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"Forest avifauna exhibit enduring responses to historical high-severity" by Michael J.M. Franklin, Richard E. Major et al.

Forest fire size, frequency and severity are increasing worldwide, with corresponding reductions in long-unburnt habitat and greater modification of forest structure over wider areas. Understanding the implications for animals is imperative in optimizing management for species persistence and overall biodiversity. We investigated how avian responses to historical high-severity fire differ in forests at short (five years) and mid-range (16 years) time since fire, including whether increased time since fire mitigates any negative responses to high-severity fire. Sites were established in fire-prone dry forests of the Greater Blue Mountains World Heritage Area, Australia. A Bayesian latent variable analysis of bird data obtained from acoustic recordings was used to estimate the occurrence of 74 species in relation to time since fire (short, mid-range), the spatial extent of historical high-severity fire (limited, extensive), and their interaction. Time since fire influenced the number of ....

Greater Blue Mountains World Heritage Area , Acoustic Survey , Bayesian Inference , Fire Severity , Forest Birds , Latent Variable Model , Ime Since Fire ,

Estimating the informativeness of data

MIT researchers discovered a new way to estimate the amount of information contained in a piece of data using probabilistic programming and probabilistic inference. The breakthrough entropy estimators open up new applications in medicine, scientific discovery, cognitive science, and artificial intelligence. ....

Claude Shannon , Feras Saad , Vikash Mansinghka , Department Of Brain , Cognitive Sciences , Mathematical Theory , Emeritus Claude Shannon , Marco Cusumano Towner Phd , Probabilistic Models , Mit Csail , Probabilistic Computing Project , Information Theory , Probabilistic Programming , Probabilistic Inference , Ntropy Estimators , Ikash Mansinghkha , Feras Saad , Bayesian Inference , Artificial Intelligence Research , Ntropy Via Inference Eevi , Medical Diagnoses , Claude Shannon ,