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Dispersal is generally difficult to directly observe. Instead, dispersal is often inferred from genetic markers and biophysical modelling where a correspondence indicates that dispersal routes and barriers explain a significant part of population genetic differentiation. Biophysical models are used for wind-driven dispersal in terrestrial environments and for propagules drifting with ocean currents in the sea. In the ocean, such seascape genetic or seascape genomic studies provide promising tools in applied sciences, as actions within management and conservation rely on an understanding of population structure, genetic diversity and presence of local adaptations, all dependent on dispersal within the metapopulation. Here, we surveyed 87 studies that combine population genetics and biophysical models of dispersal. Our aim was to understand if biophysical dispersal models can generally explain genetic differentiation. Our analysis shows that genetic differentiation and lack of genetic differentiation can often be explained by dispersal, but the realism of the biophysical model, as well as local geomorphology and species biology also play a role. The review supports the use of a combination of both methods, and we discuss our findings in terms of recommendations for future studies and pinpoint areas where further development is necessary, particularly on how to compare both approaches. This article is part of the theme issue 'Species' ranges in the face of changing environments (part I)'.

Biodiversity is proposed to be important for the rate of ecosystem functions. Most biodiversity—ecosystem function studies, however, consider only one response variable at a time, and even when multiple variables are examined they are analyzed separately. This means that a very important aspect of biodiversity is overlooked: the possibility for different species to carry out different functions at any one time. We propose a conceptual model to explore the effects of species loss on overall ecosystem functioning, where overall functioning is defined as the joint effect of many ecosystem functions. We show that, due to multifunctional complementarity among species, overall functioning is more susceptible to species loss than are single functions. Modeled relationships between species richness and overall ecosystem functioning using five empirical data sets on monocultures reflected the range of effects of species loss on multiple functions predicted by the model. Furthermore, an exploration of the correlations across functions and the degree of redundancy within functions revealed that multifunctional redundancy was generally lower than single-function redundancy in these empirical data sets. We suggest that by shifting the focus to the variety of functions maintained by a diversity of species, the full importance of biodiversity for the functioning of ecosystems can be uncovered. Our results are thus important for conservation and management of biota and ecosystem services.

The periwinkle Littorina saxatilis has repeatedly evolved both a small, fragile and globose \"wave ecotype\" confined to wave-swept shores and a large, robust and elongated \"crab ecotype\" found in nearby crab-rich but less-exposed shores. This phenotypic divergence is assumed to reflect, in some part, local adaptation to wave exposure, but this hypothesis has received incomplete experimental testing. Here, we report a test of the prediction that the wave ecotype has a higher capacity to resist water flow than the crab ecotype. We sampled snails along a crab-wave transect and measured their resistance to dislodgement in a high-speed water flume with water speeds that match those of breaking waves in a range of relevant field conditions. Snails from the wave environment were consistently more resistant to water flow than snails from the crab environment and high resistance was positively correlated with the surface area of the foot and the area of the outer aperture contour both relative to shell size, and to the extent of lateral shell compression. In a separate experiment, we found that snails raised in still water in a common garden showed higher resistance to water flow if originating from a wave environment than from a crab environment, and this was true both at juvenile (2 weeks) and adult (10 months) developmental stages. This result suggests genetic control of a distinct “wave adapted” phenotype, likely to be maintained under strong divergent selection between the two adjacent habitats.

The eelgrass Zostera marina is an important foundation species of coastal areas in the Northern Hemisphere, but is continuing to decline, despite management actions. The development of new management tools is therefore urgent in order to prioritize limited resources for protecting meadows most vulnerable to local extinctions and identifying most valuable present and historic meadows to protect and restore, respectively. We assessed 377 eelgrass meadows along the complex coastlines of two fjord regions on the Swedish west coast—one is currently healthy and the other is substantially degraded. Shoot dispersal for all meadows was assessed with Lagrangian biophysical modeling (scale: 100–1,000 m) and used for barrier analysis and clustering; a subset (n = 22) was also assessed with population genetic methods (20 microsatellites) including diversity, structure, and network connectivity. Both approaches were in very good agreement, resulting in seven subpopulation groupings or management units (MUs). The MUs correspond to a spatial scale appropriate for coastal management of “waterbodies” used in the European Water Framework Directive. Adding demographic modeling based on the genetic and biophysical data as a third approach, we are able to assess past, present, and future metapopulation dynamics to identify especially vulnerable and valuable meadows. In a further application, we show how the biophysical approach, using eigenvalue perturbation theory (EPT) and distribution records from the 1980s, can be used to identify lost meadows where restoration would best benefit the present metapopulation. The combination of methods, presented here as a toolbox, allows the assessment of different temporal and spatial scales at the same time, as well as ranking of specific meadows according to key genetic, demographic and ecological metrics. It could be applied to any species or region, and we exemplify its versatility as a management guide for eelgrass along the Swedish west coast.

Understanding the genetic structure of populations is key to revealing past and present demographic and evolutionary processes in a species. In the past decade high genetic differentiation has been observed in many microbial species challenging the previous view of cosmopolitan distribution. Populations have displayed high genetic differentiation, even at small spatial scales, despite apparent high dispersal. Numerous species of microalgae have a life-history strategy that includes a long-term resting stage, which can accumulate in sediments and serve as refuge during adverse conditions. It is presently unclear how these seed banks affect the genetic structure of populations in aquatic environments. Here we provide a conceptual framework, using a simple model, to show that long-term resting stages have an anchoring effect on populations leading to increased genetic diversity and population differentiation in the presence of gene flow. The outcome that species with resting stages have a higher degree of genetic differentiation compared to species without, is supported by empirical data obtained from a systematic literature review. With this work we propose that seed banks in aquatic microalgae play an important role in the contradicting patterns of gene flow, and ultimately the adaptive potential and population dynamics in species with long-term resting stages.

Barnacles are sessile macro-invertebrates, found along rocky shores in coastal areas worldwide. The euryhaline bay barnacle Balanus improvisus (Darwin, 1854) (= Amphibalanus improvisus) can tolerate a wide range of salinities, but the molecular mechanisms underlying the osmoregulatory capacity of this truly brackish species are not well understood. Aquaporins are pore-forming integral membrane proteins that facilitate transport of water, small solutes and ions through cellular membranes, and that have been shown to be important for osmoregulation in many organisms. The knowledge of the function of aquaporins in crustaceans is, however, limited and nothing is known about them in barnacles. We here present the repertoire of aquaporins from a thecostracan crustacean, the barnacle B. improvisus, based on genome and transcriptome sequencing. Our analyses reveal that B. improvisus contains eight genes for aquaporins. Phylogenetic analysis showed that they represented members of the classical water aquaporins (Aqp1, Aqp2), the aquaglyceroporins (Glp1, Glp2), the unorthodox aquaporin (Aqp12) and the arthropod-specific big brain aquaporin (Bib). Interestingly, we also found two big brain-like proteins (BibL1 and BibL2) constituting a new group of aquaporins not yet described in arthropods. In addition, we found that the two water-specific aquaporins were expressed as C-terminal splice variants. Heterologous expression of some of the aquaporins followed by functional characterization showed that Aqp1 transported water and Glp2 water and glycerol, agreeing with the predictions of substrate specificity based on 3D modeling and phylogeny. To investigate a possible role for the B. improvisus aquaporins in osmoregulation, mRNA expression changes in adult barnacles were analysed after long-term acclimation to different salinities. The most pronounced expression difference was seen for AQP1 with a substantial (>100-fold) decrease in the mantle tissue in low salinity (3 PSU) compared to high salinity (33 PSU). Our study provides a base for future mechanistic studies on the role of aquaporins in osmoregulation.

Water flow affects settlement of marine larvae on several scales. At the smallest scale local flow regime may control the probability of adhesion to the substrate. Our aim was to mechanistically understand the transition from suspended to attached larvae in turbulent flow. Recently it was proposed that opportunities for larval settlement in turbulent boundary layers depend on time windows with suitable instantaneous flow properties. In flume flow we characterized the proportion of suitable time windows in a series of flow velocities with focus on the near-bed flow. The change in the proportion of potential settling windows with increasing free-stream velocities was compared to the proportion of temporary attachment of barnacle cypris larvae at different flow velocities. We found large instantaneous flow variations in the near-bed flow where cyprid attachment took place. The probability of temporary attachment in cyprids declined with local flow speed and this response was compatible with a settling window lasting at least 0.1 s with a maximum local flow speed of 1.9-2.4 cm s-1. Cyprids swam against the near-bed flow (negative rheotaxis) and the swimming speed (1.8 cm s-1) was close to the critical speed that permitted temporary attachment. We conclude that temporary attachment in barnacle cyprids requires upstream swimming to maintain a fixed position relative to the substrate for at least 0.1 s. This behaviour may explain the ability of barnacles to recruit to high-flow environments and give cyprids flexibility in the pre-settlement choice of substrates based on flow regime.

Many planktonic microalgae produce a range of toxins and may form harmful algal blooms. One hypothesis is that some toxins are allelopathic, suppressing the growth of competitors, and it has been suggested that allelopathy may be one important mechanism causing algal blooms. In a metaanalysis of recent experimental work, we looked for evidence that allelopathy may explain the initiation of algal blooms. With few exceptions, allelopathic effects were only significant at very high cell densities typical of blooms. We conclude that there is no experimental support for allelopathy at prebloom densities, throwing doubts on allelopathy as a mechanism in bloom formation. Most studies tested allelopathy using cell-free manipulations. With simple models we show that cell-free manipulations may underestimate allelopathy at low cell densities if effects are transmitted during cell-cell interactions. However, we suggest that the evolution of allelopathy under field conditions may be unlikely even if based on cell-cell interactions. The spatial dispersion of cells in turbulent flow will make it difficult for an allelopathic cell to receive an exclusive benefit, and a dispersion model shows that dividing cells are rapidly separated constraining clone selection. Instead, we propose that reported allelopathic effects may be nonadaptive side effects of predator-prey or casual parasitic cell-cell interactions.

Time series from Landsat and Sentinel-2 satellites have great potential for modeling vegetation seasonality. However, irregular time sampling and frequent data loss due to clouds, snow, and short growing seasons, makes this modeling a challenge. We describe a new method for modeling seasonal vegetation index dynamics from satellite time series data. The method is based on box constrained separable least squares fits to logistic model functions combined with seasonal shape priors. To enable robust estimates, we extract a base level (i.e., the minimum dormant season value) from the frequency distribution of clear-sky vegetation index values. A seasonal shape prior is computed from several years of data, and in the final fits local parameters are box constrained. More specifically, if enough data values exist in a certain time period, the corresponding local parameters determining the shape of the model function over this period are relaxed and allowed to vary freely. If there are no observations in a period, the corresponding local parameters are locked to the parameters of the shape prior. The method is flexible enough to model interannual variations, yet robust enough when data are sparse. We test the method with Landsat, Sentinel-2, and MODIS data over a forested site in Sweden, demonstrating the feasibility and potential of the method for operational modeling of growing seasons.

The intermediate disturbance hypothesis (IDH) and the dynamic equilibrium model (DEM) are influential theories in ecology. The IDH predicts large species numbers at intermediate levels of disturbance and the DEM predicts that the effect of disturbance depends on the level of productivity. However, various indices of diversity are considered more commonly than the predicted number of species in tests of the hypotheses. This issue reaches beyond the scientific community as the predictions of the IDH and the DEM are used in the management of national parks and reserves. In order to compare responses with disturbance among measures of biodiversity, we used two different approaches of mathematical modelling and conducted an extensive meta-analysis. Two-thirds of the surveyed studies present different results for different diversity measures. Accordingly, the meta-analysis showed a narrow range of negative quadratic regression components for richness, but not evenness. Also, the two models support the IDH and the DEM, respectively, when biodiversity is measured as species richness, but predict evenness to increase with increasing disturbance, for all levels of productivity. Consequently, studies that use compound indices of diversity should present logical arguments, a priori, to why a specific index of diversity should peak in response to disturbance.