992 resultados para Trait Resilience


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Accelerating rates of environmental change and the continued loss of global biodiversity threaten functions and services delivered by ecosystems. Much ecosystem monitoring and management is focused on the provision of ecosystem functions and services under current environmental conditions, yet this could lead to inappropriate management guidance and undervaluation of the importance of biodiversity. The maintenance of ecosystem functions and services under substantial predicted future environmental change (i.e., their ‘resilience’) is crucial. Here we identify a range of mechanisms underpinning the resilience of ecosystem functions across three ecological scales. Although potentially less important in the short term, biodiversity, encompassing variation from within species to across landscapes, may be crucial for the longer-term resilience of ecosystem functions and the services that they underpin.

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The practices and decision-making of contemporary agricultural producers are governed by a multitude of different, and sometimes competing, social, economic, regulatory, environmental and ethical imperatives. Understanding how they negotiate and adapt to the demands of this complex and dynamic environment is crucial in maintaining an economically and environmentally viable and resilient agricultural sector. This paper takes a socio-cultural approach to explore the development of social resilience within agriculture through an original and empirically grounded discussion of people-place connections amongst UK farmers. It positions enchantment as central in shaping farmers' embodied and experiential connections with their farms through establishing hopeful, disruptive and demanding ethical practices. Farms emerge as complex moral economies in which an expanded conceptualisation of the social entangles human and non-human actants in dynamic and contextual webs of power and responsibility. While acknowledging that all farms are embedded within broader, nested levels, this paper argues that it is at the micro-scale that the personal, contingent and embodied relations that connect farmers to their farms are experienced and which, in turn, govern their capacity to develop social resilience.

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Understanding the relationships between trait diversity, species diversity and ecosystem functioning is essential for sustainable management. For functions comprising two trophic levels, trait matching between interacting partners should also drive functioning. However, the predictive ability of trait diversity and matching is unclear for most functions, particularly for crop pollination, where interacting partners did not necessarily co-evolve. World-wide, we collected data on traits of flower visitors and crops, visitation rates to crop flowers per insect species and fruit set in 469 fields of 33 crop systems. Through hierarchical mixed-effects models, we tested whether flower visitor trait diversity and/or trait matching between flower visitors and crops improve the prediction of crop fruit set (functioning) beyond flower visitor species diversity and abundance. Flower visitor trait diversity was positively related to fruit set, but surprisingly did not explain more variation than flower visitor species diversity. The best prediction of fruit set was obtained by matching traits of flower visitors (body size and mouthpart length) and crops (nectar accessibility of flowers) in addition to flower visitor abundance, species richness and species evenness. Fruit set increased with species richness, and more so in assemblages with high evenness, indicating that additional species of flower visitors contribute more to crop pollination when species abundances are similar. Synthesis and applications. Despite contrasting floral traits for crops world-wide, only the abundance of a few pollinator species is commonly managed for greater yield. Our results suggest that the identification and enhancement of pollinator species with traits matching those of the focal crop, as well as the enhancement of pollinator richness and evenness, will increase crop yield beyond current practices. Furthermore, we show that field practitioners can predict and manage agroecosystems for pollination services based on knowledge of just a few traits that are known for a wide range of flower visitor species.

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Many studies have aimed to identify common predictors of successful introductions of alien species, but the search has had limited success, particularly for animals. Past research focused primarily on mean trait values, even though genetic and phenotypic variation has been shown to play a role in establishment success in plants and some animals (mostly invertebrates). Using a global database describing 511 introduction events representing 97 mammalian species, we show that intraspecific variation in morphological traits is associated with establishment success, even when controlling for the positive effect of propagule pressure. In particular, greater establishment success is associated with more variation in adult body size but, surprisingly, less variation in neonate body size, potentially reflecting distinct trade-offs and constraints that influence population dynamics differently. We find no mean trait descriptors associated with establishment success, although species occupying wider native distribution ranges (which likely have larger niches) are more successful. Our results emphasize the importance of explicitly considering intraspecific variation to predict establishment success in animal species and generally to understand population dynamics. This understanding might improve management of alien species and increase the success of intentional releases, for example, for biocontrol or reintroductions.

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The composition of species communities is changing rapidly through drivers such as habitat loss and climate change, with potentially serious consequences for the resilience of ecosystem functions on which humans depend. To assess such changes in resilience, we analyse trends in the frequency of species in Great Britain that provide key ecosystem functions-specifically decomposition, carbon sequestration, pollination, pest control and cultural values. For 4,424 species over four decades, there have been significant net declines among animal species that provide pollination, pest control and cultural values. Groups providing decomposition and carbon sequestration remain relatively stable, as fewer species are in decline and these are offset by large numbers of new arrivals into Great Britain. While there is general concern about degradation of a wide range of ecosystem functions, our results suggest actions should focus on particular functions for which there is evidence of substantial erosion of their resilience.

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Anticipation is increasingly central to urgent contemporary debates, from climate change to the global economic crisis. Anticipatory practices are coming to the forefront of political, organizational, and citizens’ society. Research into anticipation, however, has not kept pace with public demand for insights into anticipatory practices, their risks and uses. Where research exists, it is deeply fragmented. This paper seeks to identify how anticipation is defined and understood in the literature and to explore the role of anticipatory practice to address individual, social, and global challenges. We use a resilience lens to examine these questions. We illustrate how varying forms of anticipatory governance are enhanced by multi-scale regional networks and technologies and by the agency of individuals, drawing from an empirical case study on regional water governance of Mälaren, Sweden. Finally, we discuss how an anticipatory approach can inform adaptive institutions, decision making, strategy formation, and societal resilience.

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Community resilience is widely understood as a critical element in the relatively under-explored concept of social resilience. Through engaging with ‘more-than-human’ literatures, a more expansive view of the ‘social’ emerges, which repositions individuals as networked and agency as relational. This moves resilience away from its hegemonic positioning as a neoliberal strategy of individualisation and responsibilisation, with it instead emerging as an everyday ‘doing’ embedded in the human and non-human networks of relationality that we form and are formed by. The paper develops this socio-cultural conceptualisation through an original and empirically grounded discussion of Finnish farm communities and the role of the forest in developing, maintaining and enhancing these essential, connective assemblages. Resilience becomes conceptualised as dynamic, uneven, multiple and contextual performances or resiliences. While this further problematizes the comparative measurement and operationalisation of resilience, its networked and relational nature arguably offers a more inclusive and ethically grounded concept that, furthermore, negates the socio-ecological divide that persists in resilience thinking.

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Climate change poses new challenges to cities and new flexible forms of governance are required that are able to take into account the uncertainty and abruptness of changes. The purpose of this paper is to discuss adaptive climate change governance for urban resilience. This paper identifies and reviews three traditions of literature on the idea of transitions and transformations, and assesses to what extent the transitions encompass elements of adaptive governance. This paper uses the open source Urban Transitions Project database to assess how urban experiments take into account principles of adaptive governance. The results show that: the experiments give no explicit information of ecological knowledge; the leadership of cities is primarily from local authorities; and evidence of partnerships and anticipatory or planned adaptation is limited or absent. The analysis shows that neither technological, political nor ecological solutions alone are sufficient to further our understanding of the analytical aspects of transition thinking in urban climate governance. In conclusion, the paper argues that the future research agenda for urban climate governance needs to explore further the links between the three traditions in order to better identify contradictions, complementarities or compatibilities, and what this means in practice for creating and assessing urban experiments.

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The need for a reconsideration of resilience from both a positive and a normative point of view can be discussed using some of the lessons and conclusions drawn from individual resilience studied by psychologists in an educational context. The main point made in this article is that unless we want to approach resilience as a feature which is exogenously given in each population and society and whose dynamics, if any, are not subject to deliberate actions and policies, we need a framework for the evaluation of resilience as a social good. Relying on the hope that resilience is necessarily built in our societies as a force guaranteeing convergence to a socially desirable point of social evolution may be too optimistic and even counterproductive, because it may lead us to an inefficient or biased political and regulatory decision making. When the effect of policies and actions at a national or international level take into account the dynamic effect of such actions on resilience itself, one cannot blindly rely on the goodness of the process any more. This is mainly because resilience is not uniformly embodied in all societies and it does not have a globally positive social value by itself. The issue of socially valuing the options available beyond market-price valuations becomes fundamental in this context.

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We have shown previously that particpants “at risk” of depression have decreased neural processing of reward suggesting this might be a neural biomarker for depression. However, how the neural signal related to subjective experiences of reward (wanting, liking, intensity) might differ as trait markers for depression, is as yet unknown. Using SPM8 parametric modulation analysis the neural signal related to the subjective report of wanting, liking and intensity was compared between 25 young people with a biological parent with depression (FH) and 25 age/gender matched controls. In a second study the neural signal related to the subjective report of wanting, liking and intensity was compared between 13 unmedicated recovered depressed (RD) patients and 14 healthy age/gender matched controls. The analysis revealed differences in the neural signal for wanting, liking and intensity ratings in the ventral striatum, dmPFC and caudate respectively in the RD group compared to controls . Despite no differences in the FH groups neural signal for wanting and liking there was a difference in the neural signal for intensity ratings in the dACC and anterior insula compared to controls. These results suggest that the neural substrates tracking the intensity but not the wanting or liking for rewards and punishers might be a trait marker for depression.

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Background Anxiety related to dental treatment is a fairly common phenomenon. Some studies have shown that there is an association between dental anxiety and general fears and anxiety, neuroticism and general psychological distress. Aim This study was designed to examine the relationship between dental anxiety and trait anxiety. Subjects and methods The sample consisted of 1,030 individuals (688 women; 342 men), aged 30.8 +/- 11.7 years. The Portuguese version of Corah`s Dental Anxiety Scale (DAS) and State-Trait Anxiety Inventory (STAI-T) were used. Results A statistically significant association between high DAS and high STAI-T, but not between high STAI-T and high DAS, was found. The data indicated that subjects with high dental anxiety tend to present with high trait anxiety, but high trait anxiety seems not to predispose to high dental anxiety. Conclusions Our results indicate that dental anxiety is specific, with its own features, and its development is not necessarily associated with trait anxiety.

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The relationship between the structure and function of biological networks constitutes a fundamental issue in systems biology. Particularly, the structure of protein-protein interaction networks is related to important biological functions. In this work, we investigated how such a resilience is determined by the large scale features of the respective networks. Four species are taken into account, namely yeast Saccharomyces cerevisiae, worm Caenorhabditis elegans, fly Drosophila melanogaster and Homo sapiens. We adopted two entropy-related measurements (degree entropy and dynamic entropy) in order to quantify the overall degree of robustness of these networks. We verified that while they exhibit similar structural variations under random node removal, they differ significantly when subjected to intentional attacks (hub removal). As a matter of fact, more complex species tended to exhibit more robust networks. More specifically, we quantified how six important measurements of the networks topology (namely clustering coefficient, average degree of neighbors, average shortest path length, diameter, assortativity coefficient, and slope of the power law degree distribution) correlated with the two entropy measurements. Our results revealed that the fraction of hubs and the average neighbor degree contribute significantly for the resilience of networks. In addition, the topological analysis of the removed hubs indicated that the presence of alternative paths between the proteins connected to hubs tend to reinforce resilience. The performed analysis helps to understand how resilience is underlain in networks and can be applied to the development of protein network models.

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This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models. In variance component QTL analysis, a full likelihood model accounting for uncertainty in the identity-by-descent (IBD) matrix was developed. It was found to be able to correctly adjust the bias in genetic variance component estimation and gain power in QTL mapping in terms of precision.  Double hierarchical generalized linear models, and a non-iterative simplified version, were implemented and applied to fit data of an entire genome. These whole genome models were shown to have good performance in both QTL mapping and genomic prediction. A re-analysis of a publicly available GWAS data set identified significant loci in Arabidopsis that control phenotypic variance instead of mean, which validated the idea of variance-controlling genes.  The works in the thesis are accompanied by R packages available online, including a general statistical tool for fitting random effects models (hglm), an efficient generalized ridge regression for high-dimensional data (bigRR), a double-layer mixed model for genomic data analysis (iQTL), a stochastic IBD matrix calculator (MCIBD), a computational interface for QTL mapping (qtl.outbred), and a GWAS analysis tool for mapping variance-controlling loci (vGWAS).