systems that are replacing native forest. The aim of this study was to predict soil carbon stocks and changes in the Brazilian Amazon during the period between 2000 and 2030, using the GEFSOC soil carbon (C) modelling system. In order to do so, we devised current and future land use scenarios for the Brazilian Amazon, taking into account: (i) deforestation, rates from the past three decades, (ii) census data on land use from 1940 to 2000, including the expansion and intensification of agriculture in the region, (iii) available information on management practices, primarily related to well managed pasture versus degraded pasture and conventional systems versus no-tillage systems for soybean (Glycine max) and (iv) FAO predictions on agricultural land use and land use changes for the years 2015 and 2030. The land use scenarios were integrated with spatially explicit soils data (SOTER database), climate, potential natural vegetation and land management units using the recently developed GEFSOC soil C modelling system. Results are presented in map, table and graph form for the entire Brazilian Amazon for the current situation (1990 and 2000) and the future (2015 and 2030). Results include soil organic C (SOC) stocks and SOC stock change rates estimated by three methods: (i) the Century ecosystem model, (ii) the Rothamsted C model and (iii) the intergovernmental panel on climate change (IPCC) method for assessing soil C at regional scale. In addition, we show estimated values of above and belowground biomass for native vegetation, pasture and soybean. The results on regional SOC stocks compare reasonably well with those based on mapping approaches. The GEFSOC system provided a means of efficiently handling complex interactions among biotic-edapho-climatic conditions (> 363,000 combinations) in a very large area (similar to 500 Mha) such as the Brazilian Amazon. All of the methods used showed a decline in SOC stock for the period studied; Century and RothC simulated values for 2030 being about 7% lower than those in 1990. Values from Century and RothC (30,430 and 25,000 Tg for the 0-20 cm layer for the Brazilian Amazon region were higher than those obtained from the IPCC system (23,400 Tg in the 0-30 cm layer). Finally; our results can help understand the major biogeochemical cycles that influence soil fertility and help devise management strategies that enhance the sustainability of these areas and thus slow further deforestation. (C) 2007 Elsevier B.V. All rights reserved.

Predicted soil organic carbon stocks and changes in Kenya between 1990 and 2030

Under the United Nations Framework Convention on Climate Change (UNFCCC), Non-Annex 1 countries such as Kenya are obliged to report green house gas (GHG) emissions from all sources where possible, including those from soils as a result of changes in land use or land management. At present, the convention encourages countries to estimate emissions using the most advanced methods possible, given the country circumstances and resources. Estimates of soil organic carbon (SOC) stocks and changes were made for Kenya using the Global Environment Facility Soil Organic Carbon (GEFSOC) Modelling System. The tool conducts analysis using three methods: (1) the Century general ecosystem model; (2) the RothC soil C decomposition model; and (3) the Intergovernmental Panel on Climate Change (IPCC) method for assessing soil C at regional scales. The required datasets included: land use history, monthly mean precipitation, monthly mean minimum and maximum temperatures for all the agro-climatic zones of Kenya and historical vegetation cover. Soil C stocks of 1.4-2.0 Pg (0-20 cm), compared well with a Soil and Terrain (SOTER) based approach that estimated similar to .8-2.0 Pg (0-30 cm). In 1990 48% of the country had SOC stocks of < 18 t C ha(-1) and 20% of the country had SOC stocks of 18-30 t C ha(-1), whereas in 2000 56% of the country had SOC stocks of < 18 t C ha(-1) and 31% of the country had SOC stocks of 18-30 t C ha(-1). Conversion of natural vegetation to annual crops led to the greatest soil C losses. Simulations suggest that soil C losses remain substantial throughout the modelling period of 1990-2030. All three methods involved in the GEFSOC System estimated that there would be a net loss of soil C between 2000 and 2030 in Kenya. The decline was more marked with RothC than with Century or the IPCC method. In non-hydric soils the SOC change rates were more pronounced in high sandy soils compared to high clay soils in most land use systems. (C) 2007 Elsevier B.V. All rights reserved.

National and sub-national assessments of soil organic carbon stocks and changes: The GEFSOC modelling system

Soil organic carbon (SOC) plays a vital role in ecosystem function, determining soil fertility, water holding capacity and susceptibility to land degradation. In addition, SOC is related to atmospheric CO, levels with soils having the potential for C release or sequestration, depending on land use, land management and climate. The United Nations Convention on Climate Change and its Kyoto Protocol, and other United Nations Conventions to Combat Desertification and on Biodiversity all recognize the importance of SOC and point to the need for quantification of SOC stocks and changes. An understanding of SOC stocks and changes at the national and regional scale is necessary to further our understanding of the global C cycle, to assess the responses of terrestrial ecosystems to climate change and to aid policy makers in making land use/management decisions. Several studies have considered SOC stocks at the plot scale, but these are site specific and of limited value in making inferences about larger areas. Some studies have used empirical methods to estimate SOC stocks and changes at the regional scale, but such studies are limited in their ability to project future changes, and most have been carried out using temperate data sets. The computational method outlined by the Intergovernmental Panel on Climate Change (IPCC) has been used to estimate SOC stock changes at the regional scale in several studies, including a recent study considering five contrasting eco regions. This 'one step' approach fails to account for the dynamic manner in which SOC changes are likely to occur following changes in land use and land management. A dynamic modelling approach allows estimates to be made in a manner that accounts for the underlying processes leading to SOC change. Ecosystem models, designed for site scale applications can be linked to spatial databases, giving spatially explicit results that allow geographic areas of change in SOC stocks to be identified. Some studies have used variations on this approach to estimate SOC stock changes at the sub-national and national scale for areas of the USA and Europe and at the watershed scale for areas of Mexico and Cuba. However, a need remained for a national and regional scale, spatially explicit system that is generically applicable and can be applied to as wide a range of soil types, climates and land uses as possible. The Global Environment Facility Soil Organic Carbon (GEFSOC) Modelling System was developed in response to this need. The GEFSOC system allows estimates of SOC stocks and changes to be made for diverse conditions, providing essential information for countries wishing to take part in an emerging C market, and bringing us closer to an understanding of the future role of soils in the global C cycle. (C) 2007 Elsevier B.V. All rights reserved.

Global climate change and soil carbon stocks: predictions from two contrasting models for the turnover of organic carbon in soil

Enhanced release of CO2 to the atmosphere from soil organic carbon as a result of increased temperatures may lead to a positive feedback between climate change and the carbon cycle, resulting in much higher CO2 levels and accelerated lobal warming. However, the magnitude of this effect is uncertain and critically dependent on how the decomposition of soil organic C (heterotrophic respiration) responds to changes in climate. Previous studies with the Hadley Centre’s coupled climate–carbon cycle general circulation model (GCM) (HadCM3LC) used a simple, single-pool soil carbon model to simulate the response. Here we present results from numerical simulations that use the more sophisticated ‘RothC’ multipool soil carbon model, driven with the same climate data. The results show strong similarities in the behaviour of the two models, although RothC tends to simulate slightly smaller changes in global soil carbon stocks for the same forcing. RothC simulates global soil carbon stocks decreasing by 54 GtC by 2100 in a climate change simulation compared with an 80 GtC decrease in HadCM3LC. The multipool carbon dynamics of RothC cause it to exhibit a slower magnitude of transient response to both increased organic carbon inputs and changes in climate. We conclude that the projection of a positive feedback between climate and carbon cycle is robust, but the magnitude of the feedback is dependent on the structure of the soil carbon model.

Explaining deviations from NAV in UK property companies: rationality and sentimentality

One of the most vexing issues for analysts and managers of property companies across Europe has been the existence and persistence of deviations of Net Asset Values of property companies from their market capitalisation. The issue has clear links to similar discounts and premiums in closed-end funds. The closed end fund puzzle is regarded as an important unsolved problem in financial economics undermining theories of market efficiency and the Law of One Price. Consequently, it has generated a huge body of research. Although it can be tempting to focus on the particular inefficiencies of real estate markets in attempting to explain deviations from NAV, the closed end fund discount puzzle indicates that divergences between underlying asset values and market capitalisation are not a ‘pure’ real estate phenomenon. When examining potential explanations, two recurring factors stand out in the closed end fund literature as often undermining the economic rationale for a discount – the existence of premiums and cross-sectional and periodic fluctuations in the level of discount/premium. These need to be borne in mind when considering potential explanations for real estate markets. There are two approaches to investigating the discount to net asset value in closed-end funds: the ‘rational’ approach and the ‘noise trader’ or ‘sentiment’ approach. The ‘rational’ approach hypothesizes the discount to net asset value as being the result of company specific factors relating to such factors as management quality, tax liability and the type of stocks held by the fund. Despite the intuitive appeal of the ‘rational’ approach to closed-end fund discounts the studies have not successfully explained the variance in closed-end fund discounts or why the discount to net asset value in closed-end funds varies so much over time. The variation over time in the average sector discount is not only a feature of closed-end funds but also property companies. This paper analyses changes in the deviations from NAV for UK property companies between 2000 and 2003. The paper present a new way to study the phenomenon ‘cleaning’ the gearing effect by introducing a new way of calculating the discount itself. We call it “ungeared discount”. It is calculated by assuming that a firm issues new equity to repurchase outstanding debt without any variation on asset side. In this way discount does not depend on an accounting effect and the analysis should better explain the effect of other independent variables.

Protecting degraded rainforests: enhancement of forest carbon stocks under REDD+

The likely Reducing Emissions from Deforestation and Degradation (REDD+) mechanism includes strategies for the enhancement of forest carbon stocks. Recent concerns have been expressed that such enhancement, or restoration, of forest carbon could be counterproductive to biodiversity conservation, because forests are managed as “carbon farms” with the application of intensive silvicultural management that could homogenize diverse degraded rainforests. Restoration increases regeneration rates in degraded forest compared to naturally regenerating forest, and thus could yield significant financial returns for carbon sequestered. Here, we argue that such forest restoration projects are, in fact, likely to provide a number of benefits to biodiversity conservation including the retention of biodiversity, the prevention of forest conversion to agriculture, and employment opportunities for poor local communities. As with other forms of forest-based carbon offsets, there are possible moral hazard and leakage problems with restoration. However, due to the multiple benefits, we urge that enhancement of forest carbon stocks be detailed as a major component in the future negotiations of REDD+.

How will organic carbon stocks in mineral soils evolve under future climate? Global projections using RothC for a range of climate change scenarios

We use a soil carbon (C) model (RothC), driven by a range of climate models for a range of climate scenarios to examine the impacts of future climate on global soil organic carbon (SOC) stocks. The results suggest an overall global increase in SOC stocks by 2100 under all scenarios, but with a different extent of increase among the climate model and emissions scenarios. The impacts of projected land use changes are also simulated, but have relatively minor impacts at the global scale. Whether soils gain or lose SOC depends upon the balance between C inputs and decomposition. Changes in net primary production (NPP) change C inputs to the soil, whilst decomposition usually increases under warmer temperatures, but can also be slowed by decreased soil moisture. Underlying the global trend of increasing SOC under future climate is a complex pattern of regional SOC change. SOC losses are projected to occur in northern latitudes where higher SOC decomposition rates due to higher temperatures are not balanced by increased NPP, whereas in tropical regions, NPP increases override losses due to higher SOC decomposition. The spatial heterogeneity in the response of SOC to changing climate shows how delicately balanced the competing gain and loss processes are, with subtle changes in temperature, moisture, soil type and land use, interacting to determine whether SOC increases or decreases in the future. Our results suggest that we should stop looking for a single answer regarding whether SOC stocks will increase or decrease under future climate, since there is no single answer. Instead, we should focus on improving our prediction of the factors that determine the size and direction of change, and the land management practices that can be implemented to protect and enhance SOC stocks.