Erratum: Corrigendum: The distribution and behavioral characteristics of plateau pikas (). ZooKeys 1059: 157-171. https://doi.org/10.3897/zookeys.1059.63581.

[This corrects the article DOI: 10.3897/zookeys.1059.

The distribution and behavioral characteristics of plateau pikas ().

Plateau pikas () are regarded as one of the main causes of the degradation of alpine meadows in the Qinghai-Tibet Plateau (QTP). The population density of plateau pikas is directly related to the degree of grassland damage. In this study, field observation was conducted for one week in the southeastern QTP in August 2019.

A density estimation model of plateau pika () supporting camera-monitoring programs.

As an important species in the Qinghai-Tibet Plateau, the roles played by plateau pikas in grassland degradation and protection are controversial. The behavior characteristics and population density of this species are important in answering this question, but these traits have not been fully elucidated to date. Camera-capture methods have been used widely in recent years to characterize or calculate population density with the advantage of simple operation and nonintrusive investigation.

A Novel Crow Swarm Optimization Algorithm (CSO) Coupling Particle Swarm Optimization (PSO) and Crow Search Algorithm (CSA).

The balance between exploitation and exploration essentially determines the performance of a population-based optimization algorithm, which is also a big challenge in algorithm design. Particle swarm optimization (PSO) has strong ability in exploitation, but is relatively weak in exploration, while crow search algorithm (CSA) is characterized by simplicity and more randomness. This study proposes a new crow swarm optimization algorithm coupling PSO and CSA, which provides the individuals the possibility of exploring the unknown regions under the guidance of another random individual.