An analytical study on the effect of weather changes on birds in a machine learning perspective

Abstract

Building applications that make use of the speed and specificity of algorithm development can significantly help attempts to quantify and analyze variations in bird behavior in response to weather changes in the age of machine learning. For both endotherms and ectotherms, temperature can affect everything from daily energy budgets to nesting behaviors. In birds, environmental temperature plays a key role in shaping parental incubation behavior and temperatures experienced by embryos. One of the main mechanisms used to mitigate the impacts of climate change on these species in the near future is to assess the current system of protected areas. It is necessary to ensure that these areas will continue being effective in conserving these species even under climate change. The purpose of this paper was to review the challenges faced by birds due to climate change, how it affects their growth, migration, breeding, etc. and how machine learning models can have considerable usage in helping to find out the problems affected by birds due to climate change.