Spatiotemporal connectivity dynamics in spatially structured populations

Joseph Drake*, Xavier Lambin, Chris Sutherland

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
8 Downloads (Pure)


Connectivity is a fundamental concept linking dispersal to the emergent dynamics and persistence of spatially structured populations. Functional measures of connectivity typically seek to integrate aspects of landscape structure and animal movement to describe ecologically meaningful connectedness at the landscape and population scale. Despite this focus on function, traditional measures of landscape connectivity assume it is a static property of the landscape, hence abstracting out the underlying spatiotemporal population dynamics. Connectivity is, arguably, a dynamic property of landscapes, and is inherently related to the spatial distribution of individuals and populations across the landscape. Static representations of connectivity potentially overlook this variation and therefore adopting a dynamic approach should offer improved insights about connectivity and associated ecological processes. Using a large-scale, long-term time series of occupancy data from a metapopulation of water voles Arvicola amphibius, we tested competing hypotheses about how considering the dynamic nature of connectivity improves the ability of spatially explicit occupancy models to recover population dynamics. Iteratively relaxing standing assumptions of connectivity metrics, these models ranged from spatially and temporally fixed connectivity metrics that are widely applied, to the more flexible, but lesser used model that allowed temporally varying connectivity measures that incorporate spatiotemporally dynamic patch occupancy states. Our results provide empirical evidence that demographic weighting using patch occupancy dynamics and temporal variability in connectivity measures are important for describing metapopulation dynamics. We highlight the implications of commonly held assumption in connectivity modelling and demonstrate how they result in different and highly variable predictions of metapopulation capacity. Thus, we argue that the concept of connectivity and its potential applications would benefit from recognizing inherent spatiotemporal variation in connectivity that is explicitly linked to underlying ecological state variables.

Original languageEnglish
Pages (from-to)2050-2060
Number of pages11
JournalJournal of Animal Ecology
Issue number10
Early online date30 Jul 2022
Publication statusPublished - 4 Oct 2022

Bibliographical note

ACKNOWLEDGEMENTS This work was supported in part by the UMass Organismal and Evolutionary Biology Graduate Research Grant and UMass Graduate School Fieldwork Grant. The authors thank Dr Toni- Lyn Morelli, Dr Benjamin Padilla and three anonymous reviewers for valuable feedback

Data Availability Statement

DATA AVAILABILITY STATEMENT Model output and spatial data are available via the Dryad Digital Repository (Drake et al., 2022). Sensitive location data have been augmented to obscure sensitive species exact locations while retaining relative net-work structure to allow replicability.


  • Bayesian
  • colonization-extinction
  • mammal
  • population dynamics
  • spatially realistic metapopulation model
  • SPOM
  • stochastic patch occupancy model
  • structural connectivity


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