Self‐organization of background habitat determines the nature of population spatial structure

Abstract

A substantial literature treats the dynamics of populations in response to spatial patterning of underlying habitats, the most common formulations being source/sink populations and metapopulations living in a patchwork of habitats. A separate and growing literature on the self‐organization of spatial pattern focuses on how local interactions give rise to regional patterns that can be described with scale‐free distributions. Motivated by the potential ubiquity of the coupling of these processes (spatial self organization and the dynamics of organisms in spatially structured habitats), we link these two lines of thought into a theory of populations in fragmented habitats. Using a combined analytical and computational approach, we show that self organization can generate a background into which an independent population fits, and that the scale‐free nature of such habitat creates conditions that influence both the persistence versus extinction properties of the embedded population and where it lies on the continuum between source/sink populations and metapopulations. Both the analytical framework and the computer simulations demonstrate the potential for populations to persist on either end of the metapopulation–source/sink continuum while failing to persist under intermediate conditions. These results provide a new perspective on ecological theory related to habitat fragmentation and population persistence, suggesting that under some conditions intermediate states between these two extremes may maximize risk of extinction of the population. These implications could be of particular importance for managing self‐organized systems of conservation concern.

Self-organisation in striped seagrass meadows affects the distributional pattern of the sessile bivalve Pinna nobilis

“…In fact, the measurement of habitat spatial patterns is an essential prerequisite to monitoring environmental change and to studying the multi-scale processes that drive the distribution and dynamics of resident species. Many applied environmental disciplines such as conservation, epidemiology, coastal zone management, and ecosystem services analysis should be based on the information from landscape ecology 57 . Despite the proven applicability to marine environments, landscape ecology is not growing as fast as expected, and this is a cause of our limited understanding of species-habitat relationships 58,59 .…”

Stabilizing intransitive loops: self‐organized spatial structure and disjoint time frames in the coffee agroecosystem

“…7). Most importantly, as noted elsewhere (Jackson et al 2014), any other organisms that use the ant nests as background habitat will respond to particular critical distances according to their own biological properties.…”

“…As noted above, the arboreal Azteca ant locates its nesting sites in those shade-trees and forages on the nearby coffee trees. As its colony grows, it buds, forming new colonies in nearby shade-trees, thus forming clusters of nests (Vandermeer et al 2010, Jackson et al 2014. But the ant is attacked by a parasitic fly (Pseudacteon spp.)…”

Predicting the occurrence of persistent hotspots in ecosystem variables

“…Distinguishing between these constituent patterns is vital because they represent two very different causes of PSV: Large value differences among sites suggest the importance of underlying spatial gradients in community composition (Jackson et al ), environmental conditions (Brown et al ), or disturbance (Fraterrigo and Rusak ) whereas high stability indicates the importance of temporal attributes like the frequency of environmental perturbations and the resistance and resilience of temporal dynamics to them (Ives and Carpenter , Fraterrigo and Rusak ). From an applied perspective, the dual nature of PSV suggests that no predictors (e.g.…”

“…The main ecological challenge is that many variable‐specific and interacting mechanisms can lead to spatial variation. Such mechanisms include: responses to the spatial and temporal environment (Brown et al , Ives and Klopfer ) or to disturbance (Tamburello et al ); population or community interactions (Taylor , Lecomte et al ); self‐organization (Jackson et al ); and mass effects or source–sink dynamics (Pulliam , Loreau et al ). The existence of multiple ecological pathways to the same pattern makes mechanistic understanding a demanding task.…”