Future response of global coastal wetlands to sea-level rise.

The response of coastal wetlands to sea-level rise during the twenty-first century remains uncertain. Global-scale projections suggest that between 20 and 90 per cent (for low and high sea-level rise scenarios, respectively) of the present-day coastal wetland area will be lost, which will in turn result in the loss of biodiversity and highly valued ecosystem services1-3. These projections do not necessarily take into account all essential geomorphological4-7 and socio-economic system feedbacks8. Here we present an integrated global modelling approach that considers both the ability of coastal wetlands to build up vertically by sediment accretion, and the accommodation space, namely, the vertical and lateral space available for fine sediments to accumulate and be colonized by wetland vegetation. We use this approach to assess global-scale changes in coastal wetland area in response to global sea-level rise and anthropogenic coastal occupation during the twenty-first century. On the basis of our simulations, we find that, globally, rather than losses, wetland gains of up to 60 per cent of the current area are possible, if more than 37 per cent (our upper estimate for current accommodation space) of coastal wetlands have sufficient accommodation space, and sediment supply remains at present levels. In contrast to previous studies1-3, we project that until 2100, the loss of global coastal wetland area will range between 0 and 30 per cent, assuming no further accommodation space in addition to current levels. Our simulations suggest that the resilience of global wetlands is primarily driven by the availability of accommodation space, which is strongly influenced by the building of anthropogenic infrastructure in the coastal zone and such infrastructure is expected to change over the twenty-first century. Rather than being an inevitable consequence of global sea-level rise, our findings indicate that large-scale loss of coastal wetlands might be avoidable, if sufficient additional accommodation space can be created through careful nature-based adaptation solutions to coastal management.Personal research fellowship of Mark Schuerch (Project Number 272052902) and by the Cambridge Coastal Research Unit (Visiting Scholar Programme). Furthermore, this work has partly been supported by the EU research project RISES-AM- (FP7-ENV-693396)

Pain Assessment in Impaired Cognition (PAIC): content validity of the Dutch version of a new and universal tool to measure pain in dementia

Annelore H van Dalen-Kok,1 Wilco P Achterberg,1 Wieke E Rijkmans,1 Sara A Tukker-van Vuuren,1 Suzanne Delwel,2,3 Henrica CW de Vet,4 Frank Lobbezoo,2,5 Margot WM de Waal1 1Department of Public Health and Primary Care, Leiden University Medical Centre, Leiden, 2Department of Oral Kinesiology, Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam and VU University Amsterdam, 3Department of Clinical Neuropsychology, Faculty of Behavioral and Movement Sciences, VU University, 4Department of Epidemiology and Biostatistics, The EMGO Institute for Health and Care Research, VU University Medical Center, 5MOVE Research Institute Amsterdam, VU University, Amsterdam, the Netherlands Objectives: Detection and measurement of pain in persons with dementia by using observational pain measurement tools is essential. However, the evidence for the psychometric properties of existing observational tools remains limited. Therefore, a new meta-tool has been developed: Pain Assessment in Impaired Cognition (PAIC), as a collaborative EU action. The aim is to describe the translation procedure and content validity of the Dutch version of the PAIC.Methods: Translation of the PAIC into Dutch followed the forward-backward approach of the Guidelines for Establishing Cultural Equivalence of Instruments. A questionnaire survey was administered to clinical nursing home experts (20 physicians and 20 nurses) to determine whether the PAIC items are indicative of pain and whether items are specific for pain or for other disorders (anxiety disorder, delirium, dementia, or depression). To quantify content validity, mean scores per item were calculated.Results: Eleven items were indicative of pain, for example, “frowning,” “freezing,” and “groaning.” Fifteen items were considered to be pain-specific, for example, “frowning,” “curling up,” and “complaining.” There were discrepancies between the notion of pain characteristics according to nurses and physicians, especially in the facial expressions domain.Discussion: Within the body movement domain, PAIC items correspond well with the clinical experience of the physicians and nurses. However, items in the facial expressions and vocalizations domains need further study with respect to item reduction. Also, differences were revealed in the notion of pain characteristics between physicians and nurses, suggesting the need for more interdisciplinary education on pain in dementia. Keywords: content validity, dementia, education, nursing home, observational pain measurement tool, pai

Uncertainty from Model Calibration: Applying a New Method to Transport Energy Demand Modelling

Uncertainties in energy demand modelling originate from both limited understanding of the real-world system and a lack of data for model development, calibration and validation. These uncertainties allow for the development of different models, but also leave room for different calibrations of a single model. Here, an automated model calibration procedure was developed and tested for transport sector energy use modelling in the TIMER 2.0 global energy model. This model describes energy use on the basis of activity levels, structural change and autonomous and priceinduced energy efficiency improvements. We found that the model could reasonably reproduce historic data under different sets of parameter values, leading to different projections of future energy demand levels. Projected energy use for 2030 shows a range of 44–95% around the best-fit projection. Two different model interpretations of the past can generally be distinguished: (1) high useful energy intensity and major energy efficiency improvements or (2) low useful energy intensity and little efficiency improvement. Generally, the first lead to higher future energy demand levels than the second, but model and insights do not provide decisive arguments to attribute a higher likelihood to one of the alternatives.Delft Center for Systems and ControlMechanical, Maritime and Materials Engineerin