An Ecosim Model for Exploring Gulf of Mexico Ecosystem Management Options: Implications of Including Multistanza Life-History Models for Policy Predictions
By Carl J Walters, S. Martell, Villy Christensen, B. Mahmoudi. 2008
113 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/1b8e47a7527c8a39f52f1d3e188be6c2aad8be74
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Wwl Cheung
- Marta Coll
- M. Peck
- Villy Christensen
- Elizabeth A. Fulton
- R. Watson
- Daniel Pauly
- Christos Arvanitidis
Citations in the corpus
- Red snapper management in the Gulf of Mexico: science- or faith-based? (2011, unknown): “Most importantly, if spawning stock biomass is still too low to produce the minimum number of eggs (primarily due to the truncated age distribution, Walters et al. 2008a) to avoid recruitment overfishing, even accepting the likelihood for some recruitment compensation, the debate (including AvP)…”
- Projecting changes in the distribution and productivity of living marine resources: A critical review of the suite of modelling approaches used in the large European project VECTORS (2016, methodology): “An Ecosim model for exploring Gulf of Mexico ecosystem management options: Implications of including multistanza life-history models for policy predictions.”
- Interesting times: winners, losers, and system shifts under climate change around Australia (2011, methodology): “EwE can include age structure of key groups— using life-history stanzas (Walters et al., 2008)—and this was the case for two groups in this model (mangrove jacks and small schooling fish, updated to this form from an earlier age-structured method used in Gribble, 2003).”
- The global ocean is an ecosystem: simulating marine life and fisheries (2015, methodology): “…dynamic Ecosim model (Walters et al., 1997, 2000) to evaluate settings for a number of parameters (notably the baseline biomasses and P/B rates for exploited groups) based on the model’s ability to replicate catch time series (e.g. Shannon et al., 2004; Coll et al., 2008c; Walters et al., 2008).”