scispace - formally typeset
P

PK Bricher

Researcher at University of Tasmania

Publications -  16
Citations -  267

PK Bricher is an academic researcher from University of Tasmania. The author has contributed to research in topics: Azorella macquariensis & Population. The author has an hindex of 6, co-authored 16 publications receiving 211 citations. Previous affiliations of PK Bricher include University of Queensland.

Papers
More filters
Journal ArticleDOI

Delivering Sustained, Coordinated, and Integrated Observations of the Southern Ocean for Global Impact

Louise Newman, +53 more
TL;DR: The Southern Ocean Observing System (SOOS) has established networks for enhancing regional coordination and research community groups to advance development of observing system capabilities as mentioned in this paper, which is to develop a circumpolar system that ensures time series of key variables, and deliver the greatest impact from data to all key end users.
Journal ArticleDOI

Population trends of Adélie penguin (Pygoscelis adeliae) breeding colonies: a spatial analysis of the effects of snow accumulation and human activities

TL;DR: Whether potential changes in snow cover and/or proximity to human activities were able to explain the varying population trends of colonies at two breeding localities near Casey, East Antarctica is examined.

Population trends of Adélie penguin (Pygoscelis adeliae) breeding colonies: a spatial analysis of the eVects of snow accumulation and human activities

TL;DR: This paper used Geographic Information Systems and decision trees to examine whether potential changes in snow cover and/or proximity to human activities were able to explain the varying population trends of colonies at two breeding localities near Casey, East Antarctica.
Journal ArticleDOI

Mapping sub-Antarctic cushion plants using random forests to combine very high resolution satellite imagery and terrain modelling

TL;DR: This study combines spectral data from very high resolution WorldView-2 satellite imagery and terrain variables from a high resolution digital elevation model to improve mapping accuracy, in both pixel- and object-based classifications.