856 resultados para Socio-ecological models
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The International Long-Term Ecological Research (ILTER) network comprises > 600 scientific groups conducting site-based research within 40 countries. Its mission includes improving the understanding of global ecosystems and informs solutions to current and future environmental problems at the global scales. The ILTER network covers a wide range of social-ecological conditions and is aligned with the Programme on Ecosystem Change and Society (PECS) goals and approach. Our aim is to examine and develop the conceptual basis for proposed collaboration between ILTER and PECS. We describe how a coordinated effort of several contrasting LTER site-based research groups contributes to the understanding of how policies and technologies drive either toward or away from the sustainable delivery of ecosystem services. This effort is based on three tenets: transdisciplinary research; cross-scale interactions and subsequent dynamics; and an ecological stewardship orientation. The overarching goal is to design management practices taking into account trade-offs between using and conserving ecosystems toward more sustainable solutions. To that end, we propose a conceptual approach linking ecosystem integrity, ecosystem services, and stakeholder well-being, and as a way to analyze trade-offs among ecosystem services inherent in diverse management options. We also outline our methodological approach that includes: (i) monitoring and synthesis activities following spatial and temporal trends and changes on each site and by documenting cross-scale interactions; (ii) developing analytical tools for integration; (iii) promoting trans-site comparison; and (iv) developing conceptual tools to design adequate policies and management interventions to deal with trade-offs. Finally, we highlight the heterogeneity in the social-ecological setting encountered in a subset of 15 ILTER sites. These study cases are diverse enough to provide a broad cross-section of contrasting ecosystems with different policy and management drivers of ecosystem conversion; distinct trends of biodiversity change; different stakeholders’ preferences for ecosystem services; and diverse components of well-being issues.
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PURPOSE: The use of information and communication technology (ICT) is common in modern working life. ICT demands may give rise to experience of work-related stress. Knowledge about ICT demands in relation to other types of work-related stress and to self-rated health is limited. Consequently, the aim of this study was to examine the association between ICT demands and two types of work-related stress [job strain and effort-reward imbalance (ERI)] and to evaluate the association between these work-related stress measures and self-rated health, in general and in different SES strata. METHODS: This study is based on cross-sectional data from the Swedish Longitudinal Occupational Survey of Health collected in 2014, from 14,873 gainfully employed people. ICT demands, job strain, ERI and self-rated health were analysed as the main measures. Sex, age, SES, lifestyle factors and BMI were used as covariates. RESULTS: ICT demands correlated significantly with the dimensions of the job strain and ERI models, especially with the demands (r = 0.42; p < 0.01) and effort (r = 0.51; p < 0.01) dimensions. ICT demands were associated with suboptimal self-rated health, also after adjustment for age, sex, SES, lifestyle and BMI (OR 1.49 [95 % CI 1.36-1.63]), but job strain (OR 1.93 [95 % CI 1.74-2.14) and ERI (OR 2.15 [95 % CI 1.95-2.35]) showed somewhat stronger associations with suboptimal self-rated health. CONCLUSION: ICT demands are common among people with intermediate and high SES and associated with job strain, ERI and suboptimal self-rated health. ICT demands should thus be acknowledged as a potential stressor of work-related stress in modern working life.
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A recent focus on contemporary evolution and the connections between communities has sought to more closely integrate the fields of ecology and evolutionary biology. Studies of coevolutionary dynamics, life history evolution, and rapid local adaptation demonstrate that ecological circumstances can dictate evolutionary trajectories. Thus, variation in species identity, trait distributions, and genetic composition may be maintained among ecologically divergent habitats. New theories and hypotheses (e.g., metacommunity theory and the Monopolization hypothesis) have been developed to understand better the processes occurring in spatially structured environments and how the movement of individuals among habitats contributes to ecology and evolution at broader scales. As few empirical studies of these theories exist, this work seeks to further test these concepts. Spatial and temporal dispersal are the mechanisms that connect habitats to one another. Both processes allow organisms to leave conditions that are suboptimal or unfavorable, and enable colonization and invasion, species range expansion, and gene flow among populations. Freshwater zooplankton are aquatic crustaceans that typically develop resting stages as part of their life cycle. Their dormant propagules allow organisms to disperse both temporally and among habitats. Additionally, because a number of species are cyclically parthenogenetic, they make excellent model organisms for studying evolutionary questions in a controlled environment. Here, I use freshwater zooplankton communities as model systems to explore the mechanisms and consequences of dispersal and to test these nascent theories on the influence of spatial structure in natural systems. In Chapter one, I use field experiments and mathematical models to determine the range of adult zooplankton dispersal over land and what vectors are moving zooplankton. Chapter two focuses on prolonged dormancy of one aquatic zooplankter, Daphnia pulex. Using statistical models with field and mesocosm experiments, I show that variation in Daphnia dormant egg hatching is substantial among populations in nature, and some of that variation can be attributed to genetic differences among the populations. Chapters three and four explore the consequences of dispersal at multiple levels of biological organization. Chapter three seeks to understand the population level consequences of dispersal over evolutionary time on current patterns of population genetic differentiation. Nearby populations of D. pulex often exhibit high population genetic differentiation characteristic of very low dispersal. I explore two alternative hypotheses that seek to explain this pattern. Finally, chapter four is a case study of how dispersal has influenced patterns of variation at the community, trait and genetic levels of biodiversity in a lake metacommunity.
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A fundamental problem in biology is understanding how and why things group together. Collective behavior is observed on all organismic levels - from cells and slime molds, to swarms of insects, flocks of birds, and schooling fish, and in mammals, including humans. The long-term goal of this research is to understand the functions and mechanisms underlying collective behavior in groups. This dissertation focuses on shoaling (aggregating) fish. Shoaling behaviors in fish confer foraging and anti-predator benefits through social cues from other individuals in the group. However, it is not fully understood what information individuals receive from one another or how this information is propagated throughout a group. It is also not fully understood how the environmental conditions and perturbations affect group behaviors. The specific research objective of this dissertation is to gain a better understanding of how certain social and environmental factors affect group behaviors in fish. I focus on two ecologically relevant decision-making behaviors: (i) rheotaxis, or orientation with respect to a flow, and (ii) startle response, a rapid response to a perceived threat. By integrating behavioral and engineering paradigms, I detail specifics of behavior in giant danio Devario aequipinnatus (McClelland 1893), and numerically analyze mathematical models that may be extended to group behavior for fish in general, and potentially other groups of animals as well. These models that predict behavior data, as well as generate additional, testable hypotheses. One of the primary goals of neuroethology is to study an organism's behavior in the context of evolution and ecology. Here, I focus on studying ecologically relevant behaviors in giant danio in order to better understand collective behavior in fish. The experiments in this dissertation provide contributions to fish ecology, collective behavior, and biologically-inspired robotics.
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Excess nutrient loads carried by streams and rivers are a great concern for environmental resource managers. In agricultural regions, excess loads are transported downstream to receiving water bodies, potentially causing algal blooms, which could lead to numerous ecological problems. To better understand nutrient load transport, and to develop appropriate water management plans, it is important to have accurate estimates of annual nutrient loads. This study used a Monte Carlo sub-sampling method and error-corrected statistical models to estimate annual nitrate-N loads from two watersheds in central Illinois. The performance of three load estimation methods (the seven-parameter log-linear model, the ratio estimator, and the flow-weighted averaging estimator) applied at one-, two-, four-, six-, and eight-week sampling frequencies were compared. Five error correction techniques; the existing composite method, and four new error correction techniques developed in this study; were applied to each combination of sampling frequency and load estimation method. On average, the most accurate error reduction technique, (proportional rectangular) resulted in 15% and 30% more accurate load estimates when compared to the most accurate uncorrected load estimation method (ratio estimator) for the two watersheds. Using error correction methods, it is possible to design more cost-effective monitoring plans by achieving the same load estimation accuracy with fewer observations. Finally, the optimum combinations of monitoring threshold and sampling frequency that minimizes the number of samples required to achieve specified levels of accuracy in load estimation were determined. For one- to three-weeks sampling frequencies, combined threshold/fixed-interval monitoring approaches produced the best outcomes, while fixed-interval-only approaches produced the most accurate results for four- to eight-weeks sampling frequencies.
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Over time, humanity began to realize the negative impact that the modern world has caused to the environment. The Atlantic Forest is one of the richest biomes in biodiversity, covering more than 60% of all species on the planet. This biome covered about 15% of the Brazilian territory, leaving currently only 7% of its fully fragmented forest remnants. This was the biome that suffered most from modernization and strong anthropogenic pressures in Brazil. For the account of environmental degradation, in the second half of the nineteenth century there was a shift in thinking, giving greater emphasis on conservation of some natural landscapes, with the intention of removing the man still preserved nature. Based on American models of conservation there were created the Nature Conservation Units. This study aimed to analyze the environmental quality of the State Park Vitório Piassa, a Conservation Unit located in the city of Pato Branco - PR. The environmental quality was measured by use of bio-indicators and some environmental pressures that the Park has suffered over the years also were identified. Beetles of the familiy Scarabaeinae (Coleoptera: Scarabaeidae) were used as the bioindicators. To compare the most conserved areas and the most degraded areas of the Park, three specific sites were defined within the Atlantic Forest fragment, these insects were captured with pitfall traps and identified as to their species and genera. There were two collections in February and March 2015, which resulted in 945 individuals in 22 species and nine different genus. Then the population of beetles in each area were classified based on ecological measures such as species richness, abundance of individuals of each species through diversity index (Shannon and Simpson) to identify the differences between the sampled groups and equitability (Pielou) to measure the distribution of the total abundance of the species in each area. To meet the objective of identifying the environmental pressures that occur in PEVP, evidence were collected through photographs, watching the field, aerial images and conversations with the resident population in the park. Similarly, if made relevant to build on the project running by the municipality for the construction of infrastructure for public viewing. These data served as subsidies to confront the current situation of the park and the current Brazilian legislation for UC's of full protection, highlighting the existing socio-environmental conflicts in the park, involving political issues and the proximity of the Conservation Unit with the urban area of the city.
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For decades, global climate change has directly and indirectly affected the structure and function of ecosystems. Abrupt changes in biodiversity have been observed in response to linear or sudden modifications to the environment. These abrupt shifts can cause long-term reorganizations within ecosystems, with communities exhibiting new functional responses to environmental factors. Over the last 3 decades, the Gironde estuary in southwest France has experienced 2 abrupt shifts in both the physical and chemical environments and the pelagic community. Rather than describing these shifts and their origins, we focused on the 3 inter-shift periods, describing the structure of the fish community and its relationship with the environment during these periods. We described fish biodiversity using a limited set of descriptors, taking into account both species composition and relative species abundances. Inter-shift ecosystem states were defined based on the relationship between this description and the hydro-physico-chemical variables and climatic indices defining the main features of the environment. This relationship was described using generalized linear mixed models on the entire time series and for each inter-shift period. Our results indicate that (1) the fish community structure has been significantly modified, (2) environmental drivers influencing fish diversity have changed during these 3 periods, and (3) the fish-environment relationships have been modified over time. From this, we conclude a regime shift has occurred in the Gironde estuary. We also highlight that anthropogenic influences have increased, which re-emphasizes the importance of local management in maintaining fish diversity and associated goods and services within the context of climate change.
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Alors que les activités anthropiques font basculer de nombreux écosystèmes vers des régimes fonctionnels différents, la résilience des systèmes socio-écologiques devient un problème pressant. Des acteurs locaux, impliqués dans une grande diversité de groupes — allant d’initiatives locales et indépendantes à de grandes institutions formelles — peuvent agir sur ces questions en collaborant au développement, à la promotion ou à l’implantation de pratiques plus en accord avec ce que l’environnement peut fournir. De ces collaborations répétées émergent des réseaux complexes, et il a été montré que la topologie de ces réseaux peut améliorer la résilience des systèmes socio-écologiques (SSÉ) auxquels ils participent. La topologie des réseaux d’acteurs favorisant la résilience de leur SSÉ est caractérisée par une combinaison de plusieurs facteurs : la structure doit être modulaire afin d’aider les différents groupes à développer et proposer des solutions à la fois plus innovantes (en réduisant l’homogénéisation du réseau), et plus proches de leurs intérêts propres ; elle doit être bien connectée et facilement synchronisable afin de faciliter les consensus, d’augmenter le capital social, ainsi que la capacité d’apprentissage ; enfin, elle doit être robuste, afin d’éviter que les deux premières caractéristiques ne souffrent du retrait volontaire ou de la mise à l’écart de certains acteurs. Ces caractéristiques, qui sont relativement intuitives à la fois conceptuellement et dans leur application mathématique, sont souvent employées séparément pour analyser les qualités structurales de réseaux d’acteurs empiriques. Cependant, certaines sont, par nature, incompatibles entre elles. Par exemple, le degré de modularité d’un réseau ne peut pas augmenter au même rythme que sa connectivité, et cette dernière ne peut pas être améliorée tout en améliorant sa robustesse. Cet obstacle rend difficile la création d’une mesure globale, car le niveau auquel le réseau des acteurs contribue à améliorer la résilience du SSÉ ne peut pas être la simple addition des caractéristiques citées, mais plutôt le résultat d’un compromis subtil entre celles-ci. Le travail présenté ici a pour objectifs (1), d’explorer les compromis entre ces caractéristiques ; (2) de proposer une mesure du degré auquel un réseau empirique d’acteurs contribue à la résilience de son SSÉ ; et (3) d’analyser un réseau empirique à la lumière, entre autres, de ces qualités structurales. Cette thèse s’articule autour d’une introduction et de quatre chapitres numérotés de 2 à 5. Le chapitre 2 est une revue de la littérature sur la résilience des SSÉ. Il identifie une série de caractéristiques structurales (ainsi que les mesures de réseaux qui leur correspondent) liées à l’amélioration de la résilience dans les SSÉ. Le chapitre 3 est une étude de cas sur la péninsule d’Eyre, une région rurale d’Australie-Méridionale où l’occupation du sol, ainsi que les changements climatiques, contribuent à l’érosion de la biodiversité. Pour cette étude de cas, des travaux de terrain ont été effectués en 2010 et 2011 durant lesquels une série d’entrevues a permis de créer une liste des acteurs de la cogestion de la biodiversité sur la péninsule. Les données collectées ont été utilisées pour le développement d’un questionnaire en ligne permettant de documenter les interactions entre ces acteurs. Ces deux étapes ont permis la reconstitution d’un réseau pondéré et dirigé de 129 acteurs individuels et 1180 relations. Le chapitre 4 décrit une méthodologie pour mesurer le degré auquel un réseau d’acteurs participe à la résilience du SSÉ dans lequel il est inclus. La méthode s’articule en deux étapes : premièrement, un algorithme d’optimisation (recuit simulé) est utilisé pour fabriquer un archétype semi-aléatoire correspondant à un compromis entre des niveaux élevés de modularité, de connectivité et de robustesse. Deuxièmement, un réseau empirique (comme celui de la péninsule d’Eyre) est comparé au réseau archétypique par le biais d’une mesure de distance structurelle. Plus la distance est courte, et plus le réseau empirique est proche de sa configuration optimale. La cinquième et dernier chapitre est une amélioration de l’algorithme de recuit simulé utilisé dans le chapitre 4. Comme il est d’usage pour ce genre d’algorithmes, le recuit simulé utilisé projetait les dimensions du problème multiobjectif dans une seule dimension (sous la forme d’une moyenne pondérée). Si cette technique donne de très bons résultats ponctuellement, elle n’autorise la production que d’une seule solution parmi la multitude de compromis possibles entre les différents objectifs. Afin de mieux explorer ces compromis, nous proposons un algorithme de recuit simulé multiobjectifs qui, plutôt que d’optimiser une seule solution, optimise une surface multidimensionnelle de solutions. Cette étude, qui se concentre sur la partie sociale des systèmes socio-écologiques, améliore notre compréhension des structures actorielles qui contribuent à la résilience des SSÉ. Elle montre que si certaines caractéristiques profitables à la résilience sont incompatibles (modularité et connectivité, ou — dans une moindre mesure — connectivité et robustesse), d’autres sont plus facilement conciliables (connectivité et synchronisabilité, ou — dans une moindre mesure — modularité et robustesse). Elle fournit également une méthode intuitive pour mesurer quantitativement des réseaux d’acteurs empiriques, et ouvre ainsi la voie vers, par exemple, des comparaisons d’études de cas, ou des suivis — dans le temps — de réseaux d’acteurs. De plus, cette thèse inclut une étude de cas qui fait la lumière sur l’importance de certains groupes institutionnels pour la coordination des collaborations et des échanges de connaissances entre des acteurs aux intérêts potentiellement divergents.
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The long-term adverse effects on health associated with air pollution exposure can be estimated using either cohort or spatio-temporal ecological designs. In a cohort study, the health status of a cohort of people are assessed periodically over a number of years, and then related to estimated ambient pollution concentrations in the cities in which they live. However, such cohort studies are expensive and time consuming to implement, due to the long-term follow up required for the cohort. Therefore, spatio-temporal ecological studies are also being used to estimate the long-term health effects of air pollution as they are easy to implement due to the routine availability of the required data. Spatio-temporal ecological studies estimate the health impact of air pollution by utilising geographical and temporal contrasts in air pollution and disease risk across $n$ contiguous small-areas, such as census tracts or electoral wards, for multiple time periods. The disease data are counts of the numbers of disease cases occurring in each areal unit and time period, and thus Poisson log-linear models are typically used for the analysis. The linear predictor includes pollutant concentrations and known confounders such as socio-economic deprivation. However, as the disease data typically contain residual spatial or spatio-temporal autocorrelation after the covariate effects have been accounted for, these known covariates are augmented by a set of random effects. One key problem in these studies is estimating spatially representative pollution concentrations in each areal which are typically estimated by applying Kriging to data from a sparse monitoring network, or by computing averages over modelled concentrations (grid level) from an atmospheric dispersion model. The aim of this thesis is to investigate the health effects of long-term exposure to Nitrogen Dioxide (NO2) and Particular matter (PM10) in mainland Scotland, UK. In order to have an initial impression about the air pollution health effects in mainland Scotland, chapter 3 presents a standard epidemiological study using a benchmark method. The remaining main chapters (4, 5, 6) cover the main methodological focus in this thesis which has been threefold: (i) how to better estimate pollution by developing a multivariate spatio-temporal fusion model that relates monitored and modelled pollution data over space, time and pollutant; (ii) how to simultaneously estimate the joint effects of multiple pollutants; and (iii) how to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. Specifically, chapters 4 and 5 are developed to achieve (i), while chapter 6 focuses on (ii) and (iii). In chapter 4, I propose an integrated model for estimating the long-term health effects of NO2, that fuses modelled and measured pollution data to provide improved predictions of areal level pollution concentrations and hence health effects. The air pollution fusion model proposed is a Bayesian space-time linear regression model for relating the measured concentrations to the modelled concentrations for a single pollutant, whilst allowing for additional covariate information such as site type (e.g. roadside, rural, etc) and temperature. However, it is known that some pollutants might be correlated because they may be generated by common processes or be driven by similar factors such as meteorology. The correlation between pollutants can help to predict one pollutant by borrowing strength from the others. Therefore, in chapter 5, I propose a multi-pollutant model which is a multivariate spatio-temporal fusion model that extends the single pollutant model in chapter 4, which relates monitored and modelled pollution data over space, time and pollutant to predict pollution across mainland Scotland. Considering that we are exposed to multiple pollutants simultaneously because the air we breathe contains a complex mixture of particle and gas phase pollutants, the health effects of exposure to multiple pollutants have been investigated in chapter 6. Therefore, this is a natural extension to the single pollutant health effects in chapter 4. Given NO2 and PM10 are highly correlated (multicollinearity issue) in my data, I first propose a temporally-varying linear model to regress one pollutant (e.g. NO2) against another (e.g. PM10) and then use the residuals in the disease model as well as PM10, thus investigating the health effects of exposure to both pollutants simultaneously. Another issue considered in chapter 6 is to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. There are in total four approaches being developed to adjust the exposure uncertainty. Finally, chapter 7 summarises the work contained within this thesis and discusses the implications for future research.
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Mechanistic models used for prediction should be parsimonious, as models which are over-parameterised may have poor predictive performance. Determining whether a model is parsimonious requires comparisons with alternative model formulations with differing levels of complexity. However, creating alternative formulations for large mechanistic models is often problematic, and usually time-consuming. Consequently, few are ever investigated. In this paper, we present an approach which rapidly generates reduced model formulations by replacing a model’s variables with constants. These reduced alternatives can be compared to the original model, using data based model selection criteria, to assist in the identification of potentially unnecessary model complexity, and thereby inform reformulation of the model. To illustrate the approach, we present its application to a published radiocaesium plant-uptake model, which predicts uptake on the basis of soil characteristics (e.g. pH, organic matter content, clay content). A total of 1024 reduced model formulations were generated, and ranked according to five model selection criteria: Residual Sum of Squares (RSS), AICc, BIC, MDL and ICOMP. The lowest scores for RSS and AICc occurred for the same reduced model in which pH dependent model components were replaced. The lowest scores for BIC, MDL and ICOMP occurred for a further reduced model in which model components related to the distinction between adsorption on clay and organic surfaces were replaced. Both these reduced models had a lower RSS for the parameterisation dataset than the original model. As a test of their predictive performance, the original model and the two reduced models outlined above were used to predict an independent dataset. The reduced models have lower prediction sums of squares than the original model, suggesting that the latter may be overfitted. The approach presented has the potential to inform model development by rapidly creating a class of alternative model formulations, which can be compared.
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Les organismes aquatiques sont adaptés à une grande variabilité hydrique et thermique des rivières. Malgré ceci, la régulation des eaux suscite des changements aux débits qui peuvent provoquer des impacts négatifs sur la biodiversité et les processus écologiques en rivière. Celle-ci peut aussi causer des modifications au niveau des régimes thermiques et des caractéristiques de l’habitat du poisson. Des données environnementales et biologiques décrivant l’habitat du poisson existent, mais elles sont incomplètes pour plusieurs rivières au Canada et de faible qualité, limitant les relations quantitatives débit-température-poissons à un petit nombre de rivières ou à une région étudiée. La recherche menée dans le cadre de mon doctorat concerne les impacts de la génération d'hydroélectricité sur les rivières; soit les changements aux régimes hydriques et thermiques reliés à la régulation des eaux sur la variation des communautés ichtyologiques qui habitent les rivières régulées et naturelles au Canada. Suite à une comparaison d’échantillonnage de pêche, une méthode constante pour obtenir des bons estimés de poisson (richesse, densité et biomasse des espèces) a été établie pour évaluer la structure de la communauté de poissons pour l’ensemble des rivières ciblées par l’étude. Afin de mieux comprendre ces changements environnementaux, les principales composantes décrivant ces régimes ont été identifiées et l’altération des régimes hydriques pour certaines rivières régulées a été quantifiée. Ces résultats ont servi à établir la relation significative entre le degré de changement biotique et le degré de changement hydrique pour illustrer les différences entre les régimes de régulation. Pour faire un complément aux indices biotiques déjà calculés pour l’ensemble des communautés de poissons (diversité, densité et biomasse des espèces par rivière), les différences au niveau des guildes de poissons ont été quantifiées pour expliquer les divers effets écologiques dus aux changements de régimes hydriques et thermiques provenant de la gestion des barrages. Ces derniers résultats servent à prédire pour quels traits écologiques ou groupes d’espèces de poissons les composantes hydriques et thermiques sont importantes. De plus, ces derniers résultats ont servi à mettre en valeur les variables décrivant les régimes thermiques qui ne sont pas toujours inclues dans les études hydro-écologiques. L’ensemble des résultats de cette thèse ont des retombées importantes sur la gestion des rivières en évaluant, de façon cohérente, l’impact de la régulation des rivières sur les communautés de poissons et en développant des outils de prévision pour la restauration des écosystèmes riverains.
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This study explores, from an ecological perspective, the relationship between perceived housing quality and the perception of choice, and between perceived choice and recovery of 45 Housing First Lisbon participants. For this purpose, we used a quantitative method and applied three instruments that report perceived housing quality, perceived choice and severe mental illness recovery. The findings reveal a significant and positive association between perceived housing quality and perceived choice, and between perceived choice and recovery, with choice being predicted by housing quality and recovery predicted by choice. These results reinforce the scientific evidence regarding the success of housing first models as a consumer choice-driven intervention, addressing pertinent environmental factors that contribute to housing stability. The study demonstrates that recovery processes can be maximized through services that empower their consumers by allowing them to choose and control the priority and order of the support services received.
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Dependence of some species on landscape structure has been proved in numerous studies. So far, however, little progress has been made in the integration of landscape metrics in the prediction of species associated with coastal features. Specific landscape metrics were tested as predictors of coastal shape using three coastal features of the Iberian Peninsula (beaches, capes and gulfs) at different scales. We used the landscape metrics in combination with environmental variables to model the niche and find suitable habitats for a seagrass species (Cymodocea nodosa) throughout its entire range of distribution. Landscape metrics able to capture variation in the coastline enhanced significantly the accuracy of the models, despite the limitations caused by the scale of the study. We provided the first global model of the factors that can be shaping the environmental niche and distribution of C. nodosa throughout its range. Sea surface temperature and salinity were the most relevant variables. We identified areas that seem unsuitable for C. nodosa as well as those suitable habitats not occupied by the species. We also present some preliminary results of testing historical biogeographical hypotheses derived from distribution predictions under Last Glacial Maximum conditions and genetic diversity data.
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Abstract During the last few decades, there has been an increasing international recognition of the studies related to the analysis of the family models change, the focus being the determinants of the female employment and the problems related to the work family balance (Lewis, 2001; Petit & Hook, 2005Saraceno, Crompton & Lyonette, 20062008; Pfau-Effinger, 2012). The majority of these studies have been focused on the analysis of the work-family balance problems as well as the effectiveness of the family and gender policies in order to encourage female employment (Korpi et al., 2013). In Spain, special attention has been given to the family policies implemented, the employability of women and on the role of the father in the family (Flaquer et al., 2015; Meil, 2015); however, there has been far less emphasis on the analysis of the family cultural models (González and Jurado, 2012; Crespi and Moreno, 2016). The purpose of this paper is to present some of the first results on the influence of the socio-demographic factors on the expectations and attitudes about the family models. This study offers an analytical reflection upon the foundation of the determinants of the family ambivalence in Spain from the cultural and the institutional dimension. This study shows the Spanish family models of preferences following the Pfau-Effinger (2004) classification of the famiy living arrangements. The reason for this study is twofold; on the one hand, there is confirmed the scarcity of studies that have focused their attention on this objective in Spain; on the other hand, the studies carried out in the international context have confirmed the analytical effectiveness of researching on the attitude and value changes to explain the meaning and trends of the family changes. There is also presented some preliminary results that have been obtained from the multinomial analysis related to the influence of the socio-demographic factors on the family model chosen by the individuals in Spain (father and mother working full time; mother part-time father full-time; mother not at work father full-time; mother and father part-time). 3 The database used has been the International Social Survey Programme: Family and Changing Gender Roles IV- ISSP 2012-. Spain is the only country of South Europe that has participated in the survey. For this reason it has been considered as a representative case study.