Environmental DNA (eDNA) is the fastest growing biomonitoring tool fuelled by two key
features: time efficiency and sensitivity. Technological advancements allow rapid …

Conservation of marine ecosystems has been highlighted as a priority to ensure a
sustainable future. Effective management requires data collection over large spatio-temporal …

Choices made in modeling matter and demand more explication since they determine how
much we can trust modeling insights and predictions within their social, political and ethical …

Applied ecology has traditionally approached management problems through a simplified,
single-species lens. Repeated failures of single-species management have led us to a new …

Species distribution models are commonly applied to predict species responses to
environmental conditions. A wide variety of models with different properties exist that vary in …

Monitoring land use change dynamics is critical for tackling food security, climate change,
and biodiversity loss on a global scale. This study is designed to classify land use and land …

Freshwater biodiversity loss is accelerating globally, but humanity can change this trajectory
through actions that enable recovery. To be successful, these actions require coordination …

Abstract Machine learning modeling techniques have emerged as a potential means for
predicting algal blooms. In this study, synthetic spatio-temporal water quality data for a river …

Predicting the impacts of multiple stressors is important for informing ecosystem
management but is impeded by a lack of a general framework for predicting whether …

Understanding the complex interlinkages between humans and nature is crucial for
develo** strategies to effectively manage natural resources and to enhance resilience of …