Inferring connectivity range in submerged aquatic populations (<i>Ruppia</i> L.) along European coastal lagoons from genetic imprint and simulated dispersal trajectories

Coastal salt- and brackish water lagoons are unique shallow habitats characterized by beds of submerged seagrasses and salt-tolerant Ruppia species. Established long-term and large-scale patterns of connectivity in lagoon systems can be strongly determined by patterns of nearshore and coastal currents next to local bird-mediated seed dispersal. Despite the importance of dispersal in landscape ecology, characterizing patterns of connectivity remains challenging in aquatic systems. Here, we aimed at inferring connectivity distances of Ruppia cirrhosa along European coastal lagoons using a population genetic imprint and modeled dispersal trajectories using an eddy-resolving numerical ocean model that includes tidal forcing. We investigated 1,303 individuals of 46 populations alongside subbasins of the Mediterranean (Balearic, Tyrrhenian, Ionian) and the Atlantic to Baltic Sea coastline over maximum distances of 563–2,684 km. Ten microsatellite loci under an autotetraploid condition revealed a mixed sexual and vegetative reproduction mode. A pairwise FST permutation test of populations revealed high levels of historical connectivity only for distance classes up to 104–280 km. Since full range analysis was not fully explanatory, we assessed connectivity in more detail at coastline and subbasin level using four approaches. Firstly, a regression over restricted geographical distances (300 km) was done though remained comparable to full range analysis. Secondly, piecewise linear regression analyses yielded much better explained variance but the obtained breakpoints were shifted toward greater geographical distances due to a flat slope of regression lines that most likely reflect genetic drift. Thirdly, classification and regression tree analyses revealed threshold values of 47–179 km. Finally, simulated ocean surface dispersal trajectories for propagules with floating periods of 1–4 weeks, were congruent with inferred distances, a spatial Bayesian admixed gene pool clustering and a barrier detection method. A kinship based spatial autocorrelation showed a contemporary within-lagoon connectivity up to 20 km. Our findings indicate that strong differentiation or admixtures shaped historical connectivity and that a pre- and post LGM genetic imprint of R. cirrhosa along the European coasts was maintained from their occurrence in primary habitats. Additionally, this study demonstrates the importance of unraveling thresholds of genetic breaks in combination with ocean dispersal modeling to infer patterns of connectivity

Caught in transit: offshore interception of seafaring propagules from seven mangrove species

Many organisms are transported passively and make use of the energy of natural phenomena or other organisms to disperse. However, not all species are equally likely to disperse over long distances. In mangroves, which possess seafaring propagules, it is largely unknown which species are more likely to reach the ocean and contribute to long‐distance dispersal. This is because dispersal has been mainly studied under reductionist laboratory conditions and via localized release–recapture experiments. Direct interceptions of propagules at sea have hardly been attempted because of the high labor intensity. Here, we set up a local citizen‐science network and engaged local fishermen to collect floating mangrove propagules over a period of 27&nbsp;months. By comparing the dispersing community of propagules from the local stands in which they were produced, the open water of the bay, and the open ocean beyond the coral reef barrier, we could study the transition between local and long‐distance dispersal. The composition of the dispersing community changed from the local stands toward the ocean, suggesting that this transition imposes an important selective filter for leaving the local system. With the exception of three rare species (Lumnitzera racemosa, Pemphis acidula, and Xylocarpus moluccensis), we intercepted dispersing propagules of every mangrove species occurring in the East African region. Most intercepted propagules were produced by Rhizophora mucronata and Ceriops tagal, followed by Bruguiera gymnorrhiza and Avicennia marina, which also represent the most abundant species in the nearby mangrove forest. A larger number of propagules were intercepted during the wet season, with fewer propagules recovered during the dry season. Overall, our study indicates that differences in the dispersal capacity of mangrove propagules are not straightforward and that some species may better disperse at local scales within an estuary or embayment, while others might be more suitable for dispersal over longer distances. The presence of such trade‐offs may help explain why current attempts to use mangrove traits to predict mangrove species distributions at different scales have remained only moderately successful

Floating with seeds: understanding hydrochorous mangrove propagule dispersal: a field and modeling approach

Présentation avec posterinfo:eu-repo/semantics/publishedYoung Marine Scientists’ Day Vlaams Instituut voor de Zee (VLIZ), 24 février, Brugge, Belgiqu

Island-wide coastal vulnerability assessment of Sri Lanka reveals that sand dunes, planted trees and natural vegetation may play a role as potential barriers against ocean surges

Since the Indian Ocean tsunami on 26 December 2004, there have been continuous efforts to upgrade the (tsunami) early warning systems as well as their accessibility in local and regional places in South and Southeast Asia. Meanwhile, the protection offered by coastal vegetation like mangroves to the people, property and physical landscape was also recognized and prioritized by both public and private authorities at various governance levels. As more than 90% of the Sri Lankan coastline is vulnerable to water-related impacts and existing bioshields like mangroves are potentially able to protect less than one-third of it, if at all they are in good condition, an attempt was made to build knowledge on the other potential natural barriers along the coast. In this context, a ca. 2 km belt of the entire coast was digitized, classified and assessed for vulnerability in relation to the existing land- use/cover. First, a visually interpreted land-use/cover map comprising 16 classes was developed using Google Earth imagery (Landsat-5, 2003). Second, based on the Global Digital Elevation Model data from the ASTER satellite, the land-use/cover map was further re-classified for elevation demarcation into waterless, run-up and flooded areas. And finally, both vulnerable and less vulnerable areas were identified by taking into account the average wave heights that the 2004 tsunami reached in the country (North: 5.5 m, South: 7 m, East: 5 m and West: 3.75 m). Among the selected areas studied, Jaffna and Kaluvanchikudy-Komari are found to be vulnerable and, Trincomalee, Yala and Puttalam are less vulnerable. While vulnerability was largely associated with the conditions devoid of natural barriers, the less vulnerable areas had mangroves, Casuarina, dense vegetation and/or sand dunes as land cover, all of which might prove effective against ocean surges. However, these land cover types should never be considered as providing full protection against the type of threats that can be expected. As the present study provides only baseline information on island-wide vulnerability of areas to water-related impacts, further investigation and validation along similar research lines are needed to establish a blueprint for future preparedness. (c) 2017 The Authors. Published by Elsevier B.V

The ECCO-Darwin Data-Assimilative Global Ocean Biogeochemistry Model: Estimates of Seasonal to Multidecadal Surface Ocean \u3cem\u3ep\u3c/em\u3eCO\u3csub\u3e2\u3c/sub\u3e and Air-Sea CO\u3csub\u3e2\u3c/sub\u3e Flux

Quantifying variability in the ocean carbon sink remains problematic due to sparse observations and spatiotemporal variability in surface ocean pCO2. To address this challenge, we have updated and improved ECCO-Darwin, a global ocean biogeochemistry model that assimilates both physical and biogeochemical observations. The model consists of an adjoint-based ocean circulation estimate from the Estimating the Circulation and Climate of the Ocean (ECCO) consortium and an ecosystem model developed by the Massachusetts Institute of Technology Darwin Project. In addition to the data-constrained ECCO physics, a Green\u27s function approach is used to optimize the biogeochemistry by adjusting initial conditions and six biogeochemical parameters. Over seasonal to multidecadal timescales (1995–2017), ECCO-Darwin exhibits broad-scale consistency with observed surface ocean pCO2 and air-sea CO2 flux reconstructions in most biomes, particularly in the subtropical and equatorial regions. The largest differences between CO2 uptake occur in subpolar seasonally stratified biomes, where ECCO-Darwin results in stronger winter uptake. Compared to the Global Carbon Project OBMs, ECCO-Darwin has a time-mean global ocean CO2 sink (2.47 ± 0.50 Pg C year−1) and interannual variability that are more consistent with interpolation-based products. Compared to interpolation-based methods, ECCO-Darwin is less sensitive to sparse and irregularly sampled observations. Thus, ECCO-Darwin provides a basis for identifying and predicting the consequences of natural and anthropogenic perturbations to the ocean carbon cycle, as well as the climate-related sensitivity of marine ecosystems. Our study further highlights the importance of physically consistent, property-conserving reconstructions, as are provided by ECCO, for ocean biogeochemistry studies

The ECCO‐Darwin Data‐Assimilative Global Ocean Biogeochemistry Model: Estimates of Seasonal to Multidecadal Surface Ocean pCO₂ and Air‐Sea CO₂ Flux

Quantifying variability in the ocean carbon sink remains problematic due to sparse observations and spatiotemporal variability in surface ocean pCO₂. To address this challenge, we have updated and improved ECCO‐Darwin, a global ocean biogeochemistry model that assimilates both physical and biogeochemical observations. The model consists of an adjoint‐based ocean circulation estimate from the Estimating the Circulation and Climate of the Ocean (ECCO) consortium and an ecosystem model developed by the Massachusetts Institute of Technology Darwin Project. In addition to the data‐constrained ECCO physics, a Green's function approach is used to optimize the biogeochemistry by adjusting initial conditions and six biogeochemical parameters. Over seasonal to multidecadal timescales (1995–2017), ECCO‐Darwin exhibits broad‐scale consistency with observed surface ocean pCO₂ and air‐sea CO₂ flux reconstructions in most biomes, particularly in the subtropical and equatorial regions. The largest differences between CO₂ uptake occur in subpolar seasonally stratified biomes, where ECCO‐Darwin results in stronger winter uptake. Compared to the Global Carbon Project OBMs, ECCO‐Darwin has a time‐mean global ocean CO₂ sink (2.47 ± 0.50 Pg C year⁻¹) and interannual variability that are more consistent with interpolation‐based products. Compared to interpolation‐based methods, ECCO‐Darwin is less sensitive to sparse and irregularly sampled observations. Thus, ECCO‐Darwin provides a basis for identifying and predicting the consequences of natural and anthropogenic perturbations to the ocean carbon cycle, as well as the climate‐related sensitivity of marine ecosystems. Our study further highlights the importance of physically consistent, property‐conserving reconstructions, as are provided by ECCO, for ocean biogeochemistry studies

Machiavelli\u27s Long-term Perspective : Purposes of the New Prince in Principe

はじめに　一　革新状況の政治学　二　徳の勧めと悪徳の戒め　三　長期的視座からの政策提言　おわり