The Consequences of Nonrandomness in Species-Sensitivity in Relation to Functional Traits for Ecosystem-Level Effects of Chemicals

Baert, Jeroen; Laender, Frederik De; Janssen, Colin R.

doi:10.1021/acs.est.7b00527

Cited by 12 publications

(10 citation statements)

References 54 publications

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“…Second, in the present study, the unstressed and stressed community were dominated by the same algae strains. However, how community compositions change highly depends on the correlation between competitive abilities and the sensitivity to the stressor (De Laender et al 2016, Baert et al 2017, Spaak et al 2017). Third, our study design used six algae strains that were initially present in each community, and we did not allow dispersal from the regional species pool (Lessard et al 2012).…”

Section: Discussionmentioning

confidence: 99%

Stressor fluxes alter the relationship between beta‐diversity and regional productivity

Raedt

Baert

Janssen

et al. 2019

Oikos

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Dispersal of organisms can influence the relationship between beta-diversity and regional productivity in heterogeneous environments. However, many ecosystems are also linked by fluxes of stressors, with an unknown influence on this relationship. In this study, we assess the relationship between beta-diversity (measured as Bray-Curtis dissimilarity) and regional productivity (measured as biovolume) under various levels of a stressor flux in meta-ecosystems that were composed of two marine micro-algae communities. We created heterogeneity by exposing one of the two communities to a herbicide and manipulated regional diversity by applying a dispersal gradient, which decreased beta-diversity. We applied four stressor flux levels, which homogenized the herbicide concentration between the communities over time. The stressor flux changed the relationship between beta-diversity and regional productivity by changing the effect of dispersal on regional productivity. In absence of the stressor flux, the relationship between beta-diversity and regional productivity was mostly not significant, but positive at the end of the experiment. This positive relationship was generated by a negative effect of dispersal on regional productivity, probably because dispersal disrupted local dynamics by removing organisms from the most-productive unstressed community. In presence of the stressor flux, the relationship between beta-diversity and regional productivity was often negative as dispersal now increased regional productivity. Dispersal increased regional productivity by increasing the productivity of the stressed community. This positive effect was stronger in the presence than in the absence of the stressor flux because the stressor flux reduced the concentration of the herbicide in the stressed community, where it facilitated recovery. Our study shows that stressor fluxes can strongly interact with the effects of dispersal on productivity and thus influence diversity-productivity relationships.

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Section: Discussionmentioning

confidence: 99%

Stressor fluxes alter the relationship between beta‐diversity and regional productivity

Raedt

Baert

Janssen

et al. 2019

Oikos

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“…Indirect effects are made possible because contaminants frequently affect exposed organisms differentially. Asymmetrical effects occur when one species is more sensitive and another is more resistant to a contaminant [10]. A simple, straightforward example of indirect effects in a low diversity system is illustrated by a hypothetical food chain in which one or a few producer species are consumed by one or a few primary consumer species, which are in turn consumed by one or a few secondary consumer species ( Figure 2).…”

Section: Introduction To Indirect Effectsmentioning

confidence: 99%

How Do Indirect Effects of Contaminants Inform Ecotoxicology? A Review

Fleeger

2020

Processes

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Indirect effects in ecotoxicology are defined as chemical- or pollutant-induced alterations in the density or behavior of sensitive species that have cascading effects on tolerant species in natural systems. As a result, species interaction networks (e.g., interactions associated with predation or competition) may be altered in such a way as to bring about large changes in populations and/or communities that may further cascade to disrupt ecosystem function and services. Field studies and experimental outcomes as well as models indicate that indirect effects are most likely to occur in communities in which the strength of interactions and the sensitivity to contaminants differ markedly among species, and that indirect effects will vary over space and time as species composition, trophic structure, and environmental factors vary. However, knowledge of indirect effects is essential to improve understanding of the potential for chemical harm in natural systems. For example, indirect effects may confound laboratory-based ecological risk assessment by enhancing, masking, or spuriously indicating the direct effect of chemical contaminants. Progress to better anticipate and interpret the significance of indirect effects will be made as monitoring programs and long-term ecological research are conducted that facilitate critical experimental field and mesocosm investigations, and as chemical transport and fate models, individual-based direct effects models, and ecosystem/food web models continue to be improved and become better integrated.

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“…Concerning indirect effects, impacts can turn out worse than expected due to a cascading effect at the population or community level effect. Consider, for instance, the loss of keystone species or ecosystem engineers, for which any loss of function will result in a disproportional effect on ecosystem functions (Baert, De Laender et al 2017). Alternatively, impacts can turn out lower than expected due to a high recoverability of the species (Gabsi and Preuss 2014), or due to the fact that other species take over the ecosystem function of the species that goes extinct (i.e.…”

Section: Sensitivity Is a Complex Problemmentioning

confidence: 99%

“…After the introduction of trait-based approaches as a potential tool in ERA around a decade ago (Liess and Von der Ohe 2005, Baird and Van den Brink 2007, Buchwalter, Cain et al 2007, Baird, Rubach et al 2008, they have been rapidly evolving , Liess and Beketov 2011, Van den Brink, Alexander et al | 2011, Ippolito, Todeschini et al 2012, Rico and Van den Brink 2015, Baert, De Laender et al 2017. Baird and Van den Brink (2007) were among the first to use biological traits to predict species sensitivity.…”

Section: Introductionmentioning

confidence: 99%

“…In addition to that, describing aquatic communities in terms of their biological traits increases the generality of such characterizations and their subsequent transferability between regions (Van den Brink, Alexander et al 2011). Also, correlations between species traits and species sensitivity might exist, potentially resulting in unexpected effects at the community level (Baert, De Laender et al 2017).…”

Section: Introductionmentioning

confidence: 99%

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Improving cross-species extrapolation of chemical sensitivity

Berg¹

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In this study, a trait-based macroinvertebrate sensitivity modelling tool is presented that provides two main outcomes: (1) it constructs a macroinvertebrate sensitivity ranking and, subsequently, a predictive trait model for each one of a diverse set of pre-defined Modes of Action (MOAs) and (2) it reveals data gaps and restrictions, helping with the direction of future research. Besides revealing taxonomic patterns of species sensitivity, we find that there was not one genus, family or class which was most sensitive to all MOAs, and that common test taxa were often not the most sensitive at all. Traits like life cycle duration and feeding mode were identified as important in explaining species sensitivity. For 71% of the species, no or incomplete traits data were available, making the lack of trait data the main obstacle in model construction. Research focus should therefore be on completing trait databases, and enhancing them with finer morphological traits, focusing on the toxicodynamics of the chemical (e.g. target site distribution). Further improved sensitivity models can help with the creation of ecological scenarios by predicting the sensitivity of untested species. Through this development, our approach can help reduce animal testing and contribute towards a new predictive ecotoxicology framework.

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The Consequences of Nonrandomness in Species-Sensitivity in Relation to Functional Traits for Ecosystem-Level Effects of Chemicals

Cited by 12 publications

References 54 publications

Stressor fluxes alter the relationship between beta‐diversity and regional productivity

Stressor fluxes alter the relationship between beta‐diversity and regional productivity

How Do Indirect Effects of Contaminants Inform Ecotoxicology? A Review

Improving cross-species extrapolation of chemical sensitivity

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