Metapopulation viability analysis of the greater glider Petauroides volans in a wood production area

Possingham, Hugh P.; Lindenmayer, David B.; Norton, TW; Davies, Ian D.

doi:10.1016/0006-3207(94)90167-8

Cited by 78 publications

(71 citation statements)

References 25 publications

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“…By including habitat dynamics in spatially explicit metapopulation models (Fahrig, 1992;Gyllenberg and Hanski, 1997;Brachet et al, 1999;Johnson, 2000;Keymer et al, 2000;Amarasekare and Possingham, 2001;Ellner and Fussmann, 2003;Thomas and Hanski, 2004), it is possible to provide management and conservation plans for species in successional systems and systems subject to occasional disturbance (Possingham et al, 1994;Lindenmayer and Possingham, 1996;McCarthy and Lindenmayer, 2000;Amarasekare and Possingham, 2001;Akcakaya et al, 2004). In this paper, we use a metapopulation and patch dynamic simulation model using object-oriented programming to look closely at the implications of spatial and temporal structure of disturbances in metapopulations with different spatial patch configurations.…”

Section: Discussionmentioning

confidence: 99%

How patch configuration affects the impact of disturbances on metapopulation persistence

Vuilleumier

Wilcox

Cairns

et al. 2007

Theoretical Population Biology

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Disturbances affect metapopulations directly through reductions in population size and indirectly through habitat modification. We consider how metapopulation persistence is affected by different disturbance regimes and the way in which disturbances spread, when metapopulations are compact or elongated, using a stochastic spatially explicit model which includes metapopulation and habitat dynamics. We discover that the risk of population extinction is larger for spatially aggregated disturbances than for spatially random disturbances. By changing the spatial configuration of the patches in the system-leading to different proportions of edge and interior patches-we demonstrate that the probability of metapopulation extinction is smaller when the metapopulation is more compact. Both of these results become more pronounced when colonization connectivity decreases. Our results have important management implication as edge patches, which are invariably considered to be less important, may play an important role as disturbance refugia. r

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Section: Discussionmentioning

confidence: 99%

How patch configuration affects the impact of disturbances on metapopulation persistence

Vuilleumier

Wilcox

Cairns

et al. 2007

Theoretical Population Biology

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“…ALEX is a computer simulation program that uses the Monte Carlo method, drawing pseudorandom numbers to simulate the stochastic processes that underlie population dynamics. This model has been used to study the population viability of a range of species, including marsupials (Possingham et al 1994; and birds (McCarthy et al 2000). Below is a summary of the main features of ALEX relevant to this study (for a detailed description see Possingham and Davies 1995).…”

Section: The Pva Model: Alexmentioning

confidence: 99%

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Ball

Lindenmayer

Possingham

2003

Biodiversity and Conservation

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This study examines the predictive accuracy of the population viability analysis package, ALEX (Analysis of the Likelihood of EXtinction). ALEX was used to predict the probability of patch occupancy for two species of small native Australian mammals (Antechinus agilis and Rattus fuscipes) among 13 patches of suitable habitat in a matrix of plantation pines (Pinus radiata). The study was retrospective, running each simulation from 1900 until 1997, and the model parameterised without knowledge of the 1997 observed field data of patch occupancy. Predictions were made over eight scenarios for each species, allowing for variation in the amount of dispersal between patches, level of environmental stochasticity, and size of habitat patches. Predicted occupancies were compared to the 1997 field data of patch occupancy using logistic regression, testing H r a n d o m , that there was no relationship between observed and predicted occupancy, and H p e r f e c t , that there was a perfect, 1:1 relationship between observed and predicted occupancies. Rejection of H random and failure to reject H perfect was taken as a good match between observed and predicted occupancies. Such a match was found for one scenario with R. fuscipes, and no scenarios with A. agilis. In general, patch occupancy was underestimated, with field surveys finding that 9 of the 13 patches were occupied by R. fuscipes and 10 by A. agilis. Nonetheless, PVA predictions were in the 'right direction', whereby patches predicted to have a high probability of occupancy were generally occupied, and vice versa. A post hoc search over additional scenarios found few scenarios with a better match than the original eight. The results of this study support the notion that PVA is best thought of as a relative, rather than absolute predictor of the consequences of management actions in threatened populations.

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“…Possingham et al 1994, Lindenmayer andPossingham 1996). Consequently, the general structure and most important components of ALEX are only briefly outlined below.…”

Section: The Alex Simulation Modelmentioning

confidence: 99%

“…those for Population Viability Analysis) can also help forecast population dynamics in fragmented systems (McCarthy 1995, Possingham and Davies 1995, Wahlberg et al 1996. They also can be used to predict the effects of landscape change on species decline (Lamberson et al 1994, Possingham et al 1994, McCarthy and Lindenmayer 1999. However, the accuracy of forecasts made using these tools have only rarely been tested (Hanski et al 1995, Hanski and Simberloff 1997, Lindenmayer et al 1999a.…”

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confidence: 99%

A simple landscape‐scale test of a spatially explicit population model: patch occupancy in fragmented south‐eastern Australian forests

Lindenmayer

McCarthy²,

Possingham³

et al. 2001

Oikos

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The results of a landscape-scale test of ALEX, a widely used metapopulation model for Population Viability Analysis (PVA), are described. ALEX was used to predict patch occupancy by the laughing kookkaburra and the sacred kingfisher in patches of eucalypt forest in south-eastern Australia. These predictions were compared to field surveys to determine the accuracy of the model. Predictions also were compared to a ''naïve'' null model assuming no fragmentation effects. The naïve null model significantly over-predicted the number of eucalypt patches occupied by the sacred kingfisher, but the observed patch occupancy was not significantly different from that predicted using ALEX. ALEX produced a better fit to the field data than the naïve null model for the number of patches occupied by the laughing kookaburra. Nevertheless, ALEX still significantly over-predicted the number of occupied patches, particularly remnants dominated by certain forest typesribbon gum and narrow-leaved peppermint. The predictions remained significantly different from observations, even when the habitat quality of these patches was reduced to zero. Changing the rate of dispersal improved overall predicted patch occupancy, but occupancy rates for the different forest types remained significantly different from the field observations. The lack of congruence between field data and model predictions could have arisen because the laughing kookaburra may move between an array of patches to access spatially separated food and nesting resources in response to fragmentation. Alternatively, inter-specific competition may be heightened in a fragmented habitat. These types of responses to fragmentation are not incorporated as part of traditionally applied metapopulation models. Assessments of predictions from PVA models are rare but important because they can reveal the types of species for which forecasts are accurate and those for which they are not. This can assist the collection of additional empirical data to identify important factors affecting population dynamics.

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Metapopulation viability analysis of the greater glider Petauroides volans in a wood production area

Cited by 78 publications

References 25 publications

How patch configuration affects the impact of disturbances on metapopulation persistence

How patch configuration affects the impact of disturbances on metapopulation persistence

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A simple landscape‐scale test of a spatially explicit population model: patch occupancy in fragmented south‐eastern Australian forests

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