When things don't add up: quantifying impacts of multiple stressors from individual metabolism to ecosystem processing

Abstract

Ecosystems are exposed to multiple stressors which can compromise functioning and service delivery. These stressors often co-occur and interact in different ways which are not yet fully understood. Here, we applied a population model representing a freshwater amphipod feeding on leaf litter in forested streams. We simulated impacts of hypothetical stressors, individually and in pairwise combinations that target the individuals' feeding, maintenance, growth and reproduction. Impacts were quantified by examining responses at three levels of biological organisation: individual-level body sizes and cumulative reproduction, population-level abundance and biomass and ecosystem-level leaf litter decomposition. Interactive effects of multiple stressors at the individual level were mostly antagonistic, that is, less negative than expected. Most population- and ecosystem-level responses to multiple stressors were stronger than expected from an additive model, that is, synergistic. Our results suggest that across levels of biological organisation responses to multiple stressors are rarely only additive. We suggest methods for efficiently quantifying impacts of multiple stressors at different levels of biological organisation.

Combined effects of salinity and infectious disease on Daphnia dentifera at multiple scales

“…However, this previous study (Hall et al., ) focused on individual‐level effects, while our results show that these effects can also occur at the population level. Thus, while both increased salinity and parasite exposure can reduce population densities of the host, the combined effect of these variables can be less than‐additive (Galic, Sullivan, Grimm, & Forbes, ; Romero, Sabater, Timoner, & Acuña, ). The non‐additive effect of salinity and parasitism is probably driven by the reduced infection prevalence we observed as salinity increased.…”

Give chance a chance: from coexistence to coviability in biodiversity theory

“…, Galic et al. ). These and other kinds of behavioral plasticity reflect important evolutionary principles and have consequences for species survival and hence coexistence (Jeltsch et al.…”

“…Habitat selection of brown trout, for example, depends not only on size and age but also on the presence of conspecifics, predators, and the features of a river's morphology and flow regime (Railsback and Harvey 2013). Likewise, animals invest different proportions of ingested energy into maintenance, growth, and reproduction depending on their size, their maturity, and resource availability (Sibly et al 2013, Galic et al 2018). These and other kinds of behavioral plasticity reflect important evolutionary principles and have consequences for species survival and hence coexistence (Jeltsch et al 2013a).…”

Understanding ecological change across large spatial, temporal and taxonomic scales: integrating data and methods in light of theory

“…Traitbased models may involve empirically relating intra-and/ or inter-specific trait values to environmental variation using correlative models and projecting how the spatiotemporal distribution of traits and their performance across environmental gradients give rise to assemblage-level properties (Laughlin et al 2012, Lasky et al 2014, Laughlin and Messier 2015. Alternatively, trait-based models may involve describing trait-environment relationships mechanistically from first principles (Norberg et al 2001, Shipley et al 2006, Savage et al 2007, Jabot 2010, Enquist et al 2015, Holt and Chesson 2016, Scherer et al 2016, Galic et al 2018. Such mechanistic models are highly theoretical and translate common notions of trait-based mechanisms into dynamic differential equations.…”