There are four levels of products and analyses conducted by FWDP:
1)Basic
2)Inferential/Retrospective
3)Predictive/Modeling
4)Theoretical
We examine the relative importance of fishery and natural mortality, identify critical life stages, estimate biomass and production partitioning in the system, evaluate multi-species yield dynamics, assess the impact of fishery management scenarios based an understanding of food web connectivity, and simply answer questions of "what does that fish eat..........?".
See our recent ICES Posters regarding A
Program Overview, Spatial Overlap,
Dietary Overlap, Piscivory,
and Ecosystem Goods and Services.
Very Large Files >2.5 M
1) Basic- we produce species profiles (descriptiors of who's eating who) across life histories of these fish including simple diet parameters: e.g. frequency of occurence for particular prey, diet composition, total amount of food consumed, diet overlap matrices and other comparisons, guilds, clustering by diet, etc. These are basically data summaries, exploratory, and observational analyses, and provide most of the information included in multi-species comparisons and similar reports.
Diet overlap of major species in the northeast continetal shelf ecosystem. 0 is low, 1 is high dietary overlap
2) Inferential/Retrospective- we attempt to determine what has happened in this fish community using time-series modeling; hypothesis testing for differences across regions, decades, depths, size classes, predators, etc.; multivariate analyses; and related analyses.
Examples include:
Changes in diet overlap and other estimates of competition among selected
species
Community interaction matrices
Changes in energy flows within the ecosystem across several decades
The magnitude of predation on larval fish, especially gadids, by herring and mackerel
Life history phases of key fish (in terms of trophic ecology) and essential fish habitat
Differential (predation) mortality based upon size
Consumption estimates of the pelagic fish community, contrasted with pelagic fishery landings
3) Predictive/Modeling- based upon what we understand, what will likely happen to the multi-species yield dynamics and community composition? We use short-term forecasts, time series forecasts, empirical/statistical modeling, and are developing mechanistic/deterministic models. Our models are both static and dynamic to provide instantaneous solutions for snapshot views and to link growth with predation and fishing for better assessments of yield across time. A major objective is to contrast fishing vs natural mortality. The ultimate goal is to produce predictive models of fish biomass to address scenarios of "What happens if.........?"
Examples include:
Multiple Species Models
Cross-linking population dynamics between predator
and prey populations (F vs M for key species)
Multi Species Virtual Population Analysis (MSVPA)
on key Georges Bank species: incorporating estimates of predation mortality
and similar age-structured models
Generalized Consumption Models
Predator-prey interaction models
