Climate change impacts on small pelagic fish distribution in Northwest Africa: trends, shifts, and risk for food security.

Climate change is recognised to lead to spatial shifts in the distribution of small pelagic fish, likely by altering their environmental optima. Fish supply along the Northwest African coast is significant at both socio-economic and cultural levels. Evaluating the impacts of climatic change on small pelagic fish is a challenge and of serious concern in the context of shared stock management. Evaluating the impact of climate change on the distribution of small pelagic fish, a trend analysis was conducted using data from 2363 trawl samplings and 170,000 km of acoustics sea surveys. Strong warming is reported across the Southern Canary Current Large Marine Ecosystem (CCLME), extending from Morocco to Senegal. Over 34 years, several trends emerged, with the southern CCLME experiencing increases in both wind speed and upwelling intensity, particularly where the coastal upwelling was already the strongest. Despite upwelling-induced cooling mechanisms, sea surface temperature (SST) increased in most areas, indicating the complex interplay of climatic-related stressors in shaping the marine ecosystem. Concomitant northward shifts in the distribution of small pelagic species were attributed to long-term warming trends in SST and a decrease in marine productivity in the south. The abundance of Sardinella aurita, the most abundant species along the coast, has increased in the subtropics and fallen in the intertropical region. Spatial shifts in biomass were observed for other exploited small pelagic species, similar to those recorded for surface isotherms. An intensification in upwelling intensity within the northern and central regions of the system is documented without a change in marine primary productivity. In contrast, upwelling intensity is stable in the southern region, while there is a decline in primary productivity. These environmental differences affected several small pelagic species across national boundaries. This adds a new threat to these recently overexploited fish stocks, making sustainable management more difficult. Such changes must motivate common regional policy considerations for food security and sovereignty in all West African countries sharing the same stocks.

Machine and deep learning approaches to understand and predict habitat suitability for seabird breeding.

The way animals select their breeding habitat may have great impacts on individual fitness. This complex process depends on the integration of information on various environmental factors, over a wide range of spatiotemporal scales. For seabirds, breeding habitat selection integrates both land and sea features over several spatial scales. Seabirds explore these features prior to breeding, assessing habitats' quality. However, the information-gathering and decision-making process by seabirds when choosing a breeding habitat remains poorly understood. We compiled 49 historical records of larids colonies in Cuba from 1980 to 2020. Then, we predicted potentially suitable breeding sites for larids and assessed their breeding macrohabitat selection, using deep and machine learning algorithms respectively. Using a convolutional neural network and Landsat satellite images we predicted the suitability for nesting of non-monitored sites of this archipelago. Furthermore, we assessed the relative contribution of 18 land- and marine-based environmental covariates describing macrohabitats at three spatial scales (i.e. 10, 50 and 100 km) using random forests. Convolutional neural network exhibited good performance at training, validation and test (F1-scores >85%). Sites with higher habitat suitability (p > .75) covered 20.3% of the predicting area. Larids breeding macrohabitats were sites relatively close to main islands, featuring sparse vegetation cover and high chlorophyll-a concentration at sea in 50 and 100 km around colonies. Lower sea surface temperature at larger spatial scales was determinant to distinguish the breeding from non-breeding sites. A more comprehensive understanding of the seabird breeding macrohabitats selection can be reached from the complementary use of convolutional neural networks and random forest models. Our analysis provides crucial knowledge in tropical regions that lack complete and regular monitoring of seabirds' breeding sites.

ENSO Climate Forcing of the Marine Mercury Cycle in the Peruvian Upwelling Zone Does Not Affect Methylmercury Levels of Marine Avian Top Predators.

Climate change is expected to affect marine mercury (Hg) biogeochemistry and biomagnification. Recent modeling work suggested that ocean warming increases methylmercury (MeHg) levels in fish. Here, we studied the influence of El Niño Southern Oscillations (ENSO) on Hg concentrations and stable isotopes in time series of seabird blood from the Peruvian upwelling and oxygen minimum zone. Between 2009 and 2016, La Niña (2011) and El Niño conditions (2015-2016) were accompanied by sea surface temperature anomalies up to 3 °C, oxycline depth change (20-100 m), and strong primary production gradients. Seabird Hg levels were stable and did not co-vary significantly with oceanographic parameters, nor with anchovy biomass, the primary dietary source to seabirds (90%). In contrast, seabird Δ199Hg, proxy for marine photochemical MeHg breakdown, and δ15N showed strong interannual variability (up to 0.8 and 3‰, respectively) and sharply decreased during El Niño. We suggest that lower Δ199Hg during El Niño represents reduced MeHg photodegradation due to the deepening of the oxycline. This process was balanced by equally reduced Hg methylation due to reduced productivity, carbon export, and remineralization. The non-dependence of seabird MeHg levels on strong ENSO variability suggests that marine predator MeHg levels may not be as sensitive to climate change as is currently thought.

On the robustness of an eastern boundary upwelling ecosystem exposed to multiple stressors.

The resistance of an east border upwelling system was investigated using relative index of marine pelagic biomass estimates under a changing environment spanning 20-years in the strongly exploited southern Canary Current Large marine Ecosystem (sCCLME). We divided the sCCLME in two parts (north and south of Cap Blanc), based on oceanographic regimes. We delineated two size-based groups ("plankton" and "pelagic fish") corresponding to lower and higher trophic levels, respectively. Over the 20-year period, all spatial remote sensing environmental variables increased significantly, except in the area south of Cap Blanc where sea surface Chlorophyll-a concentrations declined and the upwelling favorable wind was stable. Relative index of marine pelagic abundance was higher in the south area compared to the north area of Cap Blanc. No significant latitudinal shift to the mass center was detected, regardless of trophic level. Relative pelagic abundance did not change, suggesting sCCLME pelagic organisms were able to adapt to changing environmental conditions. Despite strong annual variability and the presence of major stressors (overfishing, climate change), the marine pelagic ressources, mainly fish and plankton remained relatively stable over the two decades, advancing our understanding on the resistance of this east border upwelling system.

Seasonality in marine ecosystems: Peruvian seabirds, anchovy, and oceanographic conditions.

In fluctuating environments, matching breeding timing to periods of high resource availability is crucial for the fitness of many vertebrate species, and may have major consequences on population health. Yet, our understanding of the proximate environmental cues driving seasonal breeding is limited. This is particularly the case in marine ecosystems, where key environmental factors and prey abundance and availability are seldom quantified. The Northern Humboldt Current System (NHCS) is a highly productive, low-latitude ecosystem of moderate seasonality. In this ecosystem, three tropical seabird species (the Guanay Cormorant Phalacrocorax bougainvillii, the Peruvian Booby Sula variegata, and the Peruvian Pelican Pelecanus thagus) live in sympatry and prey almost exclusively on anchovy, Engraulis ringens. From January 2003 to December 2012, we monitored 31 breeding sites along the Peruvian coast to investigate the breeding cycle of these species. We tested for relationships between breeding timing, oceanographic conditions, and prey availability using occupancy models. We found that all three seabird species exhibited seasonal breeding patterns, with marked interspecific differences. Whereas breeding mainly started during the austral winter/early spring and ended in summer/early fall, this pattern was stronger in boobies and pelicans than in cormorants. Breeding onset mainly occurred when upwelling was intense but ecosystem productivity was below its annual maxima, and when anchovy were less available and in poor physiological condition. Conversely, the abundance and availability of anchovy improved during chick rearing and peaked around the time of fledging. These results suggest that breeding timing is adjusted so that fledging may occur under optimal environmental conditions, rather than being constrained by nutritional requirements during egg laying. Adjusting breeding time so that fledglings meet optimal conditions at independence is unique compared with other upwelling ecosystems and could be explained by the relatively high abundances of anchovy occurring throughout the year in the NHCS.

Spatio-Temporal Dynamics of Exploited Groundfish Species Assemblages Faced to Environmental and Fishing Forcings: Insights from the Mauritanian Exclusive Economic Zone.

Environmental changes and human activities can have strong impacts on biodiversity and ecosystem functioning. This study investigates how, from a quantitative point of view, simultaneously both environmental and anthropogenic factors affect species composition and abundance of exploited groundfish assemblages (i.e. target and non-target species) at large spatio-temporal scales. We aim to investigate (1) the spatial and annual stability of groundfish assemblages, (2) relationships between these assemblages and structuring factors in order to better explain the dynamic of the assemblages' structure. The Mauritanian Exclusive Economic Zone (MEEZ) is of particular interest as it embeds a productive ecosystem due to upwelling, producing abundant and diverse resources which constitute an attractive socio-economic development. We applied the multi-variate and multi-table STATICO method on a data set consisting of 854 hauls collected during 14-years (1997-2010) from scientific trawl surveys (species abundance), logbooks of industrial fishery (fishing effort), sea surface temperature and chlorophyll a concentration as environmental variables. Our results showed that abiotic factors drove four main persistent fish assemblages. Overall, chlorophyll a concentration and sea surface temperature mainly influenced the structure of assemblages of coastal soft bottoms and those of the offshore near rocky bottoms where upwellings held. While highest levels of fishing effort were located in the northern permanent upwelling zone, effects of this variable on species composition and abundances of assemblages were relatively low, even if not negligible in some years and areas. The temporal trajectories between environmental and fishing conditions and assemblages did not match for all the entire time series analyzed in the MEEZ, but interestingly for some specific years and areas. The quantitative approach used in this work may provide to stakeholders, scientists and fishers a useful assessment for the spatio-temporal dynamics of exploited assemblages under stable or changing conditions in fishing and environment.

Co-Occurrence and Habitat Use of Fin Whales, Striped Dolphins and Atlantic Bluefin Tuna in the Northwestern Mediterranean Sea.

Different dolphin and tuna species have frequently been reported to aggregate in areas of high frontal activity, sometimes developing close multi-species associations to increase feeding success. Aerial surveys are a common tool to monitor the density and abundance of marine mammals, and have recently become a focus in the search for methods to provide fisheries-independent abundance indicators for tuna stock assessment. In this study, we present first density estimates corrected for availability bias of fin whales (Balaenoptera physalus) and striped dolphins (Stenella coeruleoalba) from the Golf of Lions (GoL), compared with uncorrected estimates of Atlantic bluefin tuna (ABFT; Thunnus thynnus) densities from 8 years of line transect aerial surveys. The raw sighting data were further used to analyze patterns of spatial co-occurrence and density of these three top marine predators in this important feeding ground in the Northwestern Mediterranean Sea. These patterns were investigated regarding known species-specific feeding preferences and environmental characteristics (i. e. mesoscale activity) of the survey zone. ABFT was by far the most abundant species during the surveys in terms of schools and individuals, followed by striped dolphins and fin whales. However, when accounted for availability bias, schools of dolphins and fin whales were of equal density. Direct interactions of the species appeared to be the exception, but results indicate that densities, presence and core sighting locations of striped dolphins and ABFT were correlated. Core sighting areas of these species were located close to an area of high mesoscale activity (oceanic fronts and eddies). Fin whales did not show such a correlation. The results further highlight the feasibility to coordinate research efforts to explore the behaviour and abundance of the investigated species, as demanded by the Marine Strategy Framework Directive (MSFD).

Defining Mediterranean and Black Sea biogeochemical subprovinces and synthetic ocean indicators using mesoscale oceanographic features.

The Mediterranean and Black Seas are semi-enclosed basins characterized by high environmental variability and growing anthropogenic pressure. This has led to an increasing need for a bioregionalization of the oceanic environment at local and regional scales that can be used for managerial applications as a geographical reference. We aim to identify biogeochemical subprovinces within this domain, and develop synthetic indices of the key oceanographic dynamics of each subprovince to quantify baselines from which to assess variability and change. To do this, we compile a data set of 101 months (2002-2010) of a variety of both "classical" (i.e., sea surface temperature, surface chlorophyll-a, and bathymetry) and "mesoscale" (i.e., eddy kinetic energy, finite-size Lyapunov exponents, and surface frontal gradients) ocean features that we use to characterize the surface ocean variability. We employ a k-means clustering algorithm to objectively define biogeochemical subprovinces based on classical features, and, for the first time, on mesoscale features, and on a combination of both classical and mesoscale features. Principal components analysis is then performed on the oceanographic variables to define integrative indices to monitor the environmental changes within each resultant subprovince at monthly resolutions. Using both the classical and mesoscale features, we find five biogeochemical subprovinces for the Mediterranean and Black Seas. Interestingly, the use of mesoscale variables contributes highly in the delineation of the open ocean. The first axis of the principal component analysis is explained primarily by classical ocean features and the second axis is explained by mesoscale features. Biogeochemical subprovinces identified by the present study can be useful within the European management framework as an objective geographical framework of the Mediterranean and Black Seas, and the synthetic ocean indicators developed here can be used to monitor variability and long-term change.