Progressing beyond colonization strategies to understand arbuscular mycorrhizal fungal life history

Knowledge of differential life-history strategies in arbuscular mycorrhizal (AM) fungi is relevant for understanding the ecology of this group and its potential role in sustainable agriculture and carbon sequestration. At present, AM fungal life-history theories often focus on differential investment into intra- vs extraradical structures among AM fungal taxa, and its implications for plant benefits. With this Viewpoint we aim to expand these theories by integrating a mycocentric economics- and resource-based life-history framework. As in plants, AM fungal carbon and nutrient demands are stoichiometrically coupled, though uptake of these elements is spatially decoupled. Consequently, investment in morphological structures for carbon vs nutrient uptake is not in competition. We argue that understanding the ecology and evolution of AM fungal life-history trade-offs requires increased focus on variation among structures foraging for the same element, that is within intra- or extraradical structures (in our view a ‘horizontal’ axis), not just between them (‘vertical’ axis). Here, we elaborate on this argument and propose a range of plausible life-history trade-offs that could lead to the evolution of strategies in AM fungi, providing testable hypotheses and creating opportunities to explain AM fungal co-existence, and the context-dependent effects of AM fungi on plant growth and soil carbon dynamics

METACOHORTS for the study of vascular disease and its contribution to cognitive decline and neurodegeneration: an initiative of the Joint Programme for Neurodegenerative Disease Research

Dementia is a global problem and major target for health care providers. Although up to 45% of cases are primarily or partly due to cerebrovascular disease, little is known of these mechanisms or treatments because most dementia research still focuses on pure Alzheimer's disease. An improved understanding of the vascular contributions to neurodegeneration and dementia, particularly by small vessel disease, is hampered by imprecise data, including the incidence and prevalence of symptomatic and clinically “silent” cerebrovascular disease, long-term outcomes (cognitive, stroke, or functional), and risk factors. New large collaborative studies with long follow-up are expensive and time consuming, yet substantial data to advance the field are available. In an initiative funded by the Joint Programme for Neurodegenerative Disease Research, 55 international experts surveyed and assessed available data, starting with European cohorts, to promote data sharing to advance understanding of how vascular disease affects brain structure and function, optimize methods for cerebrovascular disease in neurodegeneration research, and focus future research on gaps in knowledge. Here, we summarize the results and recommendations from this initiative. We identified data from over 90 studies, including over 660,000 participants, many being additional to neurodegeneration data initiatives. The enthusiastic response means that cohorts from North America, Australasia, and the Asia Pacific Region are included, creating a truly global, collaborative, data sharing platform, linked to major national dementia initiatives. Furthermore, the revised World Health Organization International Classification of Diseases version 11 should facilitate recognition of vascular-related brain damage by creating one category for all cerebrovascular disease presentations and thus accelerate identification of targets for dementia prevention

Socio-environmental modelling for sustainable development: Exploring the interplay of formal insurance and risk-sharing networks

As envisaged in the Sustainable Development Goals, eradicating poverty by 2030 is among the most important steps to achieve a better and more sustainable future. A key contribution to reach this target is to ensure that vulnerable households are effectively protected against weather-related extreme events and other economic, social and ecological shocks and disasters. Insurance products specifically designed for the needs of low-income households in developing countries are seen as an effective instrument to encompass also the poor with an affordable risk-coping mechanism and are thus highly promoted and supported by governments in recent years. However, apart from direct positive effects, the introduction of formal insurance may have unintended side effects. In particular, it might affect traditional risk-sharing arrangements where income losses are covered by an exchange of money, labour and in-kind goods between neighbours, relatives or friends. A weakening of informal safety nets may increase social inequality if poor households cannot afford formal insurance. In order to design insurance products in a sustainable way, sound understanding of their interplay with risk-sharing networks is urgently needed. Socio-environmental modelling is a suitable approach to address the complexity of this challenge. In the first part of this thesis, an agent-based model is developed to investigate the effects of formal insurance and informal risk-sharing on the resilience of smallholders. To lay the conceptual foundation for this approach, a literature review is presented which provides an overview of how to couple agent-based modelling with social network analysis. In two subsequent modelling studies, it is analysed (i) how the introduction of insurance influences the overall welfare in a population and (ii) what determines the resilience of the poorest to shocks when income is heterogeneously distributed and not all households can afford formal insurance. The simulation results underline the importance of designing insurance policies in close alignment with established risk-coping arrangements to ensure sustainability while striving to eradicate poverty. It is shown that introducing formal insurance can have negative side effects when insured households have fewer resources to share with their uninsured peers after paying the insurance premium or when they reduce their solidarity. However, especially when many households are simultaneously affected by a shock, e.g. by droughts or floods, formal insurance is a valuable addition to informal risk-sharing. By applying a regression analysis to simulation results for an empirical network from the Philippines, it is furthermore inferred that network characteristics must be considered in addition to individual household properties to identify the most vulnerable households that neither have access to formal insurance nor are adequately protected through informal risk-sharing. In the second part of this thesis, a broader perspective is taken on the use of models in socio-environmental systems. First, it is envisioned how models in combination with empirical studies could improve insurance design under climate change. Second, requirements for making socio-environmental modelling more useful to support policy and management and scientific results more influential on policy-making are synthesised. Overall, this thesis offers new insights into the interplay of formal and informal risk-coping instruments that complement existing empirical research and underlines the potential of socio-environmental modelling to address sustainability and development challenges

How to make socio‐environmental modelling more useful to support policy and management?

Abstract Dynamic process‐based modelling is often proposed as a powerful tool to understand complex socio‐environmental problems and to provide sustainable solutions as it allows disentangling cause and effect of human behaviour and environmental dynamics. However, the impact of such models in decision‐making and to support policy‐making has so far been very limited. In this paper, we want to take a critical look at the reasons behind this situation and propose steps that need to be taken to change it. We investigate a number of good practice examples from fields where models have influenced policy‐making and management to identify the main aspects that promote or impede the application of these models. Specifically, we compare examples that differ in their extent to how explicitly they represent human behaviour as part of the model, ranging from purely environmental systems (including models for river management, honeybee colonies and animal diseases), where modelling techniques have long been established, to coupled socio‐environmental systems (including models for land use, fishery management and sustainable water use). We use these examples to synthesise four key factors for successful modelling for policy and management support in socio‐environmental systems. They cover (a) the specific requirements caused by modelling the human dimension, (b) the importance of data availability and accessibility, (c) essential elements of the partnership between modellers and decision‐makers and (d) insights related to characteristics of the decision process. For each of these aspects, we give recommendations specifically to modellers, decision‐makers or both to make the use of models for practice more effective. We argue that if all parties involved in the modelling and decision‐making process take into account these suggestions during their collaboration, the full potential that socio‐environmental modelling bears can increasingly unfold. A free Plain Language Summary can be found within the Supporting Information of this article.ISSN:2575-831

D6.5 Integration guide for using common CGE/PE models with BESTMAP models

This deliverable report provides an integration guide on how information gained in BESTMAP’s agent-based model can be used in the standard economic model to improve the assessment of agricultural policies in the European Union. First, the models used in the BESTMAP are explained. The integration guide discusses in detail the preconditions and challenges when linking agent-based models with standard economic models such as partial and general equilibrium models. As a result of an expert workshop, six challenges are identified. The report also presents suggestions on how to make use of the finding and presents a way forward to integrate the two types of models

Characteristics of a prospective cohort of short-term travelers from the Netherlands who visited a malaria-endemic area, October 2006–October 2007.

<p>Characteristics of a prospective cohort of short-term travelers from the Netherlands who visited a malaria-endemic area, October 2006–October 2007.</p

Determinants for 75% adherence to malaria chemoprophylaxis during travel among a prospective cohort of 620 travelers from the Netherlands to high-endemic areas, October 2006–October 2007.

b<p>In the multivariable analysis the variable ‘type of chemoprophylaxis’ was included without the category ‘other’ because of 100% compliance, so multivariable analysis was done with 610 travelers.</p

Adherence to the most-prescribed antimalarial chemoprophylaxis among travelers who started with recommended chemoprophylaxis.

<p>NA, not applicable.</p