Scale-Dependent Community Theory for Streams and Other Linear Habitats

Abstract

The maintenance of species diversity occurs at the regional scale but depends on interacting processes at the full range of lower scales. Although there is a long history of study of regional diversity as an emergent property, analyses of fully multiscale dynamics are rare. Here, we use scale transition theory for a quantitative analysis of multiscale diversity maintenance with continuous scales of dispersal and environmental variation in space and time. We develop our analysis with a model of a linear habitat, applicable to streams or coastlines, to provide a theoretical foundation for the long-standing interest in environmental variation and dispersal, including downstream drift. We find that the strength of regional coexistence is strongest when local densities and local environmental conditions are strongly correlated. Increasing dispersal and shortening environmental correlations weaken the strength of coexistence regionally and shift the dominant coexistence mechanism from fitness-density covariance to the spatial storage effect, while increasing local diversity. Analysis of the physical and biological determinants of these mechanisms improves understanding of traditional concepts of environmental filters, mass effects, and species sorting. Our results highlight the limitations of the binary distinction between local communities and a species pool and emphasize species coexistence as a problem of multiple scales in space and time.

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

“…Scale transition theory predicts the emergent behavior of metacommunities at large spatial and/or temporal scales from the smaller spatial-and/or temporal-scale behavior of populations. Though we have included this approach in the 'Modeling selection' section, the method also includes aspects of other processes as well, particularly dispersal (Holt and Chesson 2016). These models are integrative because they estimate parameters summarizing nonlinearities at the local scale from experimental data and combine these with spatial and/or temporal variation estimated from field sampling programs, for example, to identify how properties change or emerge as the scale expands.…”

“…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.…”

“…Another development in integrative modeling -scale transition theory -shows particular promise for integrating across spatial and temporal scales (Melbourne and Chesson 2005, Chesson 2009, Holt and Chesson 2016. Scale transition theory predicts the emergent behavior of metacommunities at large spatial and/or temporal scales from the smaller spatial-and/or temporal-scale behavior of populations.…”

“…These models are integrative because they estimate parameters summarizing nonlinearities at the local scale from experimental data and combine these with spatial and/or temporal variation estimated from field sampling programs, for example, to identify how properties change or emerge as the scale expands. Though we have included this approach in the 'Modeling selection' section, the method also includes aspects of other processes as well, particularly dispersal (Holt and Chesson 2016).…”

The role of branching in the maintenance of diversity in watersheds

“…Moreover, the branching topology of the stream affects connectivity between local populations and habitats, leading to consistent findings of increased local diversity near confluences and lower in the watershed (Heino and Mykrä 2008, Brown and Swan 2010, Finn et al 2011, Carrara et al 2012, Swan and Brown 2014, Kuglerová et al 2015. Beyond patterns of local diversity, various lines of evidence, both theoretical (Tilman 1994, Snyder and Chesson 2004, Aiken and Navarrete 2014, Holt and Chesson 2016 and empirical (Campbell Grant et al 2010, Carson et al 2010, Pedruski and Arnott 2011, Bode et al 2011, Perkin and Gido 2012, suggest that connectivity has major effects on spatial coexistence mechanisms and, thus, has the potential to affect species diversity in the watershed as a whole. The resulting watershed-scale species pool then feeds into local populations.…”