Long-term variability of the siphonophores Muggiaea atlantica and M. kochi in the Western English Channel

We investigated long-term variability of the calycophoran siphonophores Muggiaea atlantica and Muggiaea kochi in the Western English Channel (WEC) between 1930 and 2011. Our aims were to describe long-term changes in abundance and temporal distribution in relation to local environmental dynamics. In order to better understand mechanisms that regulate the species’ populations, we identified periods that were characteristic of in situ population growth and the environmental optima associated with these events. Our results show that between 1930 and the 1960s both M. atlantica and M. kochi were transient components of the WEC ecosystem. In the late 1960s M. atlantica, successfully established a resident population in the WEC, while the occurrence of M. kochi became increasingly sporadic. Once established as a resident species, the seasonal abundance and distribution of M. atlantica increased. Analysis of environmental conditions associated with in situ population growth revealed that temperature and prey were key determinants of the seasonal distribution and abundance of M. atlantica. Salinity was shown to have an indirect effect, likely representing a proxy for water circulation in the WEC. Anomalies in the seasonal cycle of salinity, indicating deviation from the usual circulation pattern in the WEC, were negatively associated with in situ growth, suggesting dispersal of the locally developing M. atlantica population. However, our findings identified complexity in the relationship between characteristics of the environment and M. atlantica variability. The transition from a period of transiency (1930–1968) to residency (1969–2011) was tentatively attributed to structural changes in the WEC ecosystem that occurred under the forcing of wider-scale hydroclimatic changes.

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.