A Survey of the Relationship between Climatic Heat Stress Indices and Fundamental Milk Components Considering Uncertainty

The main purpose of this study is to assess the relationship between four bioclimatic indices for cattle (environmental stress, heat load, modified heat load, and respiratory rate predictor indices) and three main milk components (fat, protein, and milk yield) considering uncertainty. The climate parameters used to calculate the climate indices were taken from the NASA-Modern Era Retrospective-Analysis for Research and Applications (NASA-MERRA) reanalysis from 2002 to 2010. Cow milk data were considered for the same period from April to September when the cows use the natural pasture. The study is based on a linear regression analysis using correlations as a summarizing diagnostic. Bootstrapping is used to represent uncertainty information in the confidence intervals. The main results identify an interesting relationship between the milk compounds and climate indices under all climate conditions. During spring, there are reasonably high correlations between the fat and protein concentrations vs. the climate indices, whereas there are insignificant dependencies between the milk yield and climate indices. During summer, the correlation between the fat and protein concentrations with the climate indices decreased in comparison with the spring results, whereas the correlation for the milk yield increased. This methodology is suggested for studies investigating the impacts of climate variability/change on food and agriculture using short term data considering uncertainty.

Eliciting and encoding expert knowledge on variable selection into classical or Bayesian species distribution models

The quality of species distribution models (SDMs) relies to a large degree on the quality of the input data, from bioclimatic indices to environmental and habitat descriptors (Austin, 2002). Recent reviews of SDM techniques, have sought to optimize predictive performance e.g. Elith et al., 2006. In general SDMs employ one of three approaches to variable selection. The simplest approach relies on the expert to select the variables, as in environmental niche models Nix, 1986 or a generalized linear model without variable selection (Miller and Franklin, 2002). A second approach explicitly incorporates variable selection into model fitting, which allows examination of particular combinations of variables. Examples include generalized linear or additive models with variable selection (Hastie et al. 2002); or classification trees with complexity or model based pruning (Breiman et al., 1984, Zeileis, 2008). A third approach uses model averaging, to summarize the overall contribution of a variable, without considering particular combinations. Examples include neural networks, boosted or bagged regression trees and Maximum Entropy as compared in Elith et al. 2006. Typically, users of SDMs will either consider a small number of variable sets, via the first approach, or else supply all of the candidate variables (often numbering more than a hundred) to the second or third approaches. Bayesian SDMs exist, with several methods for eliciting and encoding priors on model parameters (see review in Low Choy et al. 2010). However few methods have been published for informative variable selection; one example is Bayesian trees (O’Leary 2008). Here we report an elicitation protocol that helps makes explicit a priori expert judgements on the quality of candidate variables. This protocol can be flexibly applied to any of the three approaches to variable selection, described above, Bayesian or otherwise. We demonstrate how this information can be obtained then used to guide variable selection in classical or machine learning SDMs, or to define priors within Bayesian SDMs.

Macroclimate and viticultural zoning in Europe: observed trends and atmospheric forcing

Temperature and precipitation are major forcing factors influencing grapevine phenology and yield, as well as wine quality. Bioclimatic indices describing the suitability of a particular region for wine production are a commonly used tool for viticultural zoning. For this research these indices were computed for Europe by using the E-OBS gridded daily temperature and precipitation data set for the period from 1950 to 2009. Results showed strong regional contrasts based on the different index patterns and reproduced the wide diversity of local conditions that largely explain the quality and diversity of grapevines being grown across Europe. Owing to the strong inter-annual variability in the indices, a trend analysis and a principal component analysis were applied together with an assessment of their mean patterns. Significant trends were identified in the Winkler and Huglin indices, particularly for southwestern Europe. Four statistically significant orthogonal modes of variability were isolated for the Huglin index (HI), jointly representing 82% of the total variance in Europe. The leading mode was largely dominant (48% of variance) and mainly reflected the observed historical long-term changes. The other 3 modes corresponded to regional dipoles within Europe. Despite the relevance of local and regional climatic characteristics to grapevines, it was demonstrated via canonical correlation analysis that the observed inter-annual variability of the HI was strongly controlled by the large-scale atmospheric circulation during the growing season (April to September).

Climate change scenarios applied to viticultural zoning in Europe

Climate is one of the main factors controlling winegrape production. Bioclimatic indices describing the suitability of a particular region for wine production are a widely used zoning tool. Seven suitable bioclimatic indices characterize regions in Europe with different viticultural suitability, and their possible geographical shifts under future climate conditions are addressed using regional climate model simulations. The indices are calculated from climatic variables (daily values of temperature and precipitation) obtained from transient ensemble simulations with the regional model COSMO-CLM. Index maps for recent decades (1960–2000) and for the 21st century (following the IPCC-SRES B1 and A1B scenarios) are compared. Results show that climate change is projected to have a significant effect on European viticultural geography. Detrimental impacts on winegrowing are predicted in southern Europe, mainly due to increased dryness and cumulative thermal effects during the growing season. These changes represent an important constraint to grapevine growth and development, making adaptation strategies crucial, such as changing varieties or introducing water supply by irrigation. Conversely, in western and central Europe, projected future changes will benefit not only wine quality, but might also demarcate new potential areas for viticulture, despite some likely threats associated with diseases. Regardless of the inherent uncertainties, this approach provides valuable information for implementing proper and diverse adaptation measures in different European regions.

Viticultura y Cambio Climático en España: Vulnerabilidad en las distintas regiones y estrategias de adaptación frente al desarrollo de nuevas políticas

El presente trabajo realiza un análisis de la vulnerabilidad de la viticultura en España ante el Cambio Climático que contribuya a la mejora de la capacidad de respuesta del sector vitivinícola a la hora de afrontar los retos de la globalización. Para ello se analiza el impacto que puede tener el Cambio Climático en primer lugar sobre determinados riesgos ocasionados por eventos climáticos adversos relacionados con extremos climáticos y en segundo lugar, sobre los principales índices agro-climáticos definidos en el Sistema de Clasificación Climática Multicriterio Geoviticultura (MCGG), que permiten clasificar las zonas desde un punto de vista de su potencial climático. Para el estudio de las condiciones climáticas se han utilizado los escenarios de Cambio Climático regionalizados del proyecto ESCENA, desarrollados dentro del Plan Nacional de Adaptación al Cambio Climático (PNACC) con el fin de promover iniciativas de anticipación y respuesta al Cambio Climático hasta el año 2050. Como parte clave del estudio de la vulnerabilidad, en segundo lugar se miden las necesidades de adaptación para 56 Denominaciones de Origen Protegidas, definidas por los impactos y de acuerdo con un análisis de sensibilidad desarrollado en este trabajo. De este análisis se desprende que los esfuerzos de adaptación se deberían centrar en el mantenimiento de la calidad sobre todo para mejorar las condiciones en la época de maduración en los viñedos de la mitad norte, mientras que en las zonas de la mitad sur y del arco mediterráneo, además deberían buscar mantener la productividad en la viticultura. Los esfuerzos deberían ser más intensos en esta zona sur y también estarían sujetos a más limitaciones, ya que por ejemplo el riego, que podría llegar a ser casi obligatorio para mantener el cultivo, se enfrentaría a un contexto de mayor competencia y escasez de recursos hídricos. La capacidad de afrontar estas necesidades de adaptación determinará la vulnerabilidad del viñedo en cada zona en el futuro. Esta capacidad está definida por las propias necesidades y una serie de condicionantes sociales y de limitaciones legales, como las impuestas por las propias Denominaciones de Origen, o medioambientales, como la limitación del uso de agua. El desarrollo de estrategias que aseguren una utilización sostenible de los recursos hídricos, así como el apoyo de las Administraciones dentro de la nueva Política Agraria Común (PAC) pueden mejorar esta capacidad de adaptación y con ello disminuir la vulnerabilidad. ABSTRACT This paper analyzes the vulnerability of viticulture in Spain on Climate Change in order to improve the adaptive capacity of the wine sector to meet the diverse challenges of globalization. The risks to quality and quantity are explored by considering bioclimatic indices with specific emphasis on the Protected Designation of Origin areas that produce the premium winegrapes. The Indices selected represents risks caused by adverse climatic events related to climate extremes, and requirements of varieties and vintage quality in the case of those used in the Multicriteria Climatic Classification System. (MCCS). To study the climatic conditions, an ensemble of Regional Climate Models (RCMs) of ESCENA project, developed in the framework of the Spanish Plan for Regional Climate Change Scenarios (PNACC-2012) have been used As a key part of the study of vulnerability risks and opportunities are linked to adaptation needs across the Spanish territory. Adaptation efforts are calculated as proportional to the magnitude of change and according to a sensitivity analysis for 56 protected designations of origin. This analysis shows that adaptation efforts should focus on improving conditions in the ripening period to maintain quality in the vineyards of the northern half of Iberian Peninsula, while in areas of the southern half and in the Mediterranean basin, also should seek to maintain productivity of viticulture. Therefore, efforts should be more intense in the Southern and Eastern part, and may also be subject to other limitations, such as irrigation, which could become almost mandatory to keep growing, would face a context of increased competition and lack of resources water. The ability to meet these needs will determine the vulnerability of the vineyard in each region in the future. This capability is defined also by a number of social factors and legal limitations such as environmental regulations, limited water resources or those imposed by their own Designation of Origin. The development of strategies to ensure sustainable use of water resources and the support schemes in the new Common Agricultural Policy (CAP) can improve the resilience and thus reduce vulnerability.

Sensaciones térmicas en la provincia Cienfuegos (Cuba)

Los estudios referentes a las sensaciones térmicas son de gran interés y utilidad en diferentes sectores de la sociedad, máxime en la provincia Cienfuegos (Cuba) donde existe un alto potencial económico en continuo desarrollo. Es por eso que este trabajo tiene como objetivo caracterizar temporal y espacialmente las sensaciones térmicas en horarios extremos del día en la provincia Cienfuegos durante el período 1981-2010. Para ello se calcularon los índices bioclimáticos Temperatura Efectiva-TE y Temperatura Efectiva Equivalente-TEE los cuales resultan adecuados para evaluar las sensaciones térmicas de los cubanos aclimatados a las condiciones cálidas y húmedas. Como principales resultados se obtuvo que en la provincia, las mañanas de noviembre a abril son generalmente frescas mientras las tardes de ese período pueden ser confortables o calurosas. Esta última situación es común en las mañanas de mayo a octubre cambiando a calurosas o muy calurosas en horas de la tarde. Las mayores diferencias espaciales se encontraron entre el litoral sur oriental y la zona montañosa resaltando esta última por una permanencia de sensaciones frescas o confortables.

The Effect of Climate Variability on Main Components of Cow Milk in Iran

The main purpose of this study is to assess the relationship between six bioclimatic indices for cattle (temperature humidity (THI), environmental stress (ESI), equivalent temperature (ESI), heat load (HLI), modified heat load (HLInew) and respiratory rate predictor(RRP)) and fundamental milk components (fat, protein, and milk yield) considering uncertainty. The climate parameters used to calculate the climate indices were taken from the NASA-Modern Era Retrospective-Analysis for Research and Applications (NASA-MERRA) reanalysis from 2002 to 2010. Cow milk data were considered for the same period from April to September when cows use natural pasture, with possibility for cows to choose to stay in the barn or to graze on the pasture in the pasturing system. The study is based on a linear regression analysis using correlations as a summarizing diagnostic. Bootstrapping is used to represent uncertainty estimation through resampling in the confidence intervals. To find the relationships between climate indices (THI, ETI, HLI, HLInew, ESI and RRP) and main components of cow milk (fat, protein and yield), multiple liner regression is applied. The least absolute shrinkage selection operator (LASSO) and the Akaike information criterion (AIC) techniques are applied to select the best model for milk predictands with the smallest number of climate predictors. Cross validation is used to avoid over-fitting. Based on results of investigation the effect of heat stress indices on milk compounds separately, we suggest the use of ESI and RRP in the summer and ESI in the spring. THI and HLInew are suggested for fat content and HLInew also is suggested for protein content in the spring season. The best linear models are found in spring between milk yield as predictands and THI, ESI,HLI, ETI and RRP as predictors with p-value < 0.001 and R2 0.50, 0.49. In summer, milk yield with independent variables of THI, ETI and ESI show the highest relation (p-value < 0.001) with R2 (0.69). For fat and protein the results are only marginal. It is strongly suggested that new and significant indices are needed to control critical heat stress conditions that consider more predictors of the effect of climate variability on animal products, such as sunshine duration, quality of pasture, the number of days of stress (NDS), the color of skin with attention to large black spots, and categorical predictors such as breed, welfare facility, and management system. This methodology is suggested for studies investigating the impacts of climate variability/change on food quality/security, animal science and agriculture using short term data considering uncertainty or data collection is expensive, difficult, or data with gaps.

Régionalisation et synthèse des patrons de la végétation du Québec : utilisation d'indices de patrons à l'échelle provinciale.

Le Québec est une immense province à l’intérieur de laquelle existe une grande diversité de conditions bioclimatiques et où les perturbations anthropiques et naturelles du couvert végétal sont nombreuses. À l’échelle provinciale, ces multiples facteurs interagissent pour sculpter la composition et la distribution des paysages. Les objectifs généraux de cette recherche visaient à explorer et comprendre la distribution spatiale des patrons des paysages du Québec, de même qu’à caractériser les patrons observés à partir d’images satellitaires. Pour ce faire, les patrons des paysages ont été quantifiés avec un ensemble complet d’indices calculés à partir d’une cartographie de la couverture végétale. Plusieurs approches ont été développées et appliquées pour interpréter les valeurs d’indices sur de vastes étendues et pour cartographier la distribution des patrons des paysages québécois. Les résultats ont révélé que les patrons de la végétation prédits par le Ministère des Ressources naturelles du Québec divergent des patrons de la couverture végétale observée. Ce mémoire dresse un portrait des paysages québécois et les synthétise de manière innovatrice, en plus de démontrer le potentiel d’utilisation des indices comme attributs biogéographiques à l’échelle nationale.

The taxonomic distinctness of macroinvertebrate communities of Atlantic Forest streams cannot be predicted by landscape and climate variables, but traditional biodiversity indices can

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Static load modelling and voltage stability indices

This paper analyzes the performance of some of the widely used voltage stability indices, namely, singular value, eigenvalue, and loading margin with different static load models. Well-known ZIP model is used to represent loads having components with different power to voltage sensitivities. Studies are carried out on a 10-bus power system and the New England 39-bus power system models. The effects of variation of load model on the performance of the voltage stability indices are discussed. The choice of voltage stability index in the context of load modelling is also suggested in this paper.

The development and validation of Australian indices of child development - Part II : validity support

The two outcome indices described in a companion paper (Sanson et al., Child Indicators Research, 2009) were developed using data from the Longitudinal Study of Australian Children (LSAC). These indices, one for infants and the other for 4 year to 5 year old children, were designed to fill the need for parsimonious measures of children’s developmental status to be used in analyses by a broad range of data users and to guide government policy and interventions to support young children’s optimal development. This paper presents evidence from Wave 1data from LSAC to support the validity of these indices and their three domain scores of Physical, Social/Emotional, and Learning. Relationships between the indices and child, maternal, family, and neighborhood factors which are known to relate concurrently to child outcomes were examined. Meaningful associations were found with the selected variables, thereby demonstrating the usefulness of the outcome indices as tools for understanding children’s development in their family and socio-cultural contexts. It is concluded that the outcome indices are valuable tools for increasing understanding of influences on children’s development, and for guiding policy and practice to optimize children’s life chances.

The development and validation of Australian Indices of Child Development — Part I: conceptualisation and development

The Longitudinal Study of Australian Children (LSAC) is a major national study examining the lives of Australian children, using a cross-sequential cohort design and data from parents, children, and teachers for 5,107 infants (3–19 months) and 4,983 children (4–5 years). Its data are publicly accessible and are used by researchers from many disciplinary backgrounds. It contains multiple measures of children’s developmental outcomes as well as a broad range of information on the contexts of their lives. This paper reports on the development of summary outcome indices of child development using the LSAC data. The indices were developed to fill the need for indicators suitable for use by diverse data users in order to guide government policy and interventions which support young children’s optimal development. The concepts underpinning the indices and the methods of their development are presented. Two outcome indices (infant and child) were developed, each consisting of three domains—health and physical development, social and emotional functioning, and learning competency. A total of 16 measures are used to make up these three domains in the Outcome Index for the Child Cohort and six measures for the Infant Cohort. These measures are described and evidence supporting the structure of the domains and their underlying latent constructs is provided for both cohorts. The factorial structure of the Outcome Index is adequate for both cohorts, but was stronger for the child than infant cohort. It is concluded that the LSAC Outcome Index is a parsimonious measure representing the major components of development which is suitable for non-specialist data users. A companion paper (Sanson et al. 2010) presents evidence of the validity of the Index.

Power system stability analysis based on descriptive study of electrical indices

In a power network, when a propagation energy wave caused by a disturbance hits a weak link, a reflection is appeared and some of energy is transferred across the link. In this work, an analytical descriptive methodology is proposed to study the dynamical stability of a large scale power system. For this purpose, the measured electrical indices (angle, or voltage/frequency) following a fault in different points among the network are used, and the behaviors of the propagated waves through the lines, nodes and buses are studied. This work addresses a new tool for power system stability analysis based on a descriptive study of electrical measurements. The proposed methodology is also useful to detect the contingency condition and synthesis of an effective emergency control scheme.