Spatially cascading effect of perturbations in experimental meta-ecosystems

Abstract

Ecosystems are linked to neighbouring ecosystems not only by dispersal, but also by the movement of subsidy. Such subsidy couplings between ecosystems have important landscape-scale implications because perturbations in one ecosystem may affect community structure and functioning in neighbouring ecosystems via increased/decreased subsidies. Here, we combine a general theoretical approach based on harvesting theory and a two-patch protist metaecosystem experiment to test the effect of regional perturbations on local community dynamics. We first characterized the relationship between the perturbation regime and local population demography on detritus production using a mathematical model. We then experimentally simulated a perturbation gradient affecting connected ecosystems simultaneously, thus altering crossecosystem subsidy exchanges. We demonstrate that the perturbation regime can interact with local population dynamics to trigger unexpected temporal variations in subsidy pulses from one ecosystem to another. High perturbation intensity initially led to the highest level of subsidy flows; however, the level of perturbation interacted with population dynamics to generate a crash in subsidy exchange over time. Both theoretical and experimental results show that a perturbation regime interacting with local community dynamics can induce a collapse in population levels for recipient ecosystems. These results call for integrative management of human-altered landscapes that takes into account regional dynamics of both species and resource flows.

Nonlinear higher order abiotic interactions explain riverine biodiversity

“…Furthermore, roots in soil influence biogeochemical conditions together with root-associated microbes (Schade, Fisher, Grimm, & Seddon, 2001). This is consistent with previous fieldbased studies (Kaelin & Altermatt, 2016;Kautza & Sullivan, 2015;Krell et al, 2015;Seymour, Deiner, et al, 2016) and theoretical and experimental studies that predict the importance of cross-ecosystem exchange processes (Loreau et al, 2003) and patterns across landscapes (Harvey et al, 2016). Furthermore, Relative importance score (Pimm et al, 2001).…”

“…Indeed, local biodiversity in running waters is affected by various factors across multiple spatial scales, ranging from local to regional scales (Frissell, Liss, Warren, & Hurley, 1986;O'Neill, DeAngelis, Waide, & Allen, 1986;Poff, 1997). These factors include catchment hydrological processes that reflect upstream terrestrial conditions (Richards, Haro, Johnson, & Host, 1997), connections with adjacent riparian ecosystems (Harvey, Gounand, Ganesanandamoorthy, & Altermatt, 2016;Loreau, Mouquet, & Holt 2003;Soininen, Bartels, Heino, Luoto, & Hillebrand, 2015;Vannote, Minshall, Cummins, Sedell, & Cushing, 1980) and linkages of local environments in dendritic river networks (Altermatt, 2013;Altermatt, Seymour, & Martinez, 2013;Tonkin et al, 2018;Vannote et al, 1980;Ward, 1989). Previous studies reported that major ecological surprises sometimes emerge, as these multiple factors often cause nonlinear interactive effects in freshwater ecosystems (e.g.…”

Upstream trophic structure modulates downstream community dynamics via resource subsidies

“…In the facilitation treatment, the presence of the predator level and thus lead to a decline in detritus quality (increased in recalcitrant chitin content, see Gounand et al, 2017), with negative consequences for connected ecosystems (Gounand et al, 2017). Also, the presence of Euglena (facilitation treatment) generates a local enrichment effect, albeit limited by this species slow growth rate (Harvey et al, 2016). Overall, based on our results, downstream community dynamics seem to be mainly driven by variations in upstream bacteria densities (changes to subsidy quantity due to local upstream species dynamics), which likely acted in parallel to changes in resource quality and quantity from other internal dynamics in upstream ecosystems linked to our various community structure treatments (i.e., decreased quality in the Predation treatment and increased quantity in the Facilitation treatment).…”

“…As our focus is on the effect of different upstream community structures on downstream community dynamics, we use only the treatment rather than species names in the text for the sake of clarity and consistency. The choice of each species combination is based on prior knowledge from previous experiments in similar settings (Carrara, Giometto, Seymour, Rinaldo, & Altermatt, 2015;Gounand et al, 2017;Harvey et al, 2016). These five upstream communities were either connected to a downstream community composed of bacteria alone Each microcosm consisted of a 250-ml Schott bottle that was filled to 100 ml.…”

“…Previous work has shown that directionally biased movement of organisms can have significant effects on species coexistence (Levine, 2003;Lutscher, McCauley, & Lewis, 2007;Lutscher, Pachepsky, & Lewis, 2005;Salomon, Connolly, & Bode, 2010), metapopulation dynamics and stability (Elkin, Possingham, Michalakis, & DeAngelis, 2008;Wang, Haegeman, & Loreau, 2015), and metacommunity structure (Altermatt, Schreiber, & Holyoak, 2011;Bourgeois, González, Vanasse, Aubin, & Poulin, 2016;Dong et al, 2016). Mounting evidence now suggests that communities' dynamics can be indirectly coupled by the reciprocal spatial exchange of resources, even in the absence of dispersal of organisms (i.e., meta-ecosystem, Loreau, Mouquet, & Holt, 2003;Harvey, Gounand, Ganesanandamoorthy, & Altermatt, 2016). In that context, directionally biased movement of resources is a special case of metaecosystems where spatial feedbacks are only possible in one direction.…”