Identifying “vital attributes” for assessing disturbance–recovery potential of seafloor communities
Abstract
Despite a long history of disturbance–recovery research, we still lack a generalizable understanding of the attributes that drive community recovery potential in seafloor ecosystems. Marine soft-sediment ecosystems encompass a range of heterogeneity from simple low-diversity habitats with limited biogenic structure, to species-rich systems with complex biogenic habitat structure. These differences in biological heterogeneity are a product of natural conditions and disturbance regimes. To search for unifying attributes, we explore whether a set of simple traits can characterize community disturbance–recovery potential using seafloor patch-disturbance experiments conducted in two different soft-sediment landscapes. The two landscapes represent two ends of a spectrum of landscape biotic heterogeneity in order to consider multi-scale disturbance–recovery processes. We consider traits at different levels of biological organization, from the biological traits of individual species, to the traits of species at the landscape scale associated with their occurrence across the landscape and their ability to be dominant. We show that in a biotically heterogeneous landscape (Kawau Bay, New Zealand), seafloor community recovery is stochastic, there is high species turnover, and the landscape-scale traits are good predictors of recovery. In contrast, in a biotically homogeneous landscape (Baltic Sea), the options for recovery are constrained, the recovery pathway is thus more deterministic and the scale of recovery traits important for determining recovery switches to the individual species biological traits within the disturbed patch. Our results imply that these simple, yet sophisticated, traits can be effectively used to characterize community recovery potential and highlight the role of landscapes in providing resilience to patch-scale disturbances.
The figure above is a conceptual diagram illustrating three hypotheses of how recovery traits will relate to community recovery potential in multivariate trait space. For hypothesis 1, species (circles whose size indicate abundance) in three hypothetical communities (a, b, and c) are dispersed/positioned within a multivariate trait space based on their recovery trait composition. For hypothesis 2, the trait composition of species in one hypothetical disturbed community changes through time since the disturbance. For hypothesis 3, species in two hypothetical communities at either end of the spectrum of landscape biotic homogenization are depicted to show how landscape biotic homogenization influences local (within-site) recovery trait dispersion, which in hypothesis 1 is predicted to influence community recovery potential.
Marco C Brustolin
Research Fellow
My research interests include numerical ecology, disturbance/diversity relationships and metacommunity dynamics. Pronouns he/him.