Bayesian state-space modeling of metapopulation dynamics in the Glanville fritillary butterfly

Harrison, Philip J.; Hanski, Ilkka; Ovaskainen, Otso

doi:10.1890/11-0192.1

Cited by 47 publications

(59 citation statements)

References 60 publications

(70 reference statements)

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“…Although the ability of our model to make long-term forward predictions is limited, we show that fitting stage-structured models to patch occupancy data has important benefits for understanding the roles of demography and spatial autocorrelation in naturally occurring metapopulations. Our findings provide results that could inform sensible parameterization of predictive simulation (sensu Moilanen 2004) and integrated (Buckland et al 2004, Harrison et al 2011) metapopulation models. Notably, the framework presented here does not account for FIG.…”

Section: Discussionmentioning

confidence: 66%

Multi‐scale processes in metapopulations: contributions of stage structure, rescue effect, and correlated extinctions

Sutherland

Elston

Lambin

2012

Ecology

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Metapopulations function and persist through a combination of processes acting at a variety of spatial scales. Although the contributions of stage structure, spatially correlated processes, and the rescue effect to metapopulation dynamics have been investigated in isolation, there is no empirical demonstration of all of these processes shaping dynamics in a single system. Dispersal and settlement differ according to the life stage involved; therefore, stage-specific population size may outperform total population size when predicting colonization-extinction dynamics. Synchrony in patch dynamics can lead to accelerated metapopulation extinction, although empirical evidence of the interplay between correlated colonization events and correlated extinctions is lacking. Likewise, few empirical examples exist that provide compelling evidence of migration acting to reduce extinction risk (the rescue effect). We parameterized a hierarchy of metapopulation models to investigate these predictions using a seven-year study of a naturally occurring water vole (Arvicola amphibius) metapopulation. Specifically, we demonstrated the importance of local stage structure in predicting both colonization and extinction events using juvenile and adult population sizes, respectively. Using a novel approach for quantifying correlation in extinction events, we compared the scale of synchrony in colonization and extinction. Strikingly, the scale of dispersal acting to synchronize colonization was an order of magnitude larger than that of correlated extinctions (halving distance of the effect: 12.40 km and 0.89 km, respectively). Additionally, we found compelling evidence for the existence of a nontrivial rescue effect. Here we provide a novel empirical demonstration of a variety of metapopulation processes operating at multiple spatial scales, further emphasizing the need to consider stage structure and local synchrony in the dynamics of spatially dependent, stage-structured (meta) populations.

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Section: Discussionmentioning

confidence: 66%

Multi‐scale processes in metapopulations: contributions of stage structure, rescue effect, and correlated extinctions

Sutherland

Elston

Lambin

2012

Ecology

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“…Given that imperfect data are the norm rather than an exception, overlooking this might have major consequences for predictive performance. Interestingly, however, models that do account for imperfect detection very rarely incorporate spatial effects such as dispersal (but see Bled et al 2011, Harrison et al 2011, Risk et al 2011. The key feature of our Bayesian model, and of those just noted, which allows dispersal to be explicitly incorporated into the analysis, is the simultaneous treatment of the true occupancy states of all sites as latent variables to be estimated, in this manner allowing spatial effects to be modeled despite detection error.…”

Section: Discussionmentioning

confidence: 99%

A demographic, spatially explicit patch occupancy model of metapopulation dynamics and persistence

Sutherland

Elston

Lambin

2014

Ecology

121

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Abstract. Patch occupancy models are extremely important and popular tools for understanding the dynamics, and predicting the persistence, of spatially structured populations. Typically this endeavor is facilitated either by models from classic metapopulation theory focused on spatially explicit, dispersal-driven colonization-extinction dynamics and generally assuming perfect detection, or by more recent hierarchical site occupancy models that account for imperfect detection but rarely include spatial effects, such as dispersal, explicitly. Neither approach explicitly considers local demographics in a way that can be used for future projections. However, despite being arguably of equal importance, dispersal and connectivity, local demography, and imperfect detection are rarely modeled explicitly and simultaneously. Understanding the spatiotemporal occurrence patterns of spatially structured populations and making biologically realistic long-term predictions of persistence would benefit from the simultaneous treatment of space, demography, and detectability. We integrated these key ideas in a tractable and intuitive way to develop a demographic and spatially realistic patch occupancy model that incorporates components of dispersal, local demographic stage-structure, and detectability. By explicitly relating stage-specific abundances to measurable patch properties, biologically realistic projections of long-term metapopulation dynamics could be made. We applied our model to data from a naturally fragmented population of water voles Arvicola amphibius to describe observed patch occupancy dynamics and to investigate long-term persistence under scenarios of elevated stage-specific local extinction. Accounting for biases induced by imperfect detection, we were able to estimate: stable, and higher than observed metapopulation occupancy; high rates of patch turnover and stage-specific colonization and extinction rates ( juvenile and adult, respectively); and juvenile dispersal distances (average 2.10 km). We found that metapopulation persistence in the presence of elevated extinction risk differed depending on which life stage was exposed, and was more sensitive to elevated juvenile rather than adult extinction risk. Predictions of persistence when dynamics are stage-specific suggest that metapopulations may be more resilient to changes in the environment than predicted when relationships are based on patch size approximations rather than population sizes. Our approach allows explicit consideration of local dynamics and dispersal in spatially structured and stage-structured populations, provides a more detailed mechanistic understanding of metapopulation functioning, and can be used to investigate future extinction risk under biologically meaningful scenarios.

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“…While Gibbs sampling has been introduced 30 years ago (Geman and Geman, 1984), its application to handle missing data in ecology has been mostly limited to stochastic patch occupancy models with a low number of free parameters (5e6) and either artificially simulated data or relatively restricted datasets (e.g. 72e228 resampled locations in ter Braak and Etienne, 2003;Harrison et al, 2011;Risk et al, 2011). From the technical point of view, our application of MCMC differs by taking advantage of the absolute time independence of Markov chains (allowing us to align sub-sequences starting with a known observation, see Methods and Appendix).…”

Section: A Data-intensive Approach To Understand Forest Dynamicsmentioning

confidence: 99%

Data-intensive modeling of forest dynamics

Liénard

Gravel

Strigul

2015

Environmental Modelling & Software

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a b s t r a c t Forest dynamics are highly dimensional phenomena that are not fully understood theoretically. Forest inventory datasets offer unprecedented opportunities to model these dynamics, but they are analytically challenging due to high dimensionality and sampling irregularities across years. We develop a dataintensive methodology for predicting forest stand dynamics using such datasets. Our methodology involves the following steps: 1) computing stand level characteristics from individual tree measurements, 2) reducing the characteristic dimensionality through analyses of their correlations, 3) parameterizing transition matrices for each uncorrelated dimension using Gibbs sampling, and 4) deriving predictions of forest developments at different timescales. Applying our methodology to a forest inventory database from Quebec, Canada, we discovered that four uncorrelated dimensions were required to describe the stand structure: the biomass, biodiversity, shade tolerance index and stand age. We were able to successfully estimate transition matrices for each of these dimensions. The model predicted substantial short-term increases in biomass and longer-term increases in the average age of trees, biodiversity, and shade intolerant species. Using highly dimensional and irregularly sampled forest inventory data, our original data-intensive methodology provides both descriptions of the short-term dynamics as well as predictions of forest development on a longer timescale. This method can be applied in other contexts such as conservation and silviculture, and can be delivered as an efficient tool for sustainable forest management.

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Bayesian state-space modeling of metapopulation dynamics in the Glanville fritillary butterfly

Cited by 47 publications

References 60 publications

Multi‐scale processes in metapopulations: contributions of stage structure, rescue effect, and correlated extinctions

Multi‐scale processes in metapopulations: contributions of stage structure, rescue effect, and correlated extinctions

A demographic, spatially explicit patch occupancy model of metapopulation dynamics and persistence

Data-intensive modeling of forest dynamics

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