Understanding trophic transference role in mercury biomagnification and bioaccumulation in the Atlantic spotted dolphin (Stenella frontalis)

Mercury is a metal of toxicological importance that occurs naturally. However, its concentration can be affected by anthropogenic activities and has the potential to bioaccumulate and biomagnify in food webs. Thus, knowing how its concentration varies along the trophic levels allows us to understand its potential risks to the biota. The present study aimed to investigate mercury transfer through the Stenella frontalis food web in Ilha Grande Bay (IGB), Rio de Janeiro state, Brazil. Samples of muscle and liver of S. frontalis were obtained from carcasses (n = 8) found stranded in the IGB, and its potential prey species were collected in fishing landings in the same Bay (n = 145). Total mercury (THg) concentrations were determined by atomic absorption spectrometry, and the δ15N was determined by an isotope ratio mass spectrometer. To investigate how trophic transfer affects mercury contamination in biota, six linear models were applied between THg logarithmic concentrations and δ15N or trophic position (TP). The trophic magnification factor (TMF) was calculated from each model to estimate the trophic transfer. Mean THg concentration in S. frontalis was higher in the liver than in muscle, but no correlation was found with age and δ15N values. Instead, the hepatic and muscular THg concentrations positively correlated with the trophic position. In the summer, THg concentration, TP, and δ15N values in prey species varied significantly, as well as in the winter, except for THg concentration. All trophic transfer models were significant in both seasons, and the TMF >1. The present study showed that trophic transfer is an essential factor in mercury biomagnification in both seasons but is not the unique driver. Both δ15N and TP could explain mercury trophic transfer, but TP better integrates metabolic diversity and seasonality.

β-diversity reveals ecological connectivity patterns underlying marine community recovery: Implications for conservation

As β-diversity can be seen as a proxy of ecological connections among species assemblages, modeling the decay of similarity in species composition at increasing distance may help elucidate spatial patterns of connectivity and local- to large-scale processes driving community assembly within a marine region. This, in turn, may provide invaluable information for setting ecologically coherent networks of marine protected areas (MPAs) in which protected communities are potentially interrelated and can mutually sustain against environmental perturbations. However, field studies investigating changes in β-diversity patterns at a range of spatial scales and in relation to disturbance are scant, limiting our understanding of how spatial ecological connections among marine communities may affect their recovery dynamics. We carried out a manipulative experiment simulating a strong physical disturbance on subtidal rocky reefs at several locations spanning >1000 km of coast in the Adriatic Sea (Mediterranean Sea) and compared β-diversity patterns and decay of similarity with distance and time by current transport between undisturbed and experimentally disturbed macrobenthic assemblages to shed light on connectivity processes and scales involved in recovery. In contrast to the expectation that very local-scale processes, such as vegetative regrowth and larval supply from neighboring undisturbed assemblages, might be the major determinants of recovery in disturbed patches, we found that connectivity mediated by currents at larger spatial scales strongly contributed to shape community reassembly after disturbance. Across our study sites in the Adriatic Sea, β-diversity patterns suggested that additional protected sites that matched hotspots of propagule exchange could increase the complementarity and strengthen the ecological connectivity throughout the MPA network. More generally, conditional to habitat distribution and selection of sites of high conservation priority (e.g., biodiversity hotspots), setting network internode distance within 100-150 km, along with sizing no-take zones to cover at least 5 km of coast, would help enhance the potential connectivity of Mediterranean subtidal rocky reef assemblages from local to large scale. These results can help improve conservation planning to achieve the goals of promoting ecological connectivity within MPA networks and enhancing their effectiveness in protecting marine communities against rapidly increasing natural and anthropogenic disturbances.

Taxonomic and functional responses of macrofaunal assemblage provide insight into ecological impacts of bottom-based Manila clam aquaculture

Understanding ecological impacts of bottom-based clam aquaculture can improve its management. In this study, taxonomic and functional macrofaunal assemblage were evaluated for two clam farms located in Laizhou Bay, China. Beta diversity and factors potentially regulating the dissimilarity of macrofauna were estimated. Both taxonomic and functional composition of macrofauna showed large differences between the clam farm and the control area. Functional dissimilarity within the clam farms was found to be nestedness and negatively correlated to local clam abundance. Additionally, the cultured clam enhanced the functional richness but made the macrofaunal assemblage more fragile against species or function loss. This effect would increase with clam abundance, which highlights the importance of identifying optimal clam culture intensity in developing a bottom-based clam aquaculture program.

Beta diversity differs among hydrothermal vent systems: Implications for conservation

Deep-sea hydrothermal vent habitats are small, rare and support unique species through chemosynthesis. As this vulnerable ecosystem is increasingly threatened by human activities, management approaches should address biodiversity conservation. Diversity distribution data provide a useful basis for management approaches as patterns of β-diversity (the change in diversity from site to site) can guide conservation decisions. Our question is whether such patterns are similar enough across vent systems to support a conservation strategy that can be deployed regardless of location. We compile macrofaunal species occurrence data for vent systems in three geological settings in the North Pacific: volcanic arc, back-arc and mid-ocean ridge. Recent discoveries in the Mariana region provide the opportunity to characterize diversity at many vent sites. We examine the extent to which diversity distribution patterns differ among the systems by comparing pairwise β-diversity, nestedness and their additive components. A null model approach that tests whether species compositions of each site pair are more or less similar than random provides insight into community assembly processes. We resolve several taxonomic uncertainties and find that the Mariana arc and back-arc share only 8% of species despite their proximity. Species overlap, species replacement and richness differences create different diversity distributions within the three vent systems; the arc system exhibits much greater β-diversity than both the back-arc and mid-ocean ridge systems which, instead, show greater nestedness. The influence of nestedness on β-diversity also increased from the arc to back-arc to ridge. Community assembly processes appear more deterministic in the arc and ridge systems while back-arc site pairs deviate little from the null expectation. These analyses reflect the need for a variety of management strategies that consider the character of diversity distribution to protect hydrothermal vents, especially in the context of mining hydrothermal deposits.

Generalized Linear Models outperform commonly used canonical analysis in estimating spatial structure of presence/absence data

Background

Ecological communities tend to be spatially structured due to environmental gradients and/or spatially contagious processes such as growth, dispersion and species interactions. Data transformation followed by usage of algorithms such as Redundancy Analysis (RDA) is a fairly common approach in studies searching for spatial structure in ecological communities, despite recent suggestions advocating the use of Generalized Linear Models (GLMs). Here, we compared the performance of GLMs and RDA in describing spatial structure in ecological community composition data. We simulated realistic presence/absence data typical of many β-diversity studies. For model selection we used standard methods commonly used in most studies involving RDA and GLMs.

Methods

We simulated communities with known spatial structure, based on three real spatial community presence/absence datasets (one terrestrial, one marine and one freshwater). We used spatial eigenvectors as explanatory variables. We varied the number of non-zero coefficients of the spatial variables, and the spatial scales with which these coefficients were associated and then compared the performance of GLMs and RDA frameworks to correctly retrieve the spatial patterns contained in the simulated communities. We used two different methods for model selection, Forward Selection (FW) for RDA and the Akaike Information Criterion (AIC) for GLMs. The performance of each method was assessed by scoring overall accuracy as the proportion of variables whose inclusion/exclusion status was correct, and by distinguishing which kind of error was observed for each method. We also assessed whether errors in variable selection could affect the interpretation of spatial structure.

Results

Overall GLM with AIC-based model selection (GLM/AIC) performed better than RDA/FW in selecting spatial explanatory variables, although under some simulations the methods performed similarly. In general, RDA/FW performed unpredictably, often retaining too many explanatory variables and selecting variables associated with incorrect spatial scales. The spatial scale of the pattern had a negligible effect on GLM/AIC performance but consistently affected RDA’s error rates under almost all scenarios.

Conclusion

We encourage the use of GLM/AIC for studies searching for spatial drivers of species presence/absence patterns, since this framework outperformed RDA/FW in situations most likely to be found in natural communities. It is likely that such recommendations might extend to other types of explanatory variables.

Drivers of beta diversity in modern and ancient reef-associated soft-bottom environments

Beta diversity, the compositional variation among communities, is often associated with environmental gradients. Other drivers of beta diversity include stochastic processes, priority effects, predation, or competitive exclusion. Temporal turnover may also explain differences in faunal composition between fossil assemblages. To assess the drivers of beta diversity in reef-associated soft-bottom environments, we investigate community patterns in a Middle to Late Triassic reef basin assemblage from the Cassian Formation in the Dolomites, Northern Italy, and compare results with a Recent reef basin assemblage from the Northern Bay of Safaga, Red Sea, Egypt. We evaluate beta diversity with regard to age, water depth, and spatial distance, and compare the results with a null model to evaluate the stochasticity of these differences. Using pairwise proportional dissimilarity, we find very high beta diversity for the Cassian Formation (0.91 ± 0.02) and slightly lower beta diversity for the Bay of Safaga (0.89 ± 0.04). Null models show that stochasticity only plays a minor role in determining faunal differences. Spatial distance is also irrelevant. Contrary to expectations, there is no tendency of beta diversity to decrease with water depth. Although water depth has frequently been found to be a key factor in determining beta diversity, we find that it is not the major driver in these reef-associated soft-bottom environments. We postulate that priority effects and the biotic structuring of the sediment may be key determinants of beta diversity.