Description: Global climate change is exerting profound effects on organisms and ecosystems. As resource managers and policymakers must contend with the ongoing and future effects of global climate change, they challenge scientists to predict where, when, and with what magnitude these effects are most likely to occur. By understanding the processes by which human-managed and natural ecosystems respond to a changing climate, and by quantifying levels of confidence in our ability to predict these effects, we may be able to prepare for some of these impacts, a form of adaptation to climate change. Here, we describe how knowledge of physiology can help to inform management decisions. Because physiological tolerance to environmental factors varies between species, there will likely be “winners” and “losers” in the face of climate change. We explore how a failure to consider the details of an organism’s physiology and ecology can hamper efforts to respond proactively to climate change and, conversely, how an understanding of how nonhuman organisms interact with their environment can help to provide a framework for anticipating and preparing for future changes in natural and managed ecosystems. We examine some of the physiological responses of marine organisms to climate change in three examples: thermal stress in marine invertebrates, ramifications of water temperature changes on fish bioenergetics and thus on fish reproduction and growth, and effects of changes in wave forces on damage to corals and kelp. Because factors such as temperature interact with other stressors like overexploitation and pollution to drive patterns of mortality, it may be possible to prevent some damage by reducing the impact of stressors not related to climate change. Methods such as ecological forecasting and the utilization of bioenergetic budgets can be used to help guide future adaptation to climate change by providing forecasts within a probabilistic framework. Author:  Brian Helmuth Lauren Yamane Katharine J. Mach Shilpi Chhotray Phil Levin Sarah Woodin Issue:  Climate change Download:  61_Helmuth Final.pdf

Description: Publication date: Available online 1 September 2017 Source: The Egyptian Journal of Remote Sensing and Space Science Author(s): H.A. Bharath, M.C. Chandan, S. Vinay, T.V. Ramachandra Metropolitan cities in India are emerging as major economic hubs with an unprecedented land use changes and decline of environmental resources. Globalisation and consequent relaxations of Indian markets to global players has given impetus to rapid urbanisation process. Urbanisation being irreversible and rapid coupled with fast growth of population during the last century, contributed to serious ecological and environmental consequences. This necessitates monitoring and advance visualisation of spatial patterns of landscape dynamics for evolving appropriate management strategies towards sustainable development approaches. This study visualises the growth of Indian mega cities Delhi, Mumbai, Pune, Chennai and Coimbatore, through Cellular Automata Markov model considering the influence of agent(s) of urban growth through soft computing techniques. CA Markov model is considered to be one of most effective algorithm to visualise the growth of urban spatial structures. Prediction of growth using agent based modelling considering the spatial patterns of urbanisation during the past four decades has provided insights to the urban dynamics. The industrial, infrastructural, socio-economic factors significantly influence the urban growth compared to the biophysical factors. Visualisation of urban growth suggest agents driven growth in the cities and its surroundings with large land use transformations in urban corridors and upcoming Industrial and ear marked developmental zones. Integrating local agents of urban growth help in identifying specific regions of intense growth, likely challenges and provide opportunities for evolving appropriate management strategies towards sustainable cities during the 21st century.