Real-time sea surface air temperature retrieval over Southern Ocean using AMSR-E data

The AMSR-E satellite data and in-situ data were applied to retrieve sea surface air temperature (Ta) over the Southern Ocean. The in-situ data were obtained from the 24~(th) -26~(th) Chinese Antarctic Expeditions during 2008-2010. First, Ta was used to analyze the relativity with the bright temperature (Tb) from the twelve channels of AMSR-E, and no high relativity was found between Ta and Tb from any of the channels. The highest relativity was 0.38 (with 23.8 GHz). The dataset for the modeling was obtained by using in-situ data to match up with Tb, and two methods were applied to build the retrieval model. In multi-parameters regression method, the Tbs from 12 channels were used to the model and the region was divided into two parts according to the latitude of 50°S. The retrieval results were compared with the in-situ data. The Root Mean Square Error (RMS) and relativity of high latitude zone were 0.96℃and 0.93, respectively. And those of low latitude zone were 1.29 ℃ and 0.96, respectively. Artificial neural network (ANN) method was applied to retrieve Ta.The RMS and relativity were 1.26 ℃ and 0.98, respectively.

Comparing copepod time-series in the north of Spain: Spatial autocorrelation of community composition

Four time-series of copepod species biomass in the north of Spain were contrasted to demonstrate spatial autocorrelation of local communities and their responses to short-term local and regional variability in oceanographic conditions. The series represented coastal and oceanic environments along a marked gradient of influence of seasonal upwelling from Galicia to the Mar Cantábrico (S Bay of Biscay), and each one included at least 10 years of continuous data collected at monthly frequency. Community composition (i.e. species number and diversity) was very consistent through the region, but local variations in the presence of new species and the relative proportions of common species allowed for the characterisation of the response to the environment at each site. Small-sized species were more frequent near the coast. A few species, however, captured the main patterns of variability in all series. Calanus helgolandicus and Acartia (mainly Acartia clausi) were generally the main contributors to total biomass, while other species as Paracalanus parvus and Clausocalanus spp. were important only at some locations. Most copepod indices were positively correlated with upwelling, either considering the whole community (biomass, species richness and diversity) or individual species, but only in the coastal series analysed since 1991. Copepods in the nearby ocean, however, showed negative correlations with upwelling in the period 1960–1986. The effects of upwelling may have been modulated by local factors, as showed by the increases in biomass, number of species and diversity in associations with increases in sea surface temperature in Galicia, while in the Mar Cantábrico only the warming-tolerant species increased and those typical of upwelling decreased. Density stratification of the water column was associated with decreases in total copepod biomass in Galicia, while it favoured the increase in species richness in the Mar Cantábrico. Nearly all significant responses of copepods to environmental variability were delayed by up to 5 months, showing the importance of considering time-lags in the analysis of temporal responses of zooplankton.

Long-Term Retrospective Analysis of Mackerel Spawning in the North Sea: A New Time Series and Modeling Approach to CPR Data

We present a unique view of mackerel (Scomber scombrus) in the North Sea based on a new time series of larvae caught by the Continuous Plankton Recorder (CPR) survey from 1948-2005, covering the period both before and after the collapse of the North Sea stock. Hydrographic backtrack modelling suggested that the effect of advection is very limited between spawning and larvae capture in the CPR survey. Using a statistical technique not previously applied to CPR data, we then generated a larval index that accounts for both catchability as well as spatial and temporal autocorrelation. The resulting time series documents the significant decrease of spawning from before 1970 to recent depleted levels. Spatial distributions of the larvae, and thus the spawning area, showed a shift from early to recent decades, suggesting that the central North Sea is no longer as important as the areas further west and south. These results provide a consistent and unique perspective on the dynamics of mackerel in this region and can potentially resolve many of the unresolved questions about this stock

A comparison of two zooplankton time series data collected in the Gulf of Maine

Interannual and seasonal trends of zooplankton abundance and species composition were compared between the Bongo net and Continuous Plankton Recorder (CPR) time series in the Gulf of Maine. Data from 5799 Bongo and 3118 CPR samples were compared from the years 1978–2006. The two programs use different sampling methods, with the Bongo time series composed of bimonthly vertically integrated samples from locations throughout the region, while the CPR was towed monthly at 10 m depth on a transect that bisects the region. It was found that there was a significant correlation between the interannual (r = 0.67, P < 0.01) and seasonal (r = 0.95, P < 0.01) variability of total zooplankton counts. Abundance rankings of individual taxa were highly correlated and temporal trends of dominant copepods were similar between samplers. Multivariate analysis also showed that both time series equally detected major shifts in community structure through time. However, absolute abundance levels were higher in the Bongo and temporal patterns for many of the less abundant taxa groups were not similar between the two devices. The different mesh sizes of the samplers probably caused some of the discrepancies; but diel migration patterns, damage to soft bodied animals and avoidance of the small CPR aperture by some taxa likely contributed to the catch differences between the two devices. Nonetheless, Bongo data presented here confirm the previously published patterns found in the CPR data set, and both show that the abundance increase of the 1990s has been followed by average to below average levels from 2002 to 06.

Comparisons of zooplankton time series

Evidence for climate-correlated low frequency variability of various components of marine ecosystems has accumulated rapidly over the past 2 decades. There has also been a growing recognition that society needs to learn how the fluctuations of these various components are linked, and to predict the likely amplitude and steepness of future changes. Demographic characteristics of marine zooplankton make them especially suitable for examining variability of marine ecosystems at interannual to decadal time scales. Their life cycle duration is short enough that there is little carryover of population membership from year to year, but long enough that variability can be tracked with monthly-to-seasonal sampling. Because zooplankton are rarely fished, comparative analysis of changes in their abundance can greatly enhance our ability to evaluate the importance of and interaction between physical environment, food web, and fishery harvest as causal mechanisms driving ecosystem level changes. A number of valuable within-region analyses of zooplankton time series have been published in the past decade, covering a variety of modes of variability including changes in total biomass, changes in size structure and species composition, changes in spatial distribution, and changes in seasonal timing. But because most zooplankton time series are relatively short compared to the time scales of interest, the statistical power of local analyses is often low, and between-region and between-variable comparisons are also needed. In this paper, we review the results of recent within- and between-region analyses, and suggest some priorities for future work.

Interannual variability of marine zooplankton and their environments: Within- and between-region comparisons

The work highlights the first Global Comparison of Zooplankton Time Series. ► Variation of the peak in abundance is affected by annual temperature anomalies. ► Results show no global-scale synchrony in zooplankton time-series. ► There are spatial autocorrelations over substantial distances (1000–3000 km). ► There remains considerable uncertainty about the relative causes of shifts in distributions.

Region-wide changes in marine ecosystem dynamics: state-space models to distinguish trends from step changes

Regime shifts are sudden changes in ecosystem structure that can be detected across several ecosystem components. The concept that regime shifts are common in marine ecosystems has gained popularity in recent years. Many studies have searched for the step-like changes in ecosystem state expected under a simple interpretation of this idea. However, other kinds of change, such as pervasive trends, have often been ignored. We assembled over 300 ecological time series from seven UK marine regions, covering two to three decades. We developed state-space models for the first principal component of the time series in each region, a common measure of ecosystem state. Our models allowed both trends and step changes, possibly in combination. We found trends in three of seven regions and step changes in two of seven regions. Gradual and sudden changes are therefore important trajectories to consider in marine ecosystems.

Integrated Monitoring of Mola mola Behaviour in Space and Time

Over the last decade, ocean sunfish movements have been monitored worldwide using various satellite tracking methods. This study reports the near-real time monitoring of fine-scale (< 10 m) behaviour of sunfish. The study was conducted in southern Portugal in May 2014 and involved satellite tags and underwater and surface robotic vehicles to measure both the movements and the contextual environment of the fish. A total of four individuals were tracked using custom-made GPS satellite tags providing geolocation estimates of fine-scale resolution. These accurate positions further informed sunfish areas of restricted search (ARS), which were directly correlated to steep thermal frontal zones. Simultaneously, and for two different occasions, an Autonomous Underwater Vehicle (AUV) video-recorded the path of the tracked fish and detected buoyant particles in the water column. Importantly, the densities of these particles were also directly correlated to steep thermal gradients. Thus, both sunfish foraging behaviour (ARS) and possibly prey densities, were found to be influenced by analogous environmental conditions. In addition, the dynamic structure of the water transited by the tracked individuals was described by a Lagrangian modelling approach. The model informed the distribution of zooplankton in the region, both horizontally and in the water column, and the resultant simulated densities positively correlated with sunfish ARS behaviour estimator (rs = 0.184, p<0.001). The model also revealed that tracked fish opportunistically displace with respect to subsurface current flow. Thus, we show how physical forcing and current structure provide a rationale for a predator’s fine-scale behaviour observed over a two weeks in May 2014.

Integrated Monitoring of Mola mola Behaviour in Space and Time

Over the last decade, ocean sunfish movements have been monitored worldwide using various satellite tracking methods. This study reports the near-real time monitoring of fine-scale (< 10 m) behaviour of sunfish. The study was conducted in southern Portugal in May 2014 and involved satellite tags and underwater and surface robotic vehicles to measure both the movements and the contextual environment of the fish. A total of four individuals were tracked using custom-made GPS satellite tags providing geolocation estimates of fine-scale resolution. These accurate positions further informed sunfish areas of restricted search (ARS), which were directly correlated to steep thermal frontal zones. Simultaneously, and for two different occasions, an Autonomous Underwater Vehicle (AUV) video-recorded the path of the tracked fish and detected buoyant particles in the water column. Importantly, the densities of these particles were also directly correlated to steep thermal gradients. Thus, both sunfish foraging behaviour (ARS) and possibly prey densities, were found to be influenced by analogous environmental conditions. In addition, the dynamic structure of the water transited by the tracked individuals was described by a Lagrangian modelling approach. The model informed the distribution of zooplankton in the region, both horizontally and in the water column, and the resultant simulated densities positively correlated with sunfish ARS behaviour estimator (rs = 0.184, p<0.001). The model also revealed that tracked fish opportunistically displace with respect to subsurface current flow. Thus, we show how physical forcing and current structure provide a rationale for a predator’s fine-scale behaviour observed over a two weeks in May 2014.