“Providing a mechanistic link from climate variability to fisheries management”
The focus of the Environmental and Ecosystem variability modeling program within ERD is to use physical and biogeochemical models to mechanistically relate environmental variability to the dynamics of managed fisheries species. Several current modeling projects are aimed at either characterizing the level of variability of the physical environment relevant to the marine ecosystem, or understanding directly how physical factors, such as temperature or nutrient supply, affect the growth and dynamics of marine organisms.
- The effects of dormancy on the population dynamics of the common copepod genus Calanus along the US West Coast. This project is part of the GLOBEC North East Pacific program, and is co-funded by NSF and NOAA. This project uses IBM’s (described below) to understand how a particular biological process – namely, the overwintering phase, or “dormant” phase of a key CCS copepod – affects the population dynamics of this species under various climate change scenarios.
- The effect of timing of the spring transition on spring bloom dynamics within theCalifornia Current. This project uses NPZD-style models (described below), forced by observational data, to understand how interannual changes in upwelling, stratification, and mixed layer depth affect spring bloom dynamics, and therefore the availability of food for higher organisms.
What is Modeling?
Modeling is an important methodological approach for developing a deeper understanding of the mechanisms linking physical and environmental variability to ecosystem dynamics.
The most important feature of models, are that they can be based on underlying physical, chemical, and biological principles that control an ecosystem, and thus are linked directly to known mechanisms. Modeling is also a powerful tool because it allows for the filling in of “gaps” in observational data, thus allowing analysis of places or times where we lack full information. Lastly, models can be used to conduct theoretical “experiments” which would not be possible in the real world, where the response of the ecosystem to various climate change scenarios can be examined.
Models fall into many different categories. The two major types used for research within this program are 1) NPZD-style biogeochemical models (which stands for Nitrogen-Phytoplankton-Zooplankton-Detritus), and 2) IBM’s (which stands for Individual-Based Model). NPZD models are used to directly simulate the components of the food web as they respond to physical forcing, either from observational data, or from physical models. IBM’s are used to simulate 100’s-1000’s of individual organisms of a single species in order to more accurately understand the population dynamics of that species as it responds to climate variability.
Figure 1. Example of the response of a copepod IBM to physical forcing during 1986. The histogram shows the various stages of the copepod as it wakes from overwintering and proceeds through two generations in the spring and summer, then returns to dormancy in the fall.
How Does this Program Fit into the Broader Strategic Goals of NOAA Fisheries?
One of the specific strategic goals of NOAA is to enhance our ecosystem modeling capabilities, with the eventual goal of creating operational predictive forecasting models of fisheries species. Our work at ERD is helping to develop the next generation of ecosystem models, which can be incorporated into the larger whole-ocean modeling frameworks being developed elsewhere, such as at GFDL.
Another strategic goal of NOAA is to improve our understanding of climate change on marine ecosystems. ERD’s modeling program is specifically examining this; the effects of climate variability, and future climate change scenarios, on the population dynamics of key marine species. Thus this program should increase NOAA’s ability to plan and respond to climate change in the future.
Lastly, ERD’s modeling program also addresses NOAA’s strategic goal to improve its monitoring capabilities. As described above, modeling is an excellent way to fill in gaps in knowledge, and also to predict regions and times where biological activity may be particularly dynamic. As such, ERD’s modeling program can act as a feedback to monitoring programs by providing guidance in the temporal and spatial scales necessary to fully characterize variability of the marine system.