Parameter estimation for basin-scale ecosystem-linked population models of large pelagic predators: Application to skipjack tuna

By I. Senina, John Sibert, P. Lehodey. 2008

107 citations recorded by the source corpus.

Subfields: Genetics, Global and Planetary Change, Public Health, Environmental and Occupational Health

View Paper: https://www.semanticscholar.org/paper/61361b5b1c4e2fe9a8287a2fbfbd9b20f6b89b11

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Genetics

1. Raghu Murtugudde
2. I. Senina
3. P. Lehodey
4. Verena M. Trenkel
5. J. Neilson

In Global and Planetary Change

1. I. Senina
2. Raghu Murtugudde
3. S. Nicol
4. B. Calmettes
5. J. Hampton
6. P. Lehodey
7. L. Nøttestad
8. David E. Richardson

In Public Health, Environmental and Occupational Health

1. Raghu Murtugudde
2. I. Senina
3. P. Lehodey

Citations in the corpus

• AD Model Builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models (2012, unknown): “The efficiency and stability of parameter estimation in ADMB makes it ideal for nonlinear models that are highly parameterized [18,25,41], simpler nonlinear models with hundreds of thousands of data points [39,42], or complex nonlinear models that are parameter-rich and include large data sets [58].”
• Modelling the impact of climate change on Pacific skipjack tuna population and fisheries (2013, methodology): “the tropical Pacific Ocean, strongly affects migration, abundance and catches of tuna (Lehodey et al. 1997; Lehodey 2001; Senina et al. 2008).”
• Comparative ecology of widely distributed pelagic fish species in the North Atlantic: Implications for modelling climate and fisheries impacts (2014, methodology): “The Spatial Ecosystem and Population Dynamics Model (SEAPODYM) which has been 23 parameterised for albacore in the South Pacific (Lehodey et al., 2008; Senina et al., 2008) 24 will be applied to the North Atlantic population.”
• A spatial ecosystem and populations dynamics model (SEAPODYM) – Modeling of tuna and tuna-like populations (2008, methodology): “While the present paper focuses on the description of new developments in the model and illustration of its capacity to capture important features of spatial dynamics of different tuna species in the Pacific Ocean, the actual validation is presented in a companion paper describing the approach to ha”
• Bridging the gap from ocean models to population dynamics of large marine predators: A model of mid-trophic functional groups (2010, background): “Thus, it becomes possible to use fishing data for model parameters optimisation and test if the mechanisms included into the deterministic model can be justified from available data (Senina et al., 2008).”