Russell Milne
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Russell Milne has a total of 38 co-authors. Here are the top co-authors by number of shared publications:
- Hao Wang
Department of Mathematical and Statistical Sciences University of Alberta Edmonton Canada
9 shared publications Madhur Anand
Department of Applied Mathematics, University of Waterloo, Waterloo, Canada
6 shared publicationsChris T. Bauch
Department of Applied Mathematics, University of Waterloo, Waterloo, Canada
5 shared publications- Ali Hamidoğlu
Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Canada
2 shared publications - B. A. Zambrano-Luna
School of Mathematical & Statistical Sciences, University of Texas Rio Grande Valley, One West University Blvd., Brownsville, TX 78520, USA
2 shared publications Ling Xue
College of Mathematical Sciences, Harbin Engineering University, Harbin, Heilongjiang, 150001, China
2 shared publications
Latest Publications
- 31 October 2026
- Published by Springer Nature in Theoretical Ecology
- Vol. 19 (1) , 22
Reef fish functional groups show variable declines due to deforestation-driven sedimentation, while flexible harvesting mitigates this damage
- 31 October 2026
- Published by Springer Nature in Theoretical Ecology
- Vol. 19 (1) , 22
Reef fish functional groups show variable declines due to deforestation-driven sedimentation, while flexible harvesting mitigates this damage
- Open Access
- 18 July 2026
- Published by Elsevier in Mathematical Biosciences
- Vol. 400, 109769
Modelling the impact of diffusion and eutrophic conditions on fungal parasite transmission in poorly-mixed waters
- 18 July 2026
- Published by Elsevier in Mathematical Biosciences
- Vol. 400, 109769
Open AccessModelling the impact of diffusion and eutrophic conditions on fungal parasite transmission in poorly-mixed waters
- Open Access
- 24 May 2026
- Published by Elsevier in Ecological Modelling
- Vol. 519
Deciphering culprits for cyanobacterial blooms and lake vulnerability in north-temperate lakes
- 24 May 2026
- Published by Elsevier in Ecological Modelling
- Vol. 519
Open AccessDeciphering culprits for cyanobacterial blooms and lake vulnerability in north-temperate lakes
- Open Access
- 26 February 2026
- Published by Elsevier in Renewable and Sustainable Energy Reviews
- Vol. 233
A game theory approach for the construction of a green and sustainable power grid
- 26 February 2026
- Published by Elsevier in Renewable and Sustainable Energy Reviews
- Vol. 233
Open AccessA game theory approach for the construction of a green and sustainable power grid
- Open Access
- 3 November 2025
- Published by Elsevier in Journal of Environmental Management
- Vol. 395, 127748
Dispersion based recurrent neural network model for methane monitoring in Albertan tailings ponds
- 3 November 2025
- Published by Elsevier in Journal of Environmental Management
- Vol. 395, 127748
Open AccessDispersion based recurrent neural network model for methane monitoring in Albertan tailings ponds
- Open Access
- 15 October 2025
- Published by Elsevier in Atmospheric Environment
- Vol. 363
Improved monitoring of methane emissions for the oil and gas sector with Sentinel-2 satellite observations
- 15 October 2025
- Published by Elsevier in Atmospheric Environment
- Vol. 363
Open AccessImproved monitoring of methane emissions for the oil and gas sector with Sentinel-2 satellite observations
- Open Access
- 30 September 2025
- Published by Elsevier in Applied Energy
- Vol. 401
A novel evolutionary game-based low-methane application in three-echelon energy supply chains
- 30 September 2025
- Published by Elsevier in Applied Energy
- Vol. 401
Open AccessA novel evolutionary game-based low-methane application in three-echelon energy supply chains
- Open Access
- 29 September 2025
- Published by Springer Nature in Research Square
Reef fish functional groups show variable declines due to deforestation-driven sedimentation, while flexible harvesting mitigates this damage
Sedimentation is a major coral reef stressor, with effects including suppressing algae consumption by herbivorous fish. This puts pressure on reef fish populations and the fisheries that harvest them. Deforestation causes much sedimentation on reefs, and is an ongoing concern in many tropical island states. Although ecosystem processes like deforestation and fish population dynamics are usually far from equilibrium, explicitly time-dependent analyses of reef fish vulnerability to deforestation are rare. Additionally, optimization methods for fisheries on heavily sedimented reefs are generally unexplored. Here, we construct a model coupling four reef fish functional groups with seabed dynamics and deforestation, parametrized to represent a wide variety of tropical coastal forests. We show that with predicted human population increases, highland deforestation could cause omnivorous fish abundances to halve within 15-30 years, and piscivorous fish and top predators to do so around 20 years later. In contrast, piscivorous fish and top predators are resilient to lowland deforestation, and herbivorous fish populations often recover after initial declines during sedimentation pressure. We demonstrate that flexible fishing approaches could lead to high and temporally stable populations of most functional groups, offsetting sedimentation-related stress. We show that the combination of deforestation and increased fishing demand due to human population growth may cause medium-term local reef fish extirpation. Our results provide sustainability guidelines for reef fisheries, and demonstrate nonlinear interactions between overfishing and deforestation.
- 29 September 2025
- Published by Springer Nature in Research Square
Open AccessReef fish functional groups show variable declines due to deforestation-driven sedimentation, while flexible harvesting mitigates this damage
Sedimentation is a major coral reef stressor, with effects including suppressing algae consumption by herbivorous fish. This puts pressure on reef fish populations and the fisheries that harvest them. Deforestation causes much sedimentation on reefs, and is an ongoing concern in many tropical island states. Although ecosystem processes like deforestation and fish population dynamics are usually far from equilibrium, explicitly time-dependent analyses of reef fish vulnerability to deforestation are rare. Additionally, optimization methods for fisheries on heavily sedimented reefs are generally unexplored. Here, we construct a model coupling four reef fish functional groups with seabed dynamics and deforestation, parametrized to represent a wide variety of tropical coastal forests. We show that with predicted human population increases, highland deforestation could cause omnivorous fish abundances to halve within 15-30 years, and piscivorous fish and top predators to do so around 20 years later. In contrast, piscivorous fish and top predators are resilient to lowland deforestation, and herbivorous fish populations often recover after initial declines during sedimentation pressure. We demonstrate that flexible fishing approaches could lead to high and temporally stable populations of most functional groups, offsetting sedimentation-related stress. We show that the combination of deforestation and increased fishing demand due to human population growth may cause medium-term local reef fish extirpation. Our results provide sustainability guidelines for reef fisheries, and demonstrate nonlinear interactions between overfishing and deforestation.
- 4 July 2025
- Published by Elsevier in Mathematical Biosciences
- Vol. 387, 109501
Modeling mixotroph-bacterium dynamics: Spatial homogeneity vs heterogeneity
- 4 July 2025
- Published by Elsevier in Mathematical Biosciences
- Vol. 387, 109501
Modeling mixotroph-bacterium dynamics: Spatial homogeneity vs heterogeneity
- Open Access
- 11 December 2024
- Published by Elsevier in Ecological Indicators
- Vol. 170
Decoding methane concentration in Alberta oil sands: A machine learning exploration
- 11 December 2024
- Published by Elsevier in Ecological Indicators
- Vol. 170
Open AccessDecoding methane concentration in Alberta oil sands: A machine learning exploration