Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence - Chapter 1 - Climate uncertainties and biodiversity: An overview

Biological systems are being affected by anthropogenic climate change at many dimensions, from ecosystems to genes, according to data from around the world. Temperature and precipitation changes, as well as the associated variations in winter severity, plant phenology, drought and conditions of wildlife, distribution of invasive species and predation, abundance and disease, all have the potential to influence ungulates directly or indirectly. The reactions of ungulates to climatic fluctuation and change, on the other hand, are not consistent and vary by species and region. This has consequences for the species' long-term survival. Variations in rainfall and patterns of temperature have an impact on habitat quality and, as a result, wildlife species abundance and distribution. Due to their ecology, large herbivores like elephants and hippopotamuses are particularly sensitive to climate change, whereas other species are less so. Climate-related severe events, in combination with other human stresses, combine to change in availability and distribution of animal resource. Understanding how these climate variables affect animal resources is critical for adaptive management and conservation. Human beings, as active agents, can effectively control the related health effects by taking proactive measures such as gaining an improved understanding of compound disease-specific health effects, changes in climate, and allocating resources and technologies efficiently to promote public awareness and healthy lifestyles. Adaptation measures include to find additional scientific reasons for the link between climate change and infectious illnesses beyond empirical evidence; to enhance the forecast of climate change, spatial-temporal processes and related changes in infectious disease at diverse temporal and geographical scales; and to create efficient early warning systems for the health impacts of predicted change in climate.