An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-abased models

We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll-a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed-layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite-derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low-productivity seasons as well as in sea ice-covered/deep-water regions. Depth-resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption-based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll-a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic-relevant parameters.

Spawning season and temperature relationships for sardine (Sardina pilchardus) in the eastern North Atlantic

Spawning temperature preferences for sardine (Sardina pilchardus) in the eastern North Atlantic were determined from field data. These were compared with climatological temperature cycles (1986-2002) derived from satellite data by geographical region, to predict spawning seasons. Optimum spawning temperatures were determined as 14.0-15.0oC from the English Channel to Portugal and 16.0–18.0oC for all north-west African regions. Spawning seasons were closely related to the general latitudinal trend of the annual temperature cycle, with modification by upwelling in the western Iberian and north-west African regions. Some differences between temperature-based spawning season predictions and field observations were related to variations in seasonal plankton production. Correlations in the annual time-series of favourable spawning temperatures suggested relatively strong linkages between the southern areas from Portugal to Senegal. There was no consistent relationship between annual variations in duration of temperature-predicted spawning seasons and observed field abundance of eggs.

Biophysical models of larval dispersal in the Benguela Current ecosystem

We synthesise and update results from the suite of biophysical, larval-dispersal models developed in the Benguela Current ecosystem. Biophysical models of larval dispersal use outputs of physical hydrodynamic models as inputs to individual-based models in which biological processes acting during the larval life are included. In the Benguela, such models were first applied to simulate the dispersal of anchovy Engraulis encrasicolus and sardine Sardinops sagax ichthyoplankton, and more recently of the early life stages of chokka-squid Loligo reynaudii and Cape hakes Merluccius spp. We identify how the models have helped advance understanding of key processes for these species. We then discuss which aspects of the early life of marine species in the Benguela Current ecosystem are still not well understood and could benefit from new modelling studies.

On the roles of cell size and trophic strategy in North Atlantic diatom and dinoflagellate communities

We have examined the inter- and intra-group seasonal succession of 113 diatom and dinoflagellate taxa, as surveyed by the Continuous Plankton Recorder (CPR) in the North Atlantic, by grouping taxa according to two key functional traits: cell size (mg C cell21) and trophic strategy (photoautotrophy, mixotrophy, or heterotrophy). Mixotrophic dinoflagellates follow photoautotrophic diatoms but precede their obligate heterotrophic counterparts in the succession because of the relative advantages afforded by photosynthesizing when light and nutrients are available in spring. The mean cell size of the sampled diatoms is smallest in the summer, likely because of the higher specific nutrient affinity of smaller relative to larger cells. Contrastingly, we hypothesize that mixotrophy diminishes the size selection based on nutrient limitation and accounts for the lack of a seasonal size shift among surveyed dinoflagellates. Relatively small, heterotrophic dinoflagellates (mg C cell21 , 1023) peak after other, larger dinoflagellates, in part because of the increased abundance of their small prey during nutrientdeplete summer months. The largest surveyed diatoms (mg C cell21 . 1022) bloom later than others, and we hypothesize that this may be because of their relatively slow maximum potential growth rates and high internal nutrient storage, as well as to the slower predation of these larger cells. The new trait database and analysis presented here helps translate the taxonomic information of the CPR survey into metrics that can be directly compared with trait-based models.

Future fish distributions constrained by depth in warming seas

European continental shelf seas have experienced intense warming over the past 30 years1. In the North Sea, fish have been comprehensively monitored throughout this period and resulting data provide a unique record of changes in distribution and abundance in response to climate change2, 3. We use these data to demonstrate the remarkable power of generalized additive models (GAMs), trained on data earlier in the time series, to reliably predict trends in distribution and abundance in later years. Then, challenging process-based models that predict substantial and ongoing poleward shifts of cold-water species4, 5, we find that GAMs coupled with climate projections predict future distributions of demersal (bottom-dwelling) fish species over the next 50 years will be strongly constrained by availability of habitat of suitable depth. This will lead to pronounced changes in community structure, species interactions and commercial fisheries, unless individual acclimation or population-level evolutionary adaptations enable fish to tolerate warmer conditions or move to previously uninhabitable locations.

Future fish distributions constrained by depth in warming seas

European continental shelf seas have experienced intense warming over the past 30 years1. In the North Sea, fish have been comprehensively monitored throughout this period and resulting data provide a unique record of changes in distribution and abundance in response to climate change2, 3. We use these data to demonstrate the remarkable power of generalized additive models (GAMs), trained on data earlier in the time series, to reliably predict trends in distribution and abundance in later years. Then, challenging process-based models that predict substantial and ongoing poleward shifts of cold-water species4, 5, we find that GAMs coupled with climate projections predict future distributions of demersal (bottom-dwelling) fish species over the next 50 years will be strongly constrained by availability of habitat of suitable depth. This will lead to pronounced changes in community structure, species interactions and commercial fisheries, unless individual acclimation or population-level evolutionary adaptations enable fish to tolerate warmer conditions or move to previously uninhabitable locations.

Parameterisation of bivalve functional traits for mechanistic eco-physiological dynamic energy budget (DEB) models

Mechanistic models such as those based on dynamic energy budget (DEB) theory are emergent ecomechanics tools to investigate the extent of fitness in organisms through changes in life history traits as explained by bioenergetic principles. The rapid growth in interest around this approach originates from the mechanistic characteristics of DEB, which are based on a number of rules dictating the use of mass and energy flow through organisms. One apparent bottleneck in DEB applications comes from the estimations of DEB parameters which are based on mathematical and statistical methods (covariation method). The parameterisation process begins with the knowledge of some functional traits of a target organism (e. g. embryo, sexual maturity and ultimate body size, feeding and assimilation rates, maintenance costs), identified from the literature or laboratory experiments. However, considering the prominent role of the mechanistic approach in ecology, the reduction of possible uncertainties is an important objective. We propose a revaluation of the laboratory procedures commonly used in ecological studies to estimate DEB parameters in marine bivalves. Our experimental organism was Brachidontes pharaonis. We supported our proposal with a validation exercise which compared life history traits as obtained by DEBs (implemented with parameters obtained using classical laboratory methods) with the actual set of species traits obtained in the field. Correspondence between the 2 approaches was very high (>95%) with respect to estimating both size and fitness. Our results demonstrate a good agreement between field data and model output for the effect of temperature and food density on age-size curve, maximum body size and total gamete production per life span. The mechanistic approach is a promising method of providing accurate predictions in a world that is under in creasing anthropogenic pressure.

Spatio-Temporal Variability of the North Sea Cod Recruitment in Relation to Temperature and Zooplankton

The North Sea cod (Gadus morhua, L.) stock has continuously declined over the past four decades linked with overfishing and climate change. Changes in stock structure due to overfishing have made the stock largely dependent on its recruitment success, which greatly relies on environmental conditions. Here we focus on the spatio-temporal variability of cod recruitment in an effort to detect changes during the critical early life stages. Using International Bottom Trawl Survey (IBTS) data from 1974 to 2011, a major spatio-temporal change in the distribution of cod recruits was identified in the late 1990s, characterized by a pronounced decrease in the central and southeastern North Sea stock. Other minor spatial changes were also recorded in the mid-1980s and early 1990s. We tested whether the observed changes in recruits distribution could be related with direct (i.e. temperature) and/or indirect (i.e. changes in the quantity and quality of zooplankton prey) effects of climate variability. The analyses were based on spatially-resolved time series, i.e. sea surface temperature (SST) from the Hadley Center and zooplankton records from the Continuous Plankton Recorder Survey. We showed that spring SST increase was the main driver for the most recent decrease in cod recruitment. The late 1990s were also characterized by relatively low total zooplankton biomass, particularly of energy-rich zooplankton such as the copepod Calanus finmarchicus, which have further contributed to the decline of North Sea cod recruitment. Long-term spatially-resolved observations were used to produce regional distribution models that could further be used to predict the abundance of North Sea cod recruits based on temperature and zooplankton food availability.