Evidence for rangewide panmixia despite multiple barriers to dispersal in a marine mussel

Oceanographic features shape the distributional and genetic patterns of marine species by interrupting or promoting connections among populations. Although general patterns commonly arise, distributional ranges and genetic structure are species-specific and do not always comply with the expected trends. By applying a multimarker genetic approach combined with Lagrangian particle simulations (LPS) we tested the hypothesis that oceanographic features along northeastern Atlantic and Mediterranean shores influence dispersal potential and genetic structure of the intertidal mussel Perna perna. Additionally, by performing environmental niche modelling we assessed the potential and realized niche of P. perna along its entire native distributional range and the environmental factors that best explain its realized distribution. Perna perna showed evidence of panmixia across > 4,000 km despite several oceanographic breaking points detected by LPS. This is probably the result of a combination of life history traits, continuous habitat availability and stepping-stone dynamics. Moreover, the niche modelling framework depicted minimum sea surface temperatures (SST) as the major factor shaping P. perna distributional range limits along its native areas. Forthcoming warming SST is expected to further change these limits and allow the species to expand its range polewards though this may be accompanied by retreat from warmer areas.Fundacao para a Ciencia e Tecnologia (FCT-MEC, Portugal) [UID/Multi/04326/2013, IF/01413/2014/CP1217/CT0004]; South African Research Chairs Initiative (SARChI) of the Department of Science and Technology; National Research Foundation; South African National Research Foundation (NRF); Portuguese Fundacao para a Ciencia e Tecnologia (FCT) [SFRH/BPD/85040/2012, SFRH/BPD/111003/2015]info:eu-repo/semantics/publishedVersio

Monitoring marine phytoplankton seasonality from space

Remote sensing techniques are used to study the large scale patterns related to the seasonal modes of variability of the marine phytoplankton. Ten years of monthly composite maps of sea surface chlorophyll-a concentration and the PHYSAT database of four Phytoplanktonic Functional Types (PFTs), both from SeaWiFS, are used to investigate characteristics of phytoplankton seasonality in the trades and westerlies wind oceanic biomes, where data density is adequate. We use a combination of wavelet transform and statistical techniques that allow us to quantify both intensity and duration of the seasonal oscillation of chlorophyll-a concentration and PFTs relative occurrence, and to map these relationships. Next, the seasonal oscillations detected are related to four PFTs revealing six major global phytoplanktonic associations. Our results elucidate the intensity and duration of the seasonal dynamic of the chlorophyll-a concentration and of the relative occurrence of four PFTs at a global scale. Thus, the typology of the different types of seasonality is investigated. Finally, an overall agreement between the results and the biogeochemical provinces partition proposed by Longhurst is found, revealing a strong environmental control on the seasonal oscillation of primary producers and a clear latitudinal organization in the succession of the phytoplankton types. Results provided in this study quantify the seasonal oscillation of key structural parameters of the global ocean, and their potential implications for our understanding of ecosystem dynamics

Generalised model of primary production in the southern Benguela upwelling system

We provide a proof-of-concept demonstration using a novel method for estimating depth-integrated distributions of chlorophyll from archives of data from ships, buoys or gliders combined with remotely sensed data of sea surface temperature (SST) and surface chlorophyll a (chl a) from satellites. Our area of application has contrasting hydrographic regimes, which include the dynamic southern Benguela upwelling system and the stratified waters of the Agulhas Bank, South Africa. The method involves using self-organising maps (SOMs), a type of artificial neural network, to identify 'typical' chl a profiles regardless of their statistical form, provided several of a similar shape have been found in the training set. These are arranged in a linear array, ranging from uniform profiles low in chl a to profiles with high surface or subsurface peaks. We then use generalised modelling to relate these characteristic profiles to remotely sensed surface features, viz. surface chl a and SST, as well as area, season, and water depth (a proxy for distance offshore). The model accounts for 87% of the variability in chl a profile and is used to predict the type of profile likely for each pixel in monthly remote sensing composites of SST and surface chl a and then to estimate integrated chl a and primary production with the aid of a light model. Primary production peaks in mid-summer, reaching 5 mgC m(-2) d(-1) locally, with an average over the whole area and all seasons of 1.4 mg C m(-2) d(-1). Seasonal variation is greatest in the southern part of the west coast, and lowest in the stratified southeast. Annual primary production for the southern Benguela region including the Agulhas Bank is ca. 156 million tC yr(-1). This is the most robust estimate of primary production in the Benguela system to date because it combines the spatial and temporal coverage provided by remote sensing with realistic vertical chl a profiles

Multiscale event-based mining in geophysical time series : characterization and distribution of significant time-scales in the sea surface temperature anomalies relatively to ENSO periods from 1985 to 2009

In this paper, one-dimensional (1-D) geophysical time series are regarded as series of significant time-scale events. We combine a wavelet-based analysis with a Gaussian mixture model to extract characteristic time-scales of 486 144 detected events in the Sea Surface Temperature Anomaly (SSTA) observed from satellite at global scale from 1985 to 2009. We retrieve four low-frequency characteristic time-scales of Nino Southern Oscillation (ENSO) in the 1.5- to 7-year range and show their spatial distribution. High-frequency (HF) SSTA event spatial distribution shows a dependency to the ENSO regimes, pointing out that the ENSO signal also involves specific signatures at these time-scales. These fine-scale signatures can hardly be retrieved from global EOF approaches, which tend to exhibit uppermost the low-frequency influence of ENSO onto the SSTA. In particular, we observe at global scale a major increase by 11% of the number of SSTA HF events during Nino periods, with a local maximum of 80% in Europe. The methodology is also used to highlight an ENSO-induced frequency shift during the major 1997-2000 ENSO event in the intertropical Pacific. We observe a clear shift from the high frequencies toward the 3.36-year scale with a maximum shift occurring 2 months before the ENSO maximum of energy at 3.36-year scale

Density dependence, prey accessibility and prey depletion by fisheries drive Peruvian seabird population dynamics

In marine ecosystems top predator populations are shaped by environmental factors affecting their prey abundance. Coupling top predators' population studies with independent records of prey abundance suggests that prey fluctuations affect fecundity parameters and abundance of their predators. However, prey may be abundant but inaccessible to their predators and a major challenge is to determine the relative importance of prey accessibility in shaping seabird populations. In addition, disentangling the effects of prey abundance and accessibility from the effects of prey removal by fisheries, while accounting for density dependence, remains challenging for marine top predators. Here, we investigate how climate, population density, and the accessibility and removal of prey (the Peruvian anchovy Engraulis ringens) by fisheries influence the population dynamics of the largest sedentary seabird community (approximate to 4 million individuals belonging to guanay cormorant Phalacrocorax bougainvillii, Peruvian booby Sula variegata and Peruvian pelican Pelecanus thagus) of the northern Humboldt Current System over the past half-century. Using Gompertz state-space models we found strong evidence for density dependence in abundance for the three seabird species. After accounting for density dependence, sea surface temperature, prey accessibility (defined by the depth of the upper limit of the subsurface oxygen minimum zone) and prey removal by fisheries were retained as the best predictors of annual population size across species. These factors affected seabird abundance the current year and with year lags, suggesting effects on several demographic parameters including breeding propensity and adult survival. These findings highlight the effects of prey accessibility and fishery removals on seabird populations in marine ecosystems. This will help refine management objectives of marine ecosystems in order to ensure sufficient biomass of forage fish to avoid constraining seabird population dynamics, while taking into account of the effects of environmental variability