Portraits of Peel – A Community Indicators Portal Project

Author(s):  
Srimanta Mohanty
Keyword(s):  
2019 ◽  
Vol 99 ◽  
pp. 74-82 ◽  
Author(s):  
Pierre Gaüzère ◽  
Guilhem Doulcier ◽  
Vincent Devictor ◽  
Sonia Kéfi

2020 ◽  
Vol 77 (3) ◽  
pp. 519-541
Author(s):  
V. Brosnan ◽  
C. J. Ellis

National vegetation classification (NVC) has been widely applied as a framework for mapping and conserving plant species and community types. However, a limited availability of expertise has prevented NVCs from being developed and used in cryptogam-dominated systems, such as for temperate and boreal epiphyte communities. This study simplified a recent systematically sampled NVC, trialled for epiphyte communities in Scotland, by reducing the original list of 82 community indicators to 34 easily recognisable species (lichens, mosses and liverworts). These were subsequently sampled from woodland sites positioned in Scotland’s temperate rain forest zone. Sites were positioned among localities in less intensively managed landscapes (northwest Scotland) through to peri-urban environments (southern Scotland), grouping sites for each locality based on a contrast in woodland temporal continuity (ancient or recent). The richness and diversity of epiphyte community indicators were compared with easily measured variables reflecting stand heterogeneity or ecological stability, and woodland temporal continuity, with air pollution as a covariable. Richness and diversity were significantly explained by the ecological stability of woodland stands, heterogeneity of the light environment, and nitrogen pollution. This demonstrates a tool that can be deployed by the non-specialist, with appropriate training, to quantify the condition of a woodland stand through consequences for its epiphytes in globally important temperate rain forest. The pattern of richness and diversity was consistent with the co-occurrence of particular indicator species, which represent the range of epiphyte community types supported by a woodland.


BMJ Open ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. e030524 ◽  
Author(s):  
Izabela Zakowska ◽  
Katarzyna Kosiek ◽  
Anna Kowalczyk ◽  
Jacek Grabowski ◽  
Maciek Godycki-Cwirko

IntroductionAnalyses of large sets of electronic health-related data (Big Data), including local community indicators, may improve knowledge of the outcomes of chronic diseases among patients and healthcare systems. Our study will estimate the prevalence of chronic obstructive pulmonary disease (COPD) and its exacerbations in elderly patients in the Lodz region, Poland; it will also evaluate local community factors potentially associated with disease exacerbations and rank local communities according to health and local community indicators.Methodsand analysisLocal community factors, including medical/health, socioeconomic and environmental values potentially associated with COPD exacerbations will be identified. A retrospective analysis of a cohort of about half a million people 65 years old and older, living in local communities of the Lodz region in 2016 will be performed. Relevant data will be extracted from databases, including those of the National Health Fund, Tax Office and National Statistics Centre. This cross-sectional study will include data for a 1 year period, from 1 January until 31 December 2016. The data will first be checked for quality, cleaned and analysed using data mining techniques, and then multilevel logistic regression will be used to discover the community determinants of COPD exacerbations.Ethics and disseminationThe study protocol has been approved by the Bioethical Committee of Medical University of Lodz (RNN/248/18/KE, 10 July 2018). Our findings will be published in peer-reviewed journals and reports.


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