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Modeling Copepod Populations in the Gulf of Maine: Building Prediction Capability Through a Process-Oriented Approach

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Modeling Copepod Populations in the Gulf of Maine: Building Prediction Capability Through a Process-Oriented Approach ICES CM 2010/L:17 Modeling copepod populations in the Gulf of Maine: building prediction capability through a process-oriented approach Rubao Ji, Cabell S. Davis, Christoph Stegert Abstract Zooplankton are sensitive to climate change and may amplify subtle environmental signals due to their non-linear responses to environment forcing. It is critically important to understand the underlying biological-physical mechanisms that control the variability of zooplankton populations, such that the predictions on how the climate change might affect plankton and higher trophic levels become possible. In this study, we use a coupled hydrodynamics/food-web/population-dynamics model to identify the key processes controlling the observed seasonality and distributional patterns of key copepod populations in the Gulf of Maine region including Pseudocalanus spp., Centropages typicus, and Calanus finmarchicus. The importance of life-history traits (e.g. development, reproduction, mortality, diel and seasonal migration) vs. physical processes (e.g. advection and diffusion) are examined. The implication of this modeling study on data-need, observing system design, and climate change scenario testing will also be discussed. Keywords: plankton, copepods, modeling, biological-physical interaction, life-history traits Contact author: Rubao Ji, Biology Department, Woods Hole Oceanographic Institution, MS #33, Redfield 2-14, Woods Hole, MA 02543, USA. Email: [email protected] Introduction Copepods have the highest abundance among the meso-zooplankton in the northern Atlantic Ocean and play an important role in marine food webs (e.g. Davis, 1987; GLOBEC, 1992). Copepods are also sensitive to environmental changes and therefore can be considered as important climate indicators (e.g. Richardson, 2008). Increasing efforts have been made to build the prediction capability of coupled biological-physical models, so the influence of climate change on plankton phenology and biogeographic boundaries can be quantitatively assessed (Ji et al., 2010). Of the several copepod species found in the Gulf of Maine (GoM), the relatively large- sized Calanus finmarchicus and the smaller Centropages typicus and Pseudocalanus sp. (the congener P. newmani and P. moultoni) are among the most dominant species (Kane, 2007). All three copepods show abundance peaks at different times of the year, though the temperature and food (considering the bulk property as chlorophyll-a) conditions are the same to all species (Fig. 1). Further, the spatial distributions of these species differ from each other (see Ji et al., 2009), suggesting that their spatio-temporal distributional patterns are probably related to their unique life-history trait. It is therefore expected that the response of different copepod species to climate change is likely to be different. Figure 1: Climatological seasonal cycle of temperature, chlorophyll (satellite data, top panel) and three copepod populations (MARMAP data, lower panel) in the Gulf of Maine. With the predicted warming of the oceans the adaptation of species is challenged. Pseudocalanus is a good example for adaptation to a colder environment; its development time does not increase as much as warm water species such as Centropages typicus when they are exposed to cold temperature. Meanwhile, at a warmer temperature the development of C. typicus becomes faster than Pseudocalanus. The exponential decrease in the Temperature-Development relation also indicates that a change in temperature has a stronger impact in colder regions. For the GoM an increase of ca. 2- 4°C is predicted from IPCC simulations within this century (IPCC, 2007). This temperature change is likely to cause a shift in the species distribution as conditions become more favorable for C. typicus (Stegert et al., 2010). The fidelity of this type of empirical predication depends on how well we understand the importance of different aspects of life-history traits on population dynamics, which can be examined in a biological-physical coupled population model used in this study. In this paper, we are interested in understanding the spatio-temporal distribution of the three target species Calanus finmarchicus, Pseudocalanus sp. and Centropages typicus. We hypothesize that the observed different seasonality is due to different life-history strategies manifested as the interplay of physiological processes and food web interactions (Fig. 2), including their development (from eggs to adults), reproduction and their loss by mortality. These processes are affected by environmental conditions, which can usually be expressed as empirical regressions obtained from in situ or lab measurements (e.g. the Belehradek function for temperature dependent development rate). The key questions are: • Can we reproduce the observed spatial and temporal patterns if we use life-history parameter values from experiments for these processes (found in literatures) and use environmental conditions from a validated physical-biological model? • What aspects of life-history strategies are critical for the formation of the observed spatio-temporal patterns? Figure 2: Conceptual diagram of processes forming the distribution of copepods based on their specific life-history strategies and the environment. In the following we examine the controls of population growth by different life strategies for the above-mentioned three target species, covering the following topics: T1) Temperature-dependent development for cold- vs. warm- water species; T2) The role of predation and cannibalism; T3) The importance of bottom-up effect through food-dependent development and reproduction; T4) The impact of diel and seasonal migration on seasonality and distribution; and T5) The population persistence in an advective system. Methods We used a process-oriented approach for this biological-physical coupled modeling study. It involves a simple population dynamics model that simulates key life-history processes including: development (stage duration D) as a function of temperature (T), reproduction R as a function of temperature (T) and food (F), and mortality M as a function of temperature. R and M determine the population’s increase and decrease, respectively. A 0-D (no spatial dimension) version of the population model that consists of four development stages, eggs (E), nauplii (N), copepodites (C) and adults (A), with mean-age calculation to minimize numerical diffusion of stages, was developed by Hu et al. (2008). The details for the 3-D coupled model implementation of the mean-age population model can be found in Ji et al. (2009). The population model was embedded into the three-dimensional FVCOM model (Chen et al., 2003) and a Nitrogen-Phytoplankton-Zooplankton-Detritus (NPZD) module (Ji et al., 2008). We investigate the seasonal cycle and test the effect of different life-history strategies and their importance in shaping the species spatio-temporal distribution. The tests included several simulation runs (‘RunX-Y’) to address the mentioned topics [T1-5], (where the X-value indicates the species, 1: Pseudocalanus, 2: C. typicus and 3: C. finmarchicus and the Y-value indicates runs for each species): • Run*-0: baseline case [T1]: * means for all three species. • Run2-1: mortality test 2 [T2]: including a new Q10 value for temperature dependent mortality, for C. typicus. • Run2-2: mortality test 3 [T2]: include cannibalism, for C. typicus. • Run2-3: feeding test [T3,4]: adding microzooplankton as food source instead of phytoplankton only, for C. typicus. • Run2-4: migration test 1 [T5]: individuals migrate to the layer with maximum chlorophyll concentration, for C. typicus. • Run3-1: migration test 2 [T5]: include diapause behavior, individuals migrate to depth at certain temperature and food conditions, for C. finmarchicus. • Run3-2: advection test [T6]: adding an upstream influx from the Scotian Shelf, for C. finmarchicus. Pseudocalanus Centropages typicus Centropages Calanus finmarchicus Calanus Figure 3: Bi-monthly averaged distribution for May/June and Sept/Oct from observations (left) and baseline simulation Run*-0 (center) and simulated time-series at two positions (GB crest and central Jordan Basin) compared to observations (right). Results At the baseline case (Run*-0) for all three species, the population dynamics of Pseudocalanus are similar to the observed seasonal cycle (Fig. 4): Following the spring bloom the population increased until summer. The decrease was due to increased mortality (simulations with constant mortality did not show this decrease). In contrast, the simulated annual cycles of C. typicus and C. finmarchicus at baseline runs differ significantly from observations: modeled abundances of C. typicus peak in June similar to Pseudocalanus instead of fall, while the population of C. finmarchicus goes extinct. The question is which life-history traits of these two species are missing in the model in order to get the observed distributions? The decline of Pseudocalanus in summer is probably due to the combined factors of lower food concentration and increased mortality (correlated to temperature in the model). These factors seem not to work in C. typicus. For instance, lowering the temperature dependence for mortality (Run2-1, Q10 = 1.9) resulted in a shift of abundance peak from spring to fall, but the population on Georges Bank increases much more than observed, while the population in the deeper basins became significantly lower, resulting in a unrealistically strong spatial gradient from GB to the central GoM.
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