Substantial efforts have been devoted to developing and applying biomarkers for use in ecotoxicology. These efforts have resulted partly from a desire for early warning indicators that respond before measurable effects on individuals and populations occur and partly as an aid to identifying the causes of observed population- and community-level effects. Whereas older biomarkers focused on measures of organism physiology or biochemistry, advances in molecular biology are extending the biomarker philosophy to the level of the genes (i.e., ecotoxicogenomics). However, the extent to which biomarkers are able to provide unambiguous and ecologically relevant indicators of exposure to or effects of toxicants remains highly controversial. In the present paper, we briefly discuss the application of biomarkers in ecotoxicology and ecological risk assessment, and we provide examples of how they have been applied. We conclude that although biomarkers can be helpful for gaining insight regarding the mechanisms causing observed effects of chemicals on whole-organism performance and may, in some cases, provide useful indicators of exposure, individual biomarker responses should not be expected to provide useful predictions of relevant ecological effects--and probably not even predictions of whole-organism effects. Suites of biomarkers are only likely to provide increased predictability if they can be used in a comprehensive mechanistic model that integrates them into a measure of fitness. Until this can be achieved, biomarkers may be useful for hypothesis generation in carefully controlled experiments. However, because the aims of environmental monitoring and ecological risk assessment are to detect and/or predict adverse chemical impacts on populations, communities, and ecosystems, we should be focusing our efforts on improving methods to do this directly. This will involve developing and testing models of appropriate complexity that can describe real-world systems at multiple scales.
Semi-sessile Mytilus mussels are used as indicators of climate changes, but their geographic distribution is not sufficiently known in the Arctic. The aim of this study was to investigate the taxonomic status and genetic differentiation of Mytilus populations in a Northwest Greenlandic fjord at Maarmorilik, impacted by contaminations from a former mine. In this study, mussels were collected at three sites differing in exposure to environmental factors. A total of 54 polymorphic SNPs found in the Mytilus EST and DNA sequences analyzed were successfully applied to 256 individuals. The results provided the first evidence for the existence of M. trossulus in Greenland. The mussel from M. trossulus and M. edulis taxa are shown to coexist and hybridize in the fjord. The three studied sites were found to differ significantly in the distribution of taxa with a higher prevalence of M. trossulus in the inner fjord. The identified M. edulis 9 M. trossulus hybrids mostly had a hybrid index score of about 0.5, indicating a similar number of alleles characteristic for M. trossulus and M. edulis. There was a low number of backcrosses between 'pure' taxa and hybrids. This newly discovered hybrid zone between the two taxa is unique in comparison with the Canadian populations. As Mytilus mussels in Greenland hitherto have been regarded as the one taxon M. edulis, the results have importance for biogeography and future monitoring and environmental studies.
Large-scale climate changes influence the geographic distribution of biodiversity. Many taxa have been reported to extend or reduce their geographic range, move poleward or displace other species. However, for closely related species that can hybridize in the natural environment, displacement is not the only effect of changes of environmental variables. Another option is subtler, hidden expansion, which can be found using genetic methods only. The marine blue mussels Mytilus are known to change their geographic distribution despite being sessile animals. In addition to natural dissemination at larval phase—enhanced by intentional or accidental introductions and rafting—they can spread through hybridization and introgression with local congeners, which can create mixed populations sustaining in environmental conditions that are marginal for pure taxa. The Mytilus species have a wide distribution in coastal regions of the Northern and Southern Hemisphere. In this study, we investigated the inter-regional genetic differentiation of the Mytilus species complex at 53 locations in the North Atlantic and adjacent Arctic waters and linked this genetic variability to key local environmental drivers. Of seventy-nine candidate single nucleotide polymorphisms (SNPs), all samples were successfully genotyped with a subset of 54 SNPs. There was a clear interregional separation of Mytilus species. However, all three Mytilus species hybridized in the contact area and created hybrid zones with mixed populations. Boosted regression trees (BRT) models showed that inter-regional variability was important in many allele models but did not prevail over variability in local environmental factors. Local environmental variables described over 40% of variability in about 30% of the allele frequencies of Mytilus spp. For the 30% of alleles, variability in their frequencies was only weakly coupled with local environmental conditions. For most studied alleles the linkages between environmental drivers and the genetic variability of Mytilus spp. were random in respect to “coding” and “non-coding” regions. An analysis of the subset of data involving functional genes only showed that two SNPs at Hsp70 and ATPase genes correlated with environmental variables. Total predictive ability of the highest performing models (r2 between 0.550 and 0.801) were for alleles that discriminated most effectively M. trossulus from M. edulis and M. galloprovincialis, whereas the best performing allele model (BM101A) did the best at discriminating M. galloprovincialis from M. edulis and M. trossulus. Among the local environmental variables, salinity, water temperature, ice cover and chlorophyll a concentration were by far the greatest predictors, but their predictive performance varied among different allele models. In most cases changes in the allele frequencies along these environmental gradients were abrupt and occurred at a very narrow range of environmental variables. In general, regions of change in allele frequencies for M. trossulus occurred at 8–11 psu, 0–10 °C, 60%–70% of ice cover and 0–2 mg m−3 of chlorophyll a, M. edulis at 8–11 and 30–35 psu, 10–14 °C and 60%–70% of ice cover and for M. galloprovincialis at 30–35 psu, 14–20 °C.
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