Adaptation, the ability to adjust to environmental or internal changes, is a key characteristic of living systems. In a rapidly changing world integrated knowledge of the nature, potential and limitations of adaptation, from the molecular and cellular levels up to the level of species interactions in ecosystems, is urgently needed. Yet, adaptive processes at different levels of biological organization are mostly studied in isolation. Disciplines like medical biology or behavioural neurosciences tend to ask ‘proximate’ research questions that focus on the mechanisms underlying adaptation (How does an organism respond?). In contrast, disciplines like ecology and evolutionary biology primarily ask ‘ultimate’ questions on the eco-evolutionary forces driving adaptation (Why has a particular mechanism evolved?).
At present proximate- and ultimate-oriented disciplines use different concepts and terminology while studying intrinsically linked aspects of the same adaptive processes. This impedes the exchange of ideas, insights, and research methods, while these fields could profit enormously from each other. Internationally there is a growing realization that proximate and ultimate approaches need each other in order to make firm progress in understanding and predicting adaptation in a wide array of systems, requiring an integration of neurological, physiological, behavioural, ecological and evolutionary perspectives.
Evolution on a long time scale has shaped the regulatory mechanisms acting on short time scales that determine the potential and limitations in adaptive capacity. This is relevant for understanding the prevalence and treatment of diseases, including energetic and metabolic diseases, individual differences in aging and health that determine the scope for personalized medicine, as well as the adaptive capacity and maladaptation of organisms in modern commercial farming. In turn, the nature of these mechanisms determines the potential, direction, speed, and limitation for evolutionary change. This is important for, among others, predicting the effects of virus mutation and zoönosis (co-evolution of host–parasite interactions), understanding speciation and changes in biodiversity, predicting effects of global change, and brain adaptations to cope with environmental challenges.
Integrating these approaches has the potential to provide a new foundation for the life sciences. Recent findings, such as adaptation by non-genetic inheritance, evolution taking place on much shorter time scales than previously thought, brain plasticity being much larger than previously assumed, and cascading adaptive responses in species interaction networks, request a much more integrative approach. After the genomics revolution, it is now time for an evolutionary life sciences revolution in which the key adaptive processes from genes to organisms to populations to ecosystems are fully integrated.
Three main research domains will be developed in the theme Adaptive Life, that each result in a range of applications to key questions at stake in the Sustainable Society and the Healthy Aging societal priority areas of RUG, as well as boosting fundamental progress:
The Adaptive Life theme will be primarily developed within the Groningen Institute for Evolutionary Life Sciences (GELIFES) where adaptation is a key issue in the research programme, as the ability to adjust to environmental, developmental or physiological changes is a key aspect of living systems.
The AL theme provides excellent opportunities for connecting to robotics and other human-designed adaptive systems (ALICE and ENTEG), to the modelling of cognition and neural networks (ALICE), to understanding biological processes at the molecular level (GBB), to research on energetics and metabolism (ESRIG, GBB), to biomedical (MW/UMCG) and pharmaceutical research (GRIP), and for understanding complex systems (CSB) in relation to large data (JBI, ALICE). The AL theme further opens excellent opportunities for extending collaborations with other faculties, such as FRW, FMW, MAGW and Arts, resulting in promising cross-disciplinary research.
|Laatst gewijzigd:||27 juli 2017 09:42|