Ecological quality assessment in the Eastern Mediterranean combining live and dead molluscan assemblages

Leshno, Yael; Benjamini, Chaim; Edelman‐Furstenberg, Yael

doi:10.1016/j.marpolbul.2016.01.014

Cited by 17 publications

(20 citation statements)

References 42 publications

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“…One common tool used by conservation paleobiologists to assess anthropogenic impacts on ecosystems is the analysis of live–dead agreement (e.g., see Albano and Sabelli 2011; Casey et al 2014; Negri et al 2015; Leshno et al 2016; Dietl and Smith 2017; Tomašových and Kidwell 2017). In such analyses, living assemblages and their death assemblages are assessed for agreement in species composition and rank-order abundance.…”

Section: Discussionmentioning

confidence: 99%

Life span bias explains live–dead discordance in abundance of two common bivalves

et al. 2018

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Life span bias potentially alters species abundance in death assemblages through the overrepresentation of short-lived organisms compared with their long-lived counterparts. Although previous work found that life span bias did not contribute significantly to live–dead discordance in bivalve assemblages, life span bias better explained discordance in two groups: longer-lived bivalve species and species with known life spans. More studies using local, rather than global, species-wide life spans and mortality rates would help to determine the prevalence of life span bias, especially for long-lived species with known life spans. Here, we conducted a field study at two sites in North Carolina to assess potential life span bias between Mercenaria mercenaria and Chione elevata, two long-lived bivalve species that can be aged directly. We compared the ability of directly measured local life spans with that of regional and global life spans to predict live–dead discordance between these two species. The shorter-lived species (C. elevata) was overrepresented in the death assemblage compared with its live abundance, and local life span data largely predicted the amount of live–dead discordance; local life spans predicted 43% to 88% of discordance. Furthermore, the global maximum life span for M. mercenaria resulted in substantial overpredictions of discordance (1.4 to 1.6 times the observed live–dead discordance). The results of this study suggest that life span bias should be considered as a factor affecting proportional abundances of species in death assemblages and that using life span estimates appropriate to the study locality improves predictions of discordance based on life span compared with using global life span estimates.

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Section: Discussionmentioning

confidence: 99%

Life span bias explains live–dead discordance in abundance of two common bivalves

et al. 2018

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“…Examining the benthic community data from 12 studies, Dietl et al (2016) calculated AMBI with only mollusks, emulating the type of data expected to be found in a death assemblage, and compared the results with AMBI values calculated from the whole macrobenthic invertebrate community. They developed a correction based on the relationship between whole-community and mollusk-only values that, when applied to the mollusk-only data, successfully recovered whole-community EcoQS for 78% of stations ( n = 45), validating the use of AMBI for the evaluation of the effects of eutrophication with the geohistorical record (e.g., Leshno et al 2016; Tweitmann and Dietl 2018; Caswell et al 2019).…”

Section: An Adaptable Live–dead Approach For a Changing Worldmentioning

confidence: 95%

“…In contrast, taxon-free benthic indices (e.g., Karr 1981, 1991; Kerans and Karr 1994; Borja et al 2000; Simboura and Zenetos 2002) are based in organismal biology (e.g., life histories and sensitivities to environmental factors; Schaeffer et al 1985; Borja et al 2000; Simboura and Zenetos 2002; Adakole and Anunne 2003; Bellinger et al 2006; Sutherland et al 2007; Hess et al 2020), leading to a more direct stressor–response relationship and a corresponding increase in the power to detect eutrophication (or other types of disturbances; Borja et al 2015). As such, integrating geohistorical data with taxon-free benthic indices (e.g., Dietl et al 2016) may be a fruitful opportunity to increase the salience of geohistorical data in a rapidly changing Anthropocene world (Dietl et al 2016; Leshno et al 2016; Tweitmann and Dietl 2018; Caswell et al 2019).…”

Section: An Adaptable Live–dead Approach For a Changing Worldmentioning

confidence: 99%

“…The AMBI and M-AMBI indices can readily accommodate the inclusion of geohistorical data (e.g., Dietl et al 2016; Leshno et al 2016; Tweitmann and Dietl 2018; Caswell et al 2019) and, because they are calculated based on relative proportions of ecological groups that are independent of particular species’ identities, they do not require the assumption that the environment has remained stable (Kröncke and Reiss 2010; Van Hoey et al 2010). This feature, combined with the grounding of ecological group assignments in species’ tolerances and sensitivities to human disturbance (Kröncke and Reiss 2010; Borja et al 2013; Elliott et al 2015), makes both AMBI metrics useful tools for assessing EcoQS, irrespective of environmental changes.…”

Section: An Adaptable Live–dead Approach For a Changing Worldmentioning

confidence: 99%

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Increasing the salience of marine live–dead data in the Anthropocene

2020

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As the climate changes and ecosystems shift toward novel combinations of species, the methods and metrics of conservation science are becoming less species-centric. To meet this growing need, marine conservation paleobiologists stand to benefit from the addition of new, taxon-free benthic indices to the live–dead analysis tool kit. These indices, which were developed to provide actionable, policy-specific data, can be applied to the readily preservable component of benthic communities (e.g., mollusks) to assess the ecological quality status of the entire community. Because these indices are taxon-free, they remain applicable even as the climate changes and novel communities develop—making them a potentially valuable complement to traditionally applied approaches for live–dead analysis, which tend to focus on maintaining specific combinations of species under relatively stable environmental conditions. Integrating geohistorical data with these established indices has potential to increase the salience of the live–dead approach in the eyes of resource managers and other stakeholders.

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“…For instance, using AMBI and Bentix, Nerlović et al (2011) found notable differences in the WFD ecological status categories of the bivalve community following anoxic events in the eastern portion of the northern Adriatic Sea. Similarly, again using AMBI and Bentix, Leshno et al (2016) were able to detect the effects of pollution on the molluscan fauna off the Israeli coast. Although these studies demonstrated that differences in ecological status categories can be detected using only mollusks, Nerlović et al (2011) and Leshno et al (2016) did not confirm that benthic indices based solely on mollusks were correlated with those calculated from the whole benthic community.…”

Section: Introductionmentioning

confidence: 99%