Peat multi-proxy data from Mannikjarve bog as indicators of late Holocene climate changes in Estonia

As part of a wider project on European climate change over the past 4500 years, a 4.5-m peat core was taken from a lawn microform on Mannikjarve bog, Estonia. Several methods were used to yield proxy-climate data: (i) a quadrat and leaf-count method for plant macrofossil data, (ii) testate amoebae analysis, and (iii) colorimetric determination of peat humification. These data are provided with an exceptionally high resolution and precise chronology. Changes in bog surface wetness were inferred using Detrended Correspondence Analysis (DCA) and zonation of macrofossil data, particularly concerning the occurrence of Sphagnum balticum, and a transfer function for water-table depth for testate amoebae data. Based on the results, periods of high bog surface wetness appear to have occurred at c. 3100, 3010-2990, 2300, 1750-1610, 1510, 14 10, 1110, 540 and 3 10 cal. yr BP, during four longer periods between c. 3170 and 2850 cal. yr BP, 2450 and 2000 cal. yr BP, 1770 and 1530 cal. yr BP and in the period from 880 cal. yr BP until the present. In the period between 1770 and 1530 cal. yr BP. the extension or initiation of a hollow microtope occurred, which corresponds with other research results from Mannikjarve bog. This and other changes towards increasing bog surface wetness may be the responses to colder temperatures and the predominance of a more continental climate in the region, which favoured the development of bog microdepressions and a complex bog microtopography. Located in the border zone of oceanic and continental climatic sectors, in an area almost without land uplift, this study site may provide valuable information about changes in palaeohydrological and palaeoclimatological conditions in the northern parts of the eastern Baltic Sea region.

Evaluation of the Q-method as a method of public participation in the selection of sustainable development indicators

The complexity of sustainable development means that it is often difficult to evaluate and communicate the concept effectively. One standard method to reduce complexity and improve Communication, while maintaining scientific objectivity, is to use selected indicators. The aim of this paper is to describe and evaluate a process Of public participation in the selection of sustainable development indicators that utilised the Q-method for discourse analysis. The Q-method was Utilised to combine public opinion with technical expertise to create a list of technically robust indicators that would be relevant to the public, The method comprises statement collection, statement analysis, Q-sorts and Q-sort analysis. The results of the Q-method generated a list of statements for which a preliminary list of indicators was then developed by a team of experts from the fields of environmental science, sustainable development and Psychology. Subsequently members of the public evaluated the preliminary list of indicators, to select a final list of indicators that were both technically sound and incorporated the views of the public. The Utilisation of the Q-method in this process was evaluated using previously published criteria. The application of the Q-method in this context needs to be considered not only by the quality of the indicators developed, but also from the perspective of the benefit of the process to the participants. it was concluded that the Q-method provided an effective framework for public participation in the selection of indicators as it allowed the public to discuss Sustainable development in familiar language and in the context of their daily lives. By combining this information with expert input, a list of technically robust indicators that resonate with the public was developed. The results demonstrated that many citizens are not aware Of Sustainable development, and if it is to be successfully communicated to them, then indicators and policy need to be couched in terms familiar and relevant to citizen and communities. (C) 2009 Elsevier Ltd. All rights reserved.

A Multiple Indicators Multiple Causes (MIMIC) model of Behavioural and Psychological Symptoms in Dementia (BPSD)

Introduction: Although there is evidence for distinct behavioural sub-phenotypes in Alzheimer's disease (AD), their inter-relationships and the effect of clinical variables on their expression have been little investigated.

Recent advances in the analysis of behavioural organization and interpretation as indicators of animal welfare

While the incorporation of mathematical and engineering methods has greatly advanced in other areas of the life sciences, they have been under-utilized in the field of animal welfare. Exceptions are beginning to emerge and share a common motivation to quantify 'hidden' aspects in the structure of the behaviour of an individual, or group of animals. Such analyses have the potential to quantify behavioural markers of pain and stress and quantify abnormal behaviour objectively. This review seeks to explore the scope of such analytical methods as behavioural indicators of welfare. We outline four classes of analyses that can be used to quantify aspects of behavioural organization. The underlying principles, possible applications and limitations are described for: fractal analysis, temporal methods, social network analysis, and agent-based modelling and simulation. We hope to encourage further application of analyses of behavioural organization by highlighting potential applications in the assessment of animal welfare, and increasing awareness of the scope for the development of new mathematical methods in this area.

Indicators of the impact of climate change on migratory species

The Bonn Convention on the Conservation of Migratory Species of Wild Animals adopted a Resolution in 2005 recognising the impacts of climate change on migratory species. It called on Contracting Parties to undertake more research to improve our understanding of these impacts and to implement adaptation measures to reduce foreseeable adverse effects. Given the large diversity of taxa and species affected by climate change, it is impossible to monitor all species and effects thereof. However, it is likely that many of the key ecological and physical processes through which climate change may impact wildlife could be monitored using a suite of indicators, each comprising parameters of species/populations or groups of species as proxies for wider assemblages, habitats and ecosystems. Herein, we identify a suite of 17 indicators whose attributes could reveal negative impacts of climate change on the global status of migratory species: 4 for birds, 4 for marine mammals, 2 for sea turtles, 1 for fish, 3 for land mammals and 3 for bats. A few of these indicators would be relatively straightforward to develop, but most would require additional data collation, and in many cases methodological development. Choosing and developing indicators of the impacts of climate change on migratory species is a challenge, particularly with endangered species, which are subject to many other pressures. To identify and implement conservation measures for these species, indicators must account for the full ensemble of pressures, and link to a system of alerts and triggers for action.