The recent advancement in data science coupled with the revolution in digital and satellite
technology has improved the potential for artificial intelligence (AI) applications in the …

Advances in the understanding of physical, chemical, and biological processes influencing
water quality, coupled with improvements in the collection and analysis of hydrologic data …

Microplastic pollution is an issue of concern due to the accumulation rates in the marine
environment combined with the limited knowledge about their abundance, distribution and …

Ecosystems are becoming damaged or degraded as a result of stresses especially
associated with human activities. A healthy ecosystem is essential to provide the services …

As one of the earth's key ecosystems, rivers have been intensively studied and modelled
through the application of machine learning (ML). With the amount of large data available …

Deep learning algorithms have improved predictive model performance in a variety of
disciplines because of their ability to approximate complex functions. However, the amount …

Scientists and decision-makers need tools that can assess which specific pressures lead to
ecosystem deterioration, and which measures could reduce these pressures and/or limit …

Freshwater ecosystems will be profoundly affected by global climate change, especially
those in mountainous areas, which are known to be particularly vulnerable to warming …

Artificial Neural Networks (ANNs) have wide applications in aquatic ecology and specifically
in modelling water quality and biotic responses to environmental predictors. However, data …

In order to efficiently manage nonindigenous species (NIS), predictive tools are needed to
prioritize locations where they are likely to become established and where their impacts will …