Mixing apples and oranges: Assessing ecological status and its confidence from multiple and diverse indicators.

Ecosystem responses to increasing human pressures are complex and diverse, affecting organisms across all trophic levels. This has prompted the development of methods that integrate information across many indicators for environmental management. Legislative frameworks such as the European Water Framework Directive (WFD), specifically prescribe that integrated assessme nt (IA) of ecological status must consider indicators representing various biological and supporting quality elements. We present a general approach for an IA system based on a piece-wise linear transformation of indicator distributions to a standardized scale, allowing for integrating information from multiple and diverse indicators through a policy-dependent aggregation scheme. Uncertainties associated with monitoring data used for calculating indicators and their propagation throughout the integration scheme allow for confidence assessment at all levels of the hierarchical integration. Specific pressures leading to ecological impact can be identified through the most impaired indicators in the hierarchical and transparent aggregation scheme. The IA and its confidence are facilitated though the development of an online tool that accesses information from monitoring databases and presents the outcome at all levels of the assessment, ensuring consistency and transparency in the calculations for all potential stakeholders. We demonstrate the versality and applicability of the approach using indicators and aggregation principles from the Swedish national guidelines for assessing ecological status of rivers, lakes and coastal waters according to the WFD. Although the approach and the tool were developed specifically for the WFD ecological status assessment in Sweden, the generality of the approach implies that it can easily be adapted to the WFD assessment methods of other countries as well as other policies, where an integrated assessment is required.

Recent change in spatial distribution of the European flat oyster (Ostrea edulis) inferred from field data and empirical models of living oysters and empty shells.

Marine coastal areas are increasingly affected by human activities resulting in changes in species and habitat distributions. Understanding these patterns and its causes and consequences is important for conservation and restoration of such changing habitats. One habitat that has been heavily affected by human use are the North Sea oyster beds which once were abundant but have lost large parts of its coastal distribution due to overexploitation. Based on data of living and dead assemblages of Ostrea edulis collected using video transects, we used an ensemble modeling technique to model and predict current and recent distribution of O. edulis along the Swedish west coast where its distribution is, in relative terms, still rather unaffected. We could detect a recent change in the distribution of O. edulis along the coast which to a large extent could be attributed to a change in depth distribution, suggesting that the population of O. edulis have a slightly shallower distribution today than in the past. Although a potential mismatch between living and dead assemblages, caused by a complex combination of biological and environmental conditions, needs to be considered in the interpretations drawn, it may be a way around the lack of suitable background data in management decisions. This provides important information for management and conservation of the native oyster beds. Furthermore, this study illustrates a method for identifying recent changes in species distribution using dead assemblages of bivalves.

Identifying high-density areas of oysters using species distribution modeling: Lessons for conservation of the native Ostrea edulis and management of the invasive Magallana (Crassostrea) gigas in Sweden.

AIM: Understanding spatial patterns of the distribution of adult native oyster, Ostrea edulis, and the invasive Magallana (Crassostrea) gigas is important for management of these populations. The aim of this study was to use ensemble SDM's to (a) identify and predict conservation hotspots, (b) assess the current level of protection for O. edulis, and (c) quantify the amount of overlap between the two species where interactions with M. gigas are most likely. LOCATION: Skagerrak, Sweden. METHODS: We used data collected by video at depths from 0.5 to 10 m in 436 sites. Models of occurrence and densities >1 m-2 were fitted and assessed using ensemble methods ("biomod2" package). Models of high-density hotspots were used to predict, map, and quantify areal extent of the species in order to assess the degree of overlap with protected areas and the potential for interactions between the two species. RESULTS: Both species were widely distributed in the region. Observations of high-density habitats, mainly occurring at depths of ≈3 and 0.5 m for O. edulis and M. gigas, respectively, were found in 4% and 2% of the sites. Models provided useful predictions for both species (AUC = 0.85-0.99; sensitivity = 0.74-1.0; specificity = 0.72-0.97). High-density areas occupy roughly 15 km2 each with substantial overlap between species. 50% of these are protected only by fisheries regulations, 44% are found in Natura 2000 reserves and 6% of the predicted O. edulis enjoys protection in a national park. MAIN CONCLUSIONS: Data collection by video in combination with SDM's provides a realistic approach for large-scale quantification of spatial patterns of marine population and habitats. O. edulis and M. gigas are common in the area, but a large proportion of the most valuable O. edulis habitats are not found in protected areas. The overlap between species suggests that efforts to manage the invasive M. gigas need to be integrated with management actions to conserve the native O. edulis.

In situ characterization of benthic fluxes and denitrification efficiency in a newly re-established mussel farm.

Mussel farming has been proposed as a mechanism to mitigate eutrophication in coastal waters. However, localizing the intensive filtration of organic matter by mussels can cause a concomitant enrichment of organic matter in sediments below farms, which may influence biogeochemical processes and fates of nutrients in the system. In the context of mitigating eutrophication, it is important to quantify sedimentary changes induced at early life stages of mussel farms. Accordingly, this study investigated how a newly re-established mussel farm affected sedimentation rates, sediment characteristics, sediment-water solute fluxes and nitrate (NO3-) reduction rates (measured in situ) during the first year of production. Sedimentation rates were enhanced at the farm relative to a reference station, and both organic and inorganic carbon accumulated in the sediment with time. Increased organic matter input likely drove the slightly elevated sedimentary effluxes of ammonium (NH4+) and dissolved inorganic phosphorus (DIP) in the farm. Denitrification was the main NO3- reduction process, however, there was a relative increase in the remobilization of bioavailable nitrogen underneath the farm as dissimilatory nitrate reduction to ammonium (DNRA) rates were enhanced by >200% and the denitrification efficiency was 49% lower compared to the reference station. The sedimentary methane (CH4) release tended to be higher at the farm, but fluxes were not significantly different from reference conditions. Low sedimentary pigment concentrations indicated a reduced presence of benthic microalgae at the farm, which likely influenced sediment-water solute fluxes. Over the production cycle, the release of dissolved inorganic nitrogen (DIN) and DIP underneath the farm were respectively 426% and 510% relative to reference conditions. Impacts of the mussel farm were thus measurable already during the first year of establishment. These immediate changes to the sediment biogeochemistry, as well as long-term effects, should be considered when estimating the environmental impact of mussel aquaculture.

An open-source, citizen science and machine learning approach to analyse subsea movies.

BACKGROUND: The increasing access to autonomously-operated technologies offer vast opportunities to sample large volumes of biological data. However, these technologies also impose novel demands on ecologists who need to apply tools for data management and processing that are efficient, publicly available and easy to use. Such tools are starting to be developed for a wider community and here we present an approach to combine essential analytical functions for analysing large volumes of image data in marine ecological research. NEW INFORMATION: This paper describes the Koster Seafloor Observatory, an open-source approach to analysing large amounts of subsea movie data for marine ecological research. The approach incorporates three distinct modules to: manage and archive the subsea movies, involve citizen scientists to accurately classify the footage and, finally, train and test machine learning algorithms for detection of biological objects. This modular approach is based on open-source code and allows researchers to customise and further develop the presented functionalities to various types of data and questions related to analysis of marine imagery. We tested our approach for monitoring cold water corals in a Marine Protected Area in Sweden using videos from remotely-operated vehicles (ROVs). Our study resulted in a machine learning model with an adequate performance, which was entirely trained with classifications provided by citizen scientists. We illustrate the application of machine learning models for automated inventories and monitoring of cold water corals. Our approach shows how citizen science can be used to effectively extract occurrence and abundance data for key ecological species and habitats from underwater footage. We conclude that the combination of open-source tools, citizen science systems, machine learning and high performance computational resources are key to successfully analyse large amounts of underwater imagery in the future.

Developing benthic monitoring programmes to support precise and representative status assessments: a case study from the Baltic Sea.

Benthic habitats and communities are key components of the marine ecosystem. Securing their functioning is a central aim in marine environmental management, where monitoring data provide the base for assessing the state of marine ecosystems. In the Baltic Sea, a > 50-year-long tradition of zoobenthic monitoring exists. However, the monitoring programmes were designed prior to the current policies, primarily to detect long-term trends at basin-scale and are thus not optimal to fulfil recent requirements such as area-based periodic status assessments. Here, we review the current monitoring programmes and assess the precision and representativity of the monitoring data in status assessments to identify routes for improvement. At present, the monitoring is focused on soft-bottoms, not accounting for all habitat types occurring in the Baltic Sea. Evaluating the sources of variance in the assessment data revealed that the component accounting for variability among stations forms the largest proportion of the uncertainty. Furthermore, it is shown that the precision of the status estimates can be improved, with the current number of samples. Reducing sampling effort per station, but sampling more stations, is the best option to improve precision in status assessments. Furthermore, by allocating the sampling stations more evenly in the sub-basins, a better representativity of the area can be achieved. However, emphasis on securing the long-term data series is needed if changes to the monitoring programmes are planned.

Cleaning up seas using blue growth initiatives: Mussel farming for eutrophication control in the Baltic Sea.

Eutrophication is a serious threat to aquatic ecosystems globally with pronounced negative effects in the Baltic and other semi-enclosed estuaries and regional seas, where algal growth associated with excess nutrients causes widespread oxygen free "dead zones" and other threats to sustainability. Decades of policy initiatives to reduce external (land-based and atmospheric) nutrient loads have so far failed to control Baltic Sea eutrophication, which is compounded by significant internal release of legacy phosphorus (P) and biological nitrogen (N) fixation. Farming and harvesting of the native mussel species (Mytilus edulis/trossulus) is a promising internal measure for eutrophication control in the brackish Baltic Sea. Mussels from the more saline outer Baltic had higher N and P content than those from either the inner or central Baltic. Despite their relatively low nutrient content, harvesting farmed mussels from the central Baltic can be a cost-effective complement to land-based measures needed to reach eutrophication status targets and is an important contributor to circularity. Cost effectiveness of nutrient removal is more dependent on farm type than mussel nutrient content, suggesting the need for additional development of farm technology. Furthermore, current regulations are not sufficiently conducive to implementation of internal measures, and may constitute a bottleneck for reaching eutrophication status targets in the Baltic Sea and elsewhere.

Assessment of the population of Ostrea edulis in Sweden: A marginal population of significance?

The European flat oyster Ostrea edulis is an economically and ecologically important species subjected to extensive protection and restoration efforts, due to sharp population declines in Europe. In Sweden, O. edulis occurs at the northern fringe of its range. Knowledge of the distribution and abundance of the species is limited, and the size of the population has never been estimated. Oyster fishery sustainability has never been assessed.Using a random sampling approach and towed video, we collected data on oyster occurrence at 435 sites to estimate abundance and distribution of O. edulis in the Swedish Skagerrak region. Furthermore, the size of the population was assessed and the current management and legislation strategy of the species was analyzed.Living O. edulis was found in 27% of all sampled sites above 6 m, and the size of the population was estimated to 36.6 ± 16.3 million individuals (total population ± SE). The distribution was patchy, and approximately 60% of the population was found in oyster bed densities (≥5 oysters/m2), which corresponds to around 1% of the sampled sites.The nondestructive sampling method and representative design provided useful estimates of population size and error, which indicate that the marginal population of O. edulis in Sweden constitutes a significant part of the remaining European population. We argue that the relatively good status of the Swedish population can be explained by (a) private ownership of fishing rights, (b) a small-scale fishery that exploits <0.5% of the estimated population annually, conducted using nondestructive methods, and (c) parasite-free waters, potentially due to effective prevention of spread of infection. OPEN RESEARCH BADGES: This article has earned an Open Data Badge for making publicly available the digitally-shareable data necessary to reproduce the reported results. The data is available at https://osf.io/jgpxw/?view_only=d070b45802a4426da028efffde3d0f76.

Developing methods for assessing abundance and distribution of European oysters (Ostrea edulis) using towed video.

Due to large-scale habitat losses and increasing pressures, benthic habitats in general, and perhaps oyster beds in particular, are commonly in decline and severely threatened on regional and global scales. Appropriate and cost-efficient methods for mapping and monitoring of the distribution, abundance and quality of remaining oyster populations are fundamental for sustainable management and conservation of these habitats and their associated values. Towed video has emerged as a promising method for surveying benthic communities in a both non-destructive and cost-efficient way. Here we examine its use as a tool for quantification and monitoring of oyster populations by (i) analysing how well abundances can be estimated and how living Ostrea edulis individuals can be distinguished from dead ones, (ii) estimating the variability within and among observers as well as the spatial variability at a number of scales, and finally (iii) evaluating the precision of estimated abundances under different scenarios for monitoring. Overall, the results show that the can be used to quantify abundance and occurrence of Ostrea edulis in heterogeneous environments. There was a strong correlation between abundances determined in the field and abundances estimated by video-analyses (r2 = 0.93), even though video analyses underestimated the total abundance of living oysters by 20%. Additionally, the method was largely repeatable within and among observers and revealed no evident bias in identification of living and dead oysters. We also concluded that the spatial variability was an order of magnitude larger than that due to observer errors. Subsequent modelling of precision showed that the total area sampled was the main determinant of precision and provided general method for determining precision. This study provides a thorough validation of the application of towed video on quantitative estimations of live oysters. The results suggest that the method can indeed be very useful for this purpose and we therefor recommend it for future monitoring of oysters and other threatened habitats and species.

Approaches for integrated assessment of ecological and eutrophication status of surface waters in Nordic Countries.

We review approaches and tools currently used in Nordic countries (Denmark, Finland, Norway and Sweden) for integrated assessment of 'ecological status' sensu the EU Water Framework Directive as well as assessment of 'eutrophication status' in coastal and marine waters. Integration principles for combining indicators within biological quality elements (BQEs) and combining BQEs into a final-integrated assessment are discussed. Specific focus has been put on combining different types of information into indices, since several methods are currently employed. As a consequence of the variety of methods used, comparisons across both BQEs and water categories (river, lakes and coastal waters) can be difficult. Based on our analyses, we conclude that some principles and methods for integration can be critical and that a harmonised approach should be developed. Further, we conclude that the integration principles applied within BQEs are critical and in need of harmonisation if we want a better understanding of potential transition in ecological status between surface water types, e.g. when riverine water enters a downstream lake or coastal water body.

Modeling and predicting the growth of the mussel, Mytilus edulis: implications for planning of aquaculture and eutrophication mitigation.

The increased pressure on the marine ecosystems highlights the need for policies and integrated approaches for sustainable management of coastal areas. Spatial planning based on geographic information of human activities, ecological structures and functions, and their associated goods and services is a fundamental component in this context. Here, we evaluate the potential of predictive modeling to provide spatial data on one ecosystem function, mussel growth for use in such processes. We developed a methodology based on statistical modeling, spatial prediction, and mapping for the relative growth of the blue mussel, Mytilus edulis. We evaluated the performance of different modeling techniques and classification schemes using empirical measurements of growth from 144 sampling sites and data on biological, chemical, and physical predictors. Following comparisons of the different techniques and schemes, we developed random forest models to predict growth along the Swedish west coast. Implemented into GIS the best model produced in this study predicts that low, intermediate, and high growth rates can be expected in 53%, 32%, and 15% of modeled area, respectively. The results of this study also suggest that the nature and quality of predictor data hold the key to improving the predictive power of models. On a more general note, this study exemplifies a feasible approach based on measuring, modeling, and mapping for obtaining scientifically based spatial information on ecosystem functions and services affected by a complex set of factors. Such information is fundamental for maritime spatial planning and ecosystem-based management and its importance is likely to increase in the future. Because of its close link to nutrient assimilation and production yield, site-specific information of soft tissue growth such as the map of predicted growth rate developed in this study can be used as a tool for optimizing actions aimed at mitigating eutrophication and aquaculture operations and in maritime spatial planning processes of coastal areas.

Testing the potential for predictive modeling and mapping and extending its use as a tool for evaluating management scenarios and economic valuation in the Baltic Sea (PREHAB).

We evaluated performance of species distribution models for predictive mapping, and how models can be used to integrate human pressures into ecological and economic assessments. A selection of 77 biological variables (species, groups of species, and measures of biodiversity) across the Baltic Sea were modeled. Differences among methods, areas, predictor, and response variables were evaluated. Several methods successfully predicted abundance and occurrence of vegetation, invertebrates, fish, and functional aspects of biodiversity. Depth and substrate were among the most important predictors. Models incorporating water clarity were used to predict increasing cover of the brown alga bladderwrack Fucus vesiculosus and increasing reproduction area of perch Perca fluviatilis, but decreasing reproduction areas for pikeperch Sander lucioperca following successful implementation of the Baltic Sea Action Plan. Despite variability in estimated non-market benefits among countries, such changes were highly valued by citizens in the three Baltic countries investigated. We conclude that predictive models are powerful and useful tools for science-based management of the Baltic Sea.

Using vessel monitoring system data to improve systematic conservation planning of a multiple-use marine protected area, the Kosterhavet National Park (Sweden).

When spatial fishing data is fed into systematic conservation planning processes the cost to a fishery could be ensured to be minimal in the zoning of marine protected areas. We used vessel monitoring system (VMS) data to map the distribution of prawn trawling and calculate fishing intensity for 1-ha grid cells, in the Kosterhavet National Park (Sweden). We then used the software Marxan to generate cost-efficient reserve networks that represented every biotope in the Park. We asked what were the potential gains and losses in terms of fishing effort and species conservation of different planning scenarios. Given a conservation target of 10 % representation of each biotope, the fishery need not lose more than 20 % of its fishing grounds to give way to cost-efficient conservation of benthic diversity. No additional reserved area was needed to achieve conservation targets while minimizing fishing costs. We discuss the benefits of using VMS data for conservation planning.

Disturbance-diversity models: what do they really predict and how are they tested?

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.

Predicting the distribution of out-of-reach biotopes with decision trees in a Swedish marine protected area.

Through spatially explicit predictive models, knowledge of spatial patterns of biota can be generated for out-of-reach environments, where there is a paucity of survey data. This knowledge is invaluable for conservation decisions. We used distribution modeling to predict the occurrence of benthic biotopes, or megafaunal communities of the seabed, to support the spatial planning of a marine national park. Nine biotope classes were obtained prior to modeling from multivariate species data derived from point source, underwater imagery. Five map layers relating to depth and terrain were used as predictor variables. Biotope type was predicted on a pixel-by-pixel basis, where pixel size was 15 x 15 m and total modeled area was 455 km2. To choose a suitable modeling technique we compared the performance of five common models based on recursive partitioning: two types of classification and regression trees ([1] pruned by 10-fold cross-validation and [2] pruned by minimizing complexity), random forests, conditional inference (CI) trees, and CI forests. The selected model was a CI forest (an ensemble of CI trees), a machine-learning technique whose discriminatory power (class-by-class area under the curve [AUC] ranged from 0.75 to 0.86) and classification accuracy (72%) surpassed those of the other methods tested. Conditional inference trees are virtually new to the field of ecology. The final model's overall prediction error was 28%. Model predictions were also checked against a custom-built measure of dubiousness, calculated at the polygon level. Key factors other than the choice of modeling technique include: the use of a multinomial response, accounting for the heterogeneity of observations, and spatial autocorrelation. To illustrate how the model results can be implemented in spatial planning, representation of biodiversity in the national park was described and quantified. Given a goal of maximizing classification accuracy, we conclude that conditional inference trees are a promising tool to map biota. Species distribution modeling is presented as an ecological tool that can handle a wide variety of systems (e.g., the benthic system).

Physical and biological disturbances interact differently with productivity: effects on floral and faunal richness.

Physical and biological disturbances are ecological processes affecting patterns in biodiversity at a range of scales in a variety of terrestrial and aquatic systems. Theoretical and empirical evidence suggest that effects of disturbance on diversity differ qualitatively and quantitatively, depending on levels of productivity (e.g., the dynamic equilibrium model). In this study we contrasted the interactive effects between physical disturbance and productivity to those between biological disturbance and productivity. Furthermore, to evaluate how these effects varied among different components of marine hard-substratum assemblages, analyses were done separately on algal and invertebrate richness, as well as richness of the whole assemblage. Physical disturbance (wave action) was simulated at five distinct frequencies, while biological disturbance (grazing periwinkles) was manipulated as present or absent, and productivity was manipulated as high or ambient. Uni- and multivariate analyses both showed significant effects of physical disturbance and interactive effects between biological disturbance and productivity on the composition of assemblages and total species richness. Algal richness was significantly affected by productivity and biological disturbance, whereas invertebrate richness was affected by physical disturbance only. Thus, we show, for the first time, that biological disturbance and physical disturbance interact differently with productivity, because these two types of disturbances affect different components of assemblages. These patterns might be explained by differences in the distribution (i.e., press vs. pulse) and degree of selectivity between disturbances. Because different types of disturbance can affect different components of assemblages, general ecological models will benefit from using natural diverse communities, and studies concerned with particular subsets of assemblages may be misleading. In conclusion, this study shows that the outcome of experiments on effects of disturbance and productivity on diversity is greatly influenced by the composition of the assemblage under study, as well as on the type of disturbance that is used as an experimental treatment.

The red alga Bonnemaisonia asparagoides regulates epiphytic bacterial abundance and community composition by chemical defence.

Ecological research on algal-derived metabolites with antimicrobial activity has recently received increased attention and is no longer only aimed at identifying novel natural compounds with potential use in applied perspectives. Despite this progress, few studies have so far demonstrated ecologically relevant antimicrobial roles of algal metabolites, and even fewer have utilized molecular tools to investigate the effects of these metabolites on the natural community composition of bacteria. In this study, we investigated whether the red alga Bonnemaisonia asparagoides is chemically defended against bacterial colonization of its surface by extracting surface-associated secondary metabolites and testing their antibacterial effects. Furthermore, we compared the associated bacterial abundance and community composition between B. asparagoides and two coexisting macroalgae. Surface extracts tested at natural concentrations had broad-spectrum effects on the growth of ecologically relevant bacteria, and consistent with this antibacterial activity, natural populations of B. asparagoides had significantly lower densities of epibacteria compared with the coexisting algae. Terminal restriction fragment length polymorphism analysis further showed that B. asparagoides harboured surface-associated bacteria with a community composition that was significantly different from those on coexisting macroalgae. Altogether, these findings demonstrate that B. asparagoides produces surface-bound antibacterial compounds with a significant impact on the abundance and composition of the associated bacterial community.

Equal rates of disturbance cause different patterns of diversity.

Empirical evidence suggests that disturbance has profound effects on the species diversity of aquatic and terrestrial assemblages. Conceptual ecological theories, such as the intermediate disturbance hypothesis (IDH), predict maximum diversity at intermediate levels of disturbance. Tests of the predictive power and generality of these models are, however, hampered by the fact that the meaning and units of "disturbance" are not clearly defined. For example, it is seldom recognized that the rate of disturbance is the product of both frequency and extent (e.g., area or volume) of disturbance events. This has important consequences for the design and interpretation of experiments on disturbance. Here we present, for the first time, an experimental design that allows for unconfounded testing of combinations of area and frequency (i.e., regimes) for a given rate of disturbance. We tested the prediction that species richness responds differently to equal rates of disturbance, depending on the specific combination of frequency and area, on marine hard-substratum assemblages. Five different rates of disturbance and two regimes (small frequent or large infrequent disturbances) were applied at three sites. The results showed that the effect of a certain rate of disturbance (1) varies strongly among assemblages and (2) also depends on the specific combination of frequency and area of disturbance events. Maximum species richness was observed at intermediate rates of disturbance at site 1 (i.e., support for the IDH), whereas there was a monotonic decline at site 2 and there was no evident pattern at site 3. The variable responses among sites were explained by differences in degree of competitive exclusion and rates of recruitment. At the site where the IDH was supported, the regime with a large proportion of the area disturbed infrequently showed higher richness, compared to the regime with a small proportion disturbed frequently. This was likely due to a stronger decrease of dominants, which allowed for the recruitment of new colonizing species. In summary, we conclude that tests and general syntheses of models of disturbance-diversity patterns would benefit from more explicit definitions of the components of disturbance, as well as a stronger focus on the importance of variation in inherent properties of natural assemblages.

Male discrimination of female mucous trails permits assortative mating in a marine snail species.

Recent research has shown the potential for nonallopatric speciation, but we lack an adequate understanding of the mechanisms of prezygotic barriers and how these evolve in the presence of gene flow. The marine snail Littorina saxatilis has distinct ecotypes in different shore microhabitats. Ecotypes hybridize in contact zones, but gene flow is impeded by assortative mating. Earlier studies have shown that males and females of the same ecotype copulate for longer than mates of different ecotype. Here we report a new mechanism that further contributes to reproductive isolation between ecotypes in the presence of gene flow. This mechanism is linked to the ability of males to track potential partners by following their mucous trail. We show that cliff ecotype males follow the trails of females of the same ecotype for longer than females of the alternate (boulder) ecotype. In addition, cliff males are more likely to follow the mucous trail in the correct direction if the trail is laid by a cliff-female. The capacity to discriminate the ecotype of female mucous trails combined with differential copulation times creates a strong prezygotic reproductive barrier between ecotypes of L. saxatilis that reduces gene flow from cliff to boulder ecotypes by >/=80%.