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Analysis of benthic species abundance Environmental sensitivity to stressors Organic enrichment Physical disturbance Factorial data experiment Three-way correspondence analysis Bayesian network Hidden variable Spatial autocorrelation Biomass prediction Functional network Trophic interaction Climate changeHidden variableFunctional ecosystem changeBio-physicalIndicatorsMarine renewable energy Network analysis Connectivity Larval dispersal North Sea Oil and gas structures Hotspots Marine spatial management Pacific oysters Internal variability Climate change CMIP6 Pacific oysters Invasive species Convolutional neural networks Deep learning Drone Remote sensing Ecological management

Number of items: 6.

Analysis of benthic species abundance Environmental sensitivity to stressors Organic enrichment Physical disturbance Factorial data experiment Three-way correspondence analysis

Kroonenberg, PM, Widdicombe, S and Somerfield, PJ 2024 The relative impact of co-occurring stressors on the abundance of benthic species examined with three-way correspondence analysis. Ecological Informatics, 80. 102483. 10.1016/j.ecoinf.2024.102483

Bayesian network Hidden variable Spatial autocorrelation Biomass prediction Functional network Trophic interaction

Trifonova, N, Kenny, A, Maxwell, D, Duplisea, D, Fernandes, JA and Tucker, A 2015 Spatio-temporal Bayesian network models with latent variables for revealing trophic dynamics and functional networks in fisheries ecology. Ecological Informatics, 30. 142-158. 10.1016/j.ecoinf.2015.10.003

Climate changeHidden variableFunctional ecosystem changeBio-physicalIndicatorsMarine renewable energy

Trifonova, N, Wihsgott, JU and Scott, BE 2025 Propagating uncertainty from physical and biogeochemical drivers through to top predators in dynamic Bayesian ecosystem models improves predictions. Ecological Informatics. 103510. 10.1016/j.ecoinf.2025.103510 (In Press)

Network analysis Connectivity Larval dispersal North Sea Oil and gas structures Hotspots Marine spatial management

James, MK, Lessin, G, Al Azhar, M, Bedington, M, Clubley, CH, Somerfield, PJ and Knights, AM 2025 The ‘everything is everywhere’ framework: Holistic network analysis as a marine spatial management tool. Ecological Informatics, 87. 103105. 10.1016/j.ecoinf.2025.103105

Pacific oysters Internal variability Climate change CMIP6

Wilson, RJ, Kay, S and Ciavatta, S 2024 Partitioning climate uncertainty in ecological projections: Pacific oysters in a hotter Europe. Ecological Informatics, 80. 102537. 10.1016/j.ecoinf.2024.102537

Pacific oysters Invasive species Convolutional neural networks Deep learning Drone Remote sensing Ecological management

Mata, A, Moffat, D, Almeida, S, Radeta, M, Jay, W, Mortimer, N, Awty-Carroll, K, Thomas, OR, Brotas, V and Groom, SB 2024 Drone imagery and deep learning for mapping the density of wild Pacific oysters to manage their expansion into protected areas. Ecological Informatics, 82. 1-12. 10.1016/j.ecoinf.2024.102708

This list was generated on Sat Dec 6 13:36:03 2025 UTC.