The impact of land use/land cover scale on modelling urban ecosystem services

Context Urbanisation places increasing stress on ecosystem services; however existing methods and data for testing relationships between service delivery and urban landscapes remain imprecise and uncertain. Unknown impacts of scale are among several factors that complicate research. This study models ecosystem services in the urban area comprising the towns of Milton Keynes, Bedford and Luton which together represent a wide range of the urban forms present in the UK. Objectives The objectives of this study were to test (1) the sensitivity of ecosystem service model outputs to the spatial resolution of input data, and (2) whether any resultant scale dependency is constant across different ecosystem services and model approaches (e.g. stock- versus flow-based). Methods Carbon storage, sediment erosion, and pollination were modelled with the InVEST framework using input data representative of common coarse (25 m) and fine (5 m) spatial resolutions. Results Fine scale analysis generated higher estimates of total carbon storage (9.32 vs. 7.17 kg m−2) and much lower potential sediment erosion estimates (6.4 vs. 18.1 Mg km−2 year−1) than analyses conducted at coarser resolutions; however coarse-scale analysis estimated more abundant pollination service provision. Conclusions Scale sensitivities depend on the type of service being modelled; stock estimates (e.g. carbon storage) are most sensitive to aggregation across scales, dynamic flow models (e.g. sediment erosion) are most sensitive to spatial resolution, and ecological process models involving both stocks and dynamics (e.g. pollination) are sensitive to both. Care must be taken to select model data appropriate to the scale of inquiry

A Research Agenda for Helminth Diseases of Humans: Modelling for Control and Elimination

Mathematical modelling of helminth infections has the potential to inform policy and guide research for the control and elimination of human helminthiases. However, this potential, unlike in other parasitic and infectious diseases, has yet to be realised. To place contemporary efforts in a historical context, a summary of the development of mathematical models for helminthiases is presented. These efforts are discussed according to the role that models can play in furthering our understanding of parasite population biology and transmission dynamics, and the effect on such dynamics of control interventions, as well as in enabling estimation of directly unobservable parameters, exploration of transmission breakpoints, and investigation of evolutionary outcomes of control. The Disease Reference Group on Helminth Infections (DRG4), established in 2009 by the Special Programme for Research and Training in Tropical Diseases (TDR), was given the mandate to review helminthiases research and identify research priorities and gaps. A research and development agenda for helminthiasis modelling is proposed based on identified gaps that need to be addressed for models to become useful decision tools that can support research and control operations effectively. This agenda includes the use of models to estimate the impact of large-scale interventions on infection incidence; the design of sampling protocols for the monitoring and evaluation of integrated control programmes; the modelling of co-infections; the investigation of the dynamical relationship between infection and morbidity indicators; the improvement of analytical methods for the quantification of anthelmintic efficacy and resistance; the determination of programme endpoints; the linking of dynamical helminth models with helminth geostatistical mapping; and the investigation of the impact of climate change on human helminthiases. It is concluded that modelling should be embedded in helminth research, and in the planning, evaluation, and surveillance of interventions from the outset. Modellers should be essential members of interdisciplinary teams, propitiating a continuous dialogue with end users and stakeholders to reflect public health needs in the terrain, discuss the scope and limitations of models, and update biological assumptions and model outputs regularly. It is highlighted that to reach these goals, a collaborative framework must be developed for the collation, annotation, and sharing of databases from large-scale anthelmintic control programmes, and that helminth modellers should join efforts to tackle key questions in helminth epidemiology and control through the sharing of such databases, and by using diverse, yet complementary, modelling approaches

Neuromarketing and consumer neuroscience:contributions to neurology

Background: 'Neuromarketing' is a term that has often been used in the media in recent years. These public discussions have generally centered around potential ethical aspects and the public fear of negative consequences for society in general, and consumers in particular. However, positive contributions to the scientific discourse from developing a biological model that tries to explain context-situated human behavior such as consumption have often been neglected. We argue for a differentiated terminology, naming commercial applications of neuroscientific methods 'neuromarketing' and scientific ones 'consumer neuroscience'. While marketing scholars have eagerly integrated neuroscientific evidence into their theoretical framework, neurology has only recently started to draw its attention to the results of consumer neuroscience.Discussion: In this paper we address key research topics of consumer neuroscience that we think are of interest for neurologists; namely the reward system, trust and ethical issues. We argue that there are overlapping research topics in neurology and consumer neuroscience where both sides can profit from collaboration. Further, neurologists joining the public discussion of ethical issues surrounding neuromarketing and consumer neuroscience could contribute standards and experience gained in clinical research.Summary: We identify the following areas where consumer neuroscience could contribute to the field of neurology:. First, studies using game paradigms could help to gain further insights into the underlying pathophysiology of pathological gambling in Parkinson's disease, frontotemporal dementia, epilepsy, and Huntington's disease.Second, we identify compulsive buying as a common interest in neurology and consumer neuroscience. Paradigms commonly used in consumer neuroscience could be applied to patients suffering from Parkinson's disease and frontotemporal dementia to advance knowledge of this important behavioral symptom.Third, trust research in the medical context lacks empirical behavioral and neuroscientific evidence. Neurologists entering this field of research could profit from the extensive knowledge of the biological foundation of trust that scientists in economically-orientated neurosciences have gained.Fourth, neurologists could contribute significantly to the ethical debate about invasive methods in neuromarketing and consumer neuroscience. Further, neurologists should investigate biological and behavioral reactions of neurological patients to marketing and advertising measures, as they could show special consumer vulnerability and be subject to target marketing