Large-scale and long-term wildlife research and monitoring using camera traps: a continental synthesis.

Camera traps are widely used in wildlife research and monitoring, so it is imperative to understand their strengths, limitations, and potential for increasing impact. We investigated a decade of use of wildlife cameras (2012-2022) with a case study on Australian terrestrial vertebrates using a multifaceted approach. We (i) synthesised information from a literature review; (ii) conducted an online questionnaire of 132 professionals; (iii) hosted an in-person workshop of 28 leading experts representing academia, non-governmental organisations (NGOs), and government; and (iv) mapped camera trap usage based on all sources.

Learning a global underwater geolocalization model with sectoral transformer.

Polarization-based underwater geolocalization presents an innovative method for positioning unmanned autonomous devices beneath the water surface, in environments where GPS signals are ineffective. While the state-of-the-art deep neural network (DNN) method achieves high-precision geolocalization based on sun polarization patterns in same-site tasks, its learning-based nature limits its generalizability to unseen sites and subsequently impairs its performance on cross-site tasks, where an unavoidable domain gap between training and test data exists. In this paper, we present an advanced Deep Neural Network (DNN) methodology, which includes a neural network built on a Transformer architecture, similar to the core of large language models such as ChatGPT, and integrates an unscented Kalman filter (UKF) for estimating underwater geolocation using polarization-based images.

Farm management and landscape context shape plant diversity at wetland edges in the Prairie Pothole Region of Canada.

Evaluating the impacts of farming systems on biodiversity is increasingly important given the need to stem biodiversity loss, decrease fossil fuel dependency, and maintain ecosystem services benefiting farmers. We recorded woody and herbaceous plant species diversity, composition, and abundance in 43 wetland-adjacent prairie remnants beside crop fields managed using conventional, minimum tillage, organic, or perennial cover (wildlife-friendly) land management in the Prairie Pothole Region. We used a hierarchical framework to estimate diversity at regional and local scales (gamma, alpha), and how these are related through species turnover (beta diversity).

Evidence of Australian wild deer exposure to N. caninum infection and potential implications for the maintenance of N. caninum sylvatic cycle.

Infections with the coccidian parasite Neospora caninum affect domestic and wild animals worldwide. In Australia, N. caninum infections cause considerable losses to the cattle industry with seroprevalence of 8.

Impact of a Pandemic as a Forced Disruption in Nursing Education.

The purpose of this study was to determine the impact of a pandemic as a forced disruption in nursing education to recover from and prepare for current and future disruptions. Four qualitative themes from Midwestern nursing professional development providers ( n = 60) noted impacts. Recommendations for nursing professional development leaders to support staff during turbulent times include preparation for online teaching and learning, and improved communication regarding essential education.