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1.
Conserv Biol ; 30(5): 990-9, 2016 10.
Artigo em Inglês | MEDLINE | ID: mdl-27185104

RESUMO

The number of collaborative initiatives between scientists and volunteers (i.e., citizen science) is increasing across many research fields. The promise of societal transformation together with scientific breakthroughs contributes to the current popularity of citizen science (CS) in the policy domain. We examined the transformative capacity of citizen science in particular learning through environmental CS as conservation tool. We reviewed the CS and social-learning literature and examined 14 conservation projects across Europe that involved collaborative CS. We also developed a template that can be used to explore learning arrangements (i.e., learning events and materials) in CS projects and to explain how the desired outcomes can be achieved through CS learning. We found that recent studies aiming to define CS for analytical purposes often fail to improve the conceptual clarity of CS; CS programs may have transformative potential, especially for the development of individual skills, but such transformation is not necessarily occurring at the organizational and institutional levels; empirical evidence on simple learning outcomes, but the assertion of transformative effects of CS learning is often based on assumptions rather than empirical observation; and it is unanimous that learning in CS is considered important, but in practice it often goes unreported or unevaluated. In conclusion, we point to the need for reliable and transparent measurement of transformative effects for democratization of knowledge production.


Assuntos
Participação da Comunidade , Conservação dos Recursos Naturais , Aprendizagem , Voluntários , Coleta de Dados , Europa (Continente) , Humanos , Pesquisa
2.
BMC Public Health ; 16(1): 760, 2016 08 11.
Artigo em Inglês | MEDLINE | ID: mdl-27516181

RESUMO

BACKGROUND: The current political agenda aims to promote active environments and physical activity while commuting to work, but research on it has provided mixed results. This study examines whether the proximity of green space and people's residence in different travel-related urban zones contributes to commuting physical activity. METHODS: Population-based cross-sectional health examination survey, Health 2011 study, and geographical information system (GIS) data were utilized. The GIS data on green space and travel-related urban zones were linked to the individuals of the Health 2011 study, based on their home geocoordinates. Commuting physical activity was self-reported. Logistic regression models were applied, and age, gender, education, leisure-time and occupational physical activity were adjusted. Analyses were limited to those of working age, living in the core-urban areas of Finland and having completed information on commuting physical activity (n = 2 098). RESULTS: Home location in a pedestrian zone of a main centre (odds ratio = 1.63; 95 % confidence interval = 1.06-2.51) or a pedestrian zone of a sub-centre (2.03; 1.09-3.80) and higher proportion of cycling and pedestrian networks (3.28; 1.71-6.31) contributed to higher levels of commuting physical activity. The contribution remained after adjusting for all the environmental attributes and individuals. Based on interaction analyses, women living in a public transport zone were almost two times more likely to be physically active while commuting compared to men. A high proportion of recreational green space contributed negatively to the levels of commuting physical activity (0.73; 0.57-0.94) after adjusting for several background factors. Based on interaction analyses, individuals aged from 44 to 54 years and living in sub-centres, men living in pedestrian zones of sub-centres, and those individuals who are physically inactive during leisure-time were less likely to be physically active while commuting. CONCLUSIONS: Good pedestrian and cycling infrastructure may play an important role in promoting commuting physical activity among the employed population, regardless of educational background, leisure-time and occupational physical activity. Close proximity to green space and a high proportion of green space near the home may not be sufficient to initiate commuting physical activity in Finland, where homes surrounded by green areas are often situated in car-oriented zones far from work places.


Assuntos
Ciclismo/estatística & dados numéricos , Meio Ambiente , Exercício Físico , Sistemas de Informação Geográfica , Meios de Transporte/estatística & dados numéricos , Caminhada/estatística & dados numéricos , Adulto , Idoso , Estudos Transversais , Emprego/estatística & dados numéricos , Feminino , Finlândia , Inquéritos Epidemiológicos , Humanos , Atividades de Lazer , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Pedestres/estatística & dados numéricos , Autorrelato , Meios de Transporte/métodos , Viagem/estatística & dados numéricos , População Urbana/estatística & dados numéricos , Adulto Jovem
3.
PLoS One ; 13(11): e0206672, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30383800

RESUMO

Interactions between people and ecological systems, through leisure or tourism activities, form a complex socio-ecological spatial network. The analysis of the benefits people derive from their interactions with nature-also referred to as cultural ecosystem services (CES)-enables a better understanding of these socio-ecological systems. In the age of information, the increasing availability of large social media databases enables a better understanding of complex socio-ecological interactions at an unprecedented spatio-temporal resolution. Within this context, we model and analyze these interactions based on information extracted from geotagged photographs embedded into a multiscale socio-ecological network. We apply this approach to 16 case study sites in Europe using a social media database (Flickr) containing more than 150,000 validated and classified photographs. After evaluating the representativeness of the network, we investigate the impact of visitors' origin on the distribution of socio-ecological interactions at different scales. First at a global scale, we develop a spatial measure of attractiveness and use this to identify four groups of sites. Then, at a local scale, we explore how the distance traveled by the users to reach a site affects the way they interact with this site in space and time. The approach developed here, integrating social media data into a network-based framework, offers a new way of visualizing and modeling interactions between humans and landscapes. Results provide valuable insights for understanding relationships between social demands for CES and the places of their realization, thus allowing for the development of more efficient conservation and planning strategies.


Assuntos
Ecossistema , Modelos Teóricos , Mídias Sociais , Adulto , Conservação dos Recursos Naturais , Europa (Continente) , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Fotografação , Fatores Socioeconômicos , Análise Espacial , Viagem
4.
Ecosyst Serv ; 29(Pt C): 465-480, 2018 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-29492376

RESUMO

Ecosystem service (ES) spatial modelling is a key component of the integrated assessments designed to support policies and management practices aiming at environmental sustainability. ESTIMAP ("Ecosystem Service Mapping Tool") is a collection of spatially explicit models, originally developed to support policies at a European scale. We based our analysis on 10 case studies, and 3 ES models. Each case study applied at least one model at a local scale. We analyzed the applications with respect to: the adaptation process; the "precision differential" which we define as the variation generated in the model between the degree of spatial variation within the spatial distribution of ES and what the model captures; the stakeholders' opinions on the usefulness of models. We propose a protocol for adapting ESTIMAP to the local conditions. We present the precision differential as a means of assessing how the type of model and level of model adaptation generate variation among model outputs. We then present the opinion of stakeholders; that in general considered the approach useful for stimulating discussion and supporting communication. Major constraints identified were the lack of spatial data with sufficient level of detail, and the level of expertise needed to set up and compute the models.

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