• Energy Research

Historical exploitation of the Mediterranean Sea and the absence of rigorous baselines makes it difficult to evaluate the current health of the marine ecosystems and the efficacy of conservation actions at the ecosystem level. Here we establish the first current baseline and gradient of ecosystem structure of nearshore rocky reefs at the Mediterranean scale. We conducted underwater surveys in 14 marine protected areas and 18 open access sites across the Mediterranean, and across a 31-fold range of fish biomass (from 3.8 to 118 g m(-2)). Our data showed remarkable variation in the structure of rocky reef ecosystems. Multivariate analysis showed three alternative community states: (1) large fish biomass and reefs dominated by non-canopy algae, (2) lower fish biomass but abundant native algal canopies and suspension feeders, and (3) low fish biomass and extensive barrens, with areas covered by turf algae. Our results suggest that the healthiest shallow rocky reef ecosystems in the Mediterranean have both large fish and algal biomass. Protection level and primary production were the only variables significantly correlated to community biomass structure. Fish biomass was significantly larger in well-enforced no-take marine reserves, but there were no significant differences between multi-use marine protected areas (which allow some fishing) and open access areas at the regional scale. The gradients reported here represent a trajectory of degradation that can be used to assess the health of any similar habitat in the Mediterranean, and to evaluate the efficacy of marine protected areas.

AbstractCanopy-forming algae are declining globally due to multiple disturbances. This decline has recently been on the increase due to the spread of some tropical herbivorous fishes. This new phenomenon has drawn attention to the effects of fish herbivory in temperate areas, which have been assumed to be negligible compared to that of invertebrates, such as sea urchins. In this study, the impact of a Mediterranean native herbivorous fish (Sarpa salpa, salema) was assessed on the canopy-forming seaweed Cystoseira amentacea var. stricta. Cystoseira amentacea forms belts in the infralittoral fringe of wave-exposed shores, which has so far been considered a refuge from fish herbivory. To test the effects of salema feeding on natural C. amentacea belts, an innovative herbivore deterrent device was conceived. Salema had a significant effect on C. amentacea by decreasing algal size, biomass and fertility, by up to 97%. The results suggest that the contribution of salema feeding to the loss of Cystoseira forests in the Mediterranean may have been overlooked. In addition, the analysis of temporal and spatial patterns of salema landings in the Mediterranean Sea suggests that salema abundance may have increased recently. Thus, along with invertebrate herbivory and anthropogenic stressors, fish herbivory may also represent a potential threat to algal forests in temperate areas.

Ecological connectivity is important for effective marine planning and biodiversity conservation. Our aim was to identify factors important in influencing variation in benthic community structure on shallow rocky reefs in 2 regions of the Mediterranean Sea with contrasting oceanographic regimes. We assessed beta (β) diversity at 146 sites in the littoral and shallow sublittoral from the Adriatic/Ionian Seas (eastern region) and Ligurian/Tyrrhenian Seas (western region) using a null modelling approach to account for variation in species richness. The distance decay relationship between species turnover within each region and geographic distance by sea was determined using generalised linear models. Mantel tests were used to examine correlations between β diversity and connectivity by ocean currents, estimated from Lagrangian dispersal simulations. Variation in β diversity between sites was partitioned according to environmental and spatial components using a distance-based redundancy approach. Species turnover along a gradient of geographic distance was greater by a factor of 3 to 5 in the western region than the eastern region, suggesting lower connectivity between sites. β diversity was correlated with connectivity by ocean currents at both depths in the eastern region but not in the western region. The influence of spatial and environmental predictors of β diversity varied considerably between regions, but was similar between depths. Our results highlight the interaction of oceanographic, spatial and environmental processes influencing benthic marine β diversity. Persistent currents in the eastern region may be responsible for lower observed β diversity compared to the western region, where patterns of water circulation are more variable

AbstractThe effects of global change are particularly serious in areas where range shifts of species are physically constrained such as the Ligurian Sea, which is one of the coldest sectors of the Mediterranean. In this basin, historical information on water temperature (from the sea surface down to 75 m depth) dates back to the 1950s. Early studies also recorded warm‐water species occurrence. Thanks to these data we provide the first detailed characterization of water temperature variation from 1958 up to 2010 in the layer 0–75 m depth. We coupled this analysis with the available information on rocky reef epibenthic communities (literature review from 1955 to 1964 and field data from 1980 to 2010). The analysis of water temperature revealed several patterns of variation: a cooling phase from 1958 to 1980, a phase of rapid warming from 1980 to 1990 and a phase of slower warming from 1990 to 2010. Inter‐annual variation in temperature increased over the entire period for the water layer down to 20 m. Warm‐water native and alien species richness increased during the warming phases. Literature estimates suggest a decrease in warm‐water native species richness during the cooling phase. The analysis of quantitative data collected in the early 1990s and late 2000s indicated a decrease in the cover of warm‐water native species on shallow rocky reefs and an increase in deeper waters. We argue that increased inter‐annual variation in water temperature may disadvantage native warm‐water species in shallow waters. Our results indicate that the effect of temperature rises in cold, constrained basins may be more complex than the simple prediction of species changing their geographical range according to their thermal limits.

Les forêts macroalgales sont l'un des écosystèmes marins les plus productifs et les plus précieux, mais elles sont néanmoins fortement exposées à la fragmentation et à la perte. Les informations détaillées à grande échelle sur leur distribution font largement défaut, ce qui entrave les initiatives de conservation. Dans cette étude, un effort systématique pour combiner les données spatiales sur les canopées de Cystoseira C. Agardh (Fucales, Phaeophyta) a été réalisé pour développer un modèle d'aptitude à l'habitat (HSM) à l'échelle méditerranéenne, fournissant des outils essentiels pour améliorer la priorisation des sites pour leur gestion, leur restauration et leur protection. Une base de données géoréférencée sur la présence de 20 espèces de Cystoseira a été produite en recueillant toutes les informations disponibles dans la littérature publiée et grise, les portails de données Web et les données personnelles des co-auteurs. Les données ont été associées à 55 couches de variables prédictives au format matriciel (ASCII) et ont été utilisées afin de développer le HSM au moyen d'une forêt aléatoire, une technique d'apprentissage automatique très efficace. Les connaissances sur la répartition du couvert de Cystoseira étaient disponibles pour environ 14 % du littoral méditerranéen. Les données d'absence n'étaient disponibles que pour les 2% du bassin. Malgré ces lacunes, notre HSM a montré des niveaux de précision élevés dans la reproduction de la distribution de Cystoseira, de sorte que les premières cartes continues de l'habitat dans l'ensemble du bassin ont été produites. Des erreurs de classification se sont principalement produites dans les parties est et sud du bassin, où de grandes lacunes de connaissances ont émergé. Les facteurs les plus pertinents étaient les facteurs géomorphologiques, suivis des variables anthropiques représentatives de la pollution et de l'urbanisation. Notre modèle montre l'importance du partage des données pour combiner un grand nombre de données spatiales et environnementales, permettant d'individualiser les zones à forte probabilité d'occurrence de Cystoseira comme adaptées à sa présence. Cette approche encourage l'utilisation de cet outil de modélisation pour la prédiction de la distribution de Cystoseira et pour soutenir et planifier les initiatives de conservation et de gestion. L'étape suivante consiste à affiner les informations spatiales des données de présence-absence sur les auvents de Cystoseira et des prédicteurs environnementaux afin de traiter les évaluations spécifiques aux espèces. Los bosques de macroalgas son uno de los ecosistemas marinos más productivos y valiosos, pero están fuertemente expuestos a la fragmentación y la pérdida. En gran medida, se carece de información detallada a gran escala sobre su distribución, lo que dificulta las iniciativas de protección. En este estudio, se realizó un esfuerzo sistemático para combinar datos espaciales sobre las copas de Cystoseira C. Agardh (Fucales, Phaeophyta) para desarrollar un Modelo de Idoneidad del Hábitat (HSM) a escala mediterránea, proporcionando herramientas críticas para mejorar la priorización del sitio para su manejo, restauración y protección. Se produjo una base de datos georreferenciada sobre la ocurrencia de 20 especies de Cystoseira que recopila toda la información disponible de la literatura publicada y gris, los portales de datos web y los datos personales de los coautores. Los datos se asociaron a 55 capas variables predictoras en formato raster (ASCII) y se utilizaron para desarrollar el HSM mediante un Random Forest, una técnica de Machine Learning muy eficaz. El conocimiento sobre la distribución de las copas de Cystoseira estaba disponible para aproximadamente el 14% de la costa mediterránea. Los datos de ausencia estaban disponibles solo para el 2% de la cuenca. A pesar de estas lagunas, nuestro HSM mostró altos niveles de precisión en la reproducción de la distribución de Cystoseira, de modo que se produjeron los primeros mapas continuos del hábitat en toda la cuenca. Los errores de clasificación se produjeron principalmente en la parte oriental y meridional de la cuenca, donde surgieron grandes lagunas de conocimiento. Los impulsores más relevantes fueron los geomorfológicos, seguidos de las variables antropogénicas proxies de contaminación y urbanización. Nuestro modelo muestra la importancia de compartir datos para combinar una gran cantidad de datos espaciales y ambientales, lo que permite individualizar áreas con alta probabilidad de aparición de Cystoseira como adecuadas para su presencia. Este enfoque fomenta el uso de esta herramienta de modelado para la predicción de la distribución de Cystoseira y para apoyar y planificar iniciativas de protección y gestión. El paso adelante es refinar la información espacial de los datos de presencia-ausencia sobre las copas de Cystoseira y de los predictores ambientales para abordar las evaluaciones específicas de las especies. Macroalgal forests are one of the most productive and valuable marine ecosystems, but yet strongly exposed to fragmentation and loss. Detailed large-scale information on their distribution is largely lacking, hindering conservation initiatives. In this study, a systematic effort to combine spatial data on Cystoseira C. Agardh canopies (Fucales, Phaeophyta) was carried out to develop a Habitat Suitability Model (HSM) at Mediterranean scale, providing critical tools to improve site prioritization for their management, restoration and protection. A georeferenced database on the occurrence of 20 Cystoseira species was produced collecting all the available information from published and grey literature, web data portals and co-authors personal data. Data were associated to 55 predictor variable layers in the (ASCII) raster format and were used in order to develop the HSM by means of a Random Forest, a very effective Machine Learning technique. Knowledge about the distribution of Cystoseira canopies was available for about the 14% of the Mediterranean coastline. Absence data were available only for the 2% of the basin. Despite these gaps, our HSM showed high accuracy levels in reproducing Cystoseira distribution so that the first continuous maps of the habitat across the entire basin was produced. Misclassification errors mainly occurred in the eastern and southern part of the basin, where large gaps of knowledge emerged. The most relevant drivers were the geomorphological ones, followed by anthropogenic variables proxies of pollution and urbanization. Our model shows the importance of data sharing to combine a large number of spatial and environmental data, allowing to individuate areas with high probability of Cystoseira occurrence as suitable for its presence. This approach encourages the use of this modelling tool for the prediction of Cystoseira distribution and for supporting and planning conservation and management initiatives. The step forward is to refine the spatial information of presence-absence data about Cystoseira canopies and of environmental predictors in order to address species-specific assessments. تعد غابات الطحالب الكلية واحدة من أكثر النظم الإيكولوجية البحرية إنتاجية وقيمة، ولكنها معرضة بشدة للتجزئة والفقدان. هناك نقص كبير في المعلومات التفصيلية على نطاق واسع حول توزيعها، مما يعوق مبادرات الحفظ. في هذه الدراسة، تم بذل جهد منهجي لدمج البيانات المكانية على مظلات Cystoseira C. Agardh (Fucales، Phaeophyta) لتطوير نموذج ملاءمة الموائل (HSM) على نطاق البحر الأبيض المتوسط، مما يوفر أدوات حاسمة لتحسين تحديد أولويات الموقع لإدارتها وترميمها وحمايتها. تم إنتاج قاعدة بيانات مرجعية جغرافية حول حدوث 20 نوعًا من Cystoseira لجمع جميع المعلومات المتاحة من الأدبيات المنشورة والرمادية وبوابات بيانات الويب والبيانات الشخصية للمؤلفين المشاركين. ارتبطت البيانات بـ 55 طبقة متغيرة للتنبؤ بتنسيق (ASCII) Raster واستخدمت من أجل تطوير HSM عن طريق غابة عشوائية، وهي تقنية فعالة للغاية للتعلم الآلي. كانت المعرفة حول توزيع مظلات Cystoseira متاحة لحوالي 14 ٪ من ساحل البحر الأبيض المتوسط. كانت بيانات الغياب متاحة فقط لـ 2 ٪ من الحوض. على الرغم من هذه الفجوات، أظهرت وحدة الأمن البشري لدينا مستويات عالية من الدقة في إعادة إنتاج توزيع Cystoseira بحيث تم إنتاج أول خرائط مستمرة للموائل عبر الحوض بأكمله. حدثت أخطاء في التصنيف بشكل رئيسي في الجزء الشرقي والجنوبي من الحوض، حيث ظهرت فجوات كبيرة في المعرفة. كانت الدوافع الأكثر صلة هي العوامل الجيومورفولوجية، تليها المتغيرات البشرية للتلوث والتحضر. يوضح نموذجنا أهمية مشاركة البيانات للجمع بين عدد كبير من البيانات المكانية والبيئية، مما يسمح بتخصيص المناطق ذات الاحتمال الكبير لحدوث Cystoseira كمناسبة لوجودها. يشجع هذا النهج على استخدام أداة النمذجة هذه للتنبؤ بتوزيع Cystoseira ولدعم وتخطيط مبادرات الحفظ والإدارة. تتمثل الخطوة إلى الأمام في تحسين المعلومات المكانية لبيانات غياب الوجود حول مظلات Cystoseira والمتنبئات البيئية من أجل معالجة التقييمات الخاصة بالأنواع.