Paying the extinction debt: woodland birds in the Mount Lofty Ranges, South Australia

Szabo, Judit K.; Vesk, Peter A.; Baxter, Peter; Possingham, Hugh P.

doi:10.1071/mu09114

Cited by 75 publications

(57 citation statements)

References 31 publications

(35 reference statements)

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“…It is thus unsurprising that inbreeding through population contraction leads to increased extinction risk (Saccheri et al 1998;Nieminen et al 2001;Frankham 2005a;O'Grady et al 2006). A decline in habitat quality may contribute to 'extinction debt' before demographic stochasticity finally delivers the coup de grâce (Ford et al 2009;Szabo et al 2011), but inbreeding depression may often drive demographic decline. It is detectable by genetic approaches, and is potentially reversible.…”

Section: Fitness Geneticsmentioning

confidence: 99%

“…Long-term monitoring has identified significant collapses in woodland bird populations in southern and eastern Australia, including of recently common species Szabo et al 2011;Watson 2011). The capacity to improve the situation depends on understanding the interaction of the natural history of species with habitat features, subsequent demographic outcomes, and critical ecological processes within a system (Kavanagh et al 2007;Bowen et al 2009;Selwood et al 2009;Ford 2011).…”

Section: Avian Declines and The Need For Understanding Ecological Promentioning

confidence: 99%

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Towards modelling persistence of woodland birds: the role of genetics

Sunnucks

2011

Emu - Austral Ornithology

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Abstract. Assessing how environmental change affects the probability of persistence of organisms requires an understanding of dispersal through, and occupation of, landscapes, and the associated demographic outcomes. Projections of differences in persistence probability can then be made under different scenarios of land-use and global environmental change. Rates and distances of dispersal, and demographic change and trajectories, are difficult to measure accurately, but genetic approaches can make major contributions. For two decades the field of molecular ecology has been providing useful life-history information relevant to population management, including key ecological attributes such as disease-resistance and thermal biology, mobility, dispersal and gene flow, habitat connectivity, the spatial and temporal scales of population processes, and demography. Genetic estimators of these factors could be employed to a much greater extent than they are currently. To facilitate this increased use, genetic estimates of functional connectivity (mobility and gene flow of organisms) and demography need to be integrated directly into decision-making processes. Population genetics is well suited to Bayesian approaches, with associated benefits including the ability to consider many factors, and estimation of error and parameter sensitivities. Genetic estimators based on the mobility and reproductive success of individual organisms and their key ecological traits can make unique contributions alongside other types of data into agent-based, spatially explicit modelling approaches of real landscape scenarios at the range of scales needed by managers. Virtually all the tools to do this exist. It is imperative that genetic samples be collected for contemporary and future analyses.

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Section: Fitness Geneticsmentioning

confidence: 99%

Section: Avian Declines and The Need For Understanding Ecological Promentioning

confidence: 99%

Towards modelling persistence of woodland birds: the role of genetics

Sunnucks

2011

Emu - Austral Ornithology

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“…While some studies provide evidence of historical declines (Saunders & Ingram 1995;Woinarski & Catterall 2004), others demonstrate ongoing losses (Mac Nally et al 2009;Stevens & Watson 2013;Rayner et al 2014). Taxa generally considered to be common and widespread are not immune to the problem, with declines observed for species such as grey shrike thrush (Colluricincla harmonica; Stevens & Watson 2013), grey fantail (Rhipidura albiscapa; Stevens & Watson 2013), striated thornbill (Acanthiza lineata; Szabo et al 2011), and eastern yellow robin (Eopsaltria australis; Stevens & Watson 2013). The decline of common species is concerning as they could have disproportionately large potential flow-on effects to the structure and functioning of ecosystems (Gaston & Fuller 2008;Godet et al 2015).…”

Section: Australian Woodland Bird Declinesmentioning

confidence: 99%

“…Habitat loss and fragmentation, combined with land-use intensification, have placed enormous pressure on woodland-dependent biota resulting in reduced abundance and occurrence (Ford et al 2001;Barrett et al 2007;Vié et al 2009). Even previously common, widespread taxa are in decline (Szabo et al 2011;Stevens & Watson 2013) which could have alarming knock-on effects on both the structure and function of ecosystems (Gaston & Fuller 2008). …”

Section: Introductionmentioning

confidence: 99%

Why are woodland-dependent avian insectivore populations vulnerable to declines in highly-modified landscapes?

Cosgrove¹

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Habitat loss, fragmentation, and degradation are the leading causes of faunal population declines.Substantial effort has been invested in identifying how these landscape changes are related to population parameters. However, to effectively mitigate declines, we must understand the underlying mechanisms impacted by landscape change. Woodland-dependent avian insectivores seem particularly vulnerable, and decline at rates disproportionately greater than other foraging guilds. This pattern suggests that reduced food availability in less-wooded landscapes may be a contributing factor. However, the evidence supporting this hypothesis is sparse. I adopted a multidisciplinary approach to investigate the mechanisms driving population changes of an avian insectivore in highly-modified landscapes by integrating physiological indices with measures of prey availability and landscape structure. First, I presented a framework for conceptualising how the spatiotemporal scale of fragmentation influences the mechanisms impacting populations. I then used the eastern yellow robin (Eopsaltria australis) in the Brigalow Belt South bioregion of southern Queensland to test the importance of local and landscape factors on robin site occupancy, prey density, and robin condition. I also investigated whether an index of chronic stress could be used to predict changes to robin occurrence and identify potential threats to the population. I concluded this work by conducting a supplementary feeding experiment to determine whether food availability was causing the variation in robin condition. A pilot study conducted in the study region four years earlier found that robins were more physiologically stressed (had higher heterophil:lymphocyte ratios) in sites with less woodland in the surrounding landscape, but site occupancy was unrelated to woodland cover. Re-examining the same study system, I established that woodland cover was now the strongest predictor of iii occupancy. While woodland cover at a local scale (within 500 m) was important for robin persistence, woodland cover at a broader scale relevant to dispersal movements (within 5 km) was not. While my stress index could not accurately predict the precise locations of future extirpations, patterns of stress indices (birds were more stressed where woodland cover was lower) did foreshadow a change to the pattern of occurrence. Extirpations from sites with low levels of woodland cover were balanced by colonisations of more-wooded sites. Surprisingly, I found that arthropod prey density was greater at sites that had less surrounding woodland. This result was primarily driven by a large number of Formicidae (ants). However, Formicidae have low nutritional value and once they were excluded from the results, soil moisture, not woodland cover, became the primary determinant of arthropod density. I predicted that robin condition would be strongly associated with arthropod density, but this was not the case. Instead, robins had elevated stress levels at sites with apparently more-favourable...

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“…However, a key component of the analysis of landscapes, and the fields of landscape ecology and conservation biogeography, is the influence of temporal factors Bennett et al, 2006;Lindenmayer et al, 2008;Szabo et al, 2011;Wu, 2013;Kitzes & Harte, 2015). I touch on extinction debt in Chapter 4, when inferring potential mechanisms explaining regional differences in the observed effect of vegetation area on species richness.…”

Section: Key Implications For Applied Landscape Management 622mentioning

confidence: 99%

Implications of vegetation clearing biases for the interpretation of landscape-scale species-area relationships

Simmonds¹

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Vegetation clearing results in the loss of species from landscapes. Indeed, the area of remaining native vegetation is an important determinant of species richness in humanmodified mosaics. Of interest to ecologists and landscape managers is the effect of areathat is, how the number of species a landscape supports changes with the amount of native vegetation, as revealed by the shape and functional form of the species-area relationship. Understanding this is vital for guiding conservation interventions such as setting limits to vegetation clearing or establishing revegetation targets.Crucially though, it is not only vegetation area that affects patterns of species richness at the landscape level-so do environmental attributes such as soil properties and topography. Complicating the matter is the fact that these attributes tend to be correlated ii Second, I explored the extent to which the effect of native vegetation area on species richness differed in 100 km 2 landscapes categorised by attributes such as soil fertility, range in elevation or matrix land use. Using a case study of south-east Australian birds, Ifound that the shape of the species-area relationship varied substantially depending on whether landscapes were, for example, more-or less-topographically variable, or had higher or lower soil fertility. While threshold models depicting a point of sudden change in the effect of area emerged consistently, the amount of vegetation corresponding with observed thresholds differed considerably among landscape types. Therefore, aggregating and analysing species-area data from different landscape types is likely to misrepresent how species richness is affected by vegetation area. This will be exacerbated by clearing biases, because heavily cleared landscapes tend to be characterised by very different attributes to high cover landscapes. When data for the entire study extent were analysed, a remarkable degree of scaleinvariance was observed-namely, a threshold relationship with a change-point at approximately 30% vegetation cover. However, when data were analysed for two regional subsets of the overall dataset, the effect of vegetation area, and the factors moderating this relationship, were scale-dependent. Given this finding, observed thresholds can only reliably be used to guide landscape management at the scale and in the region where the relationship was observed.Finally, I evaluated the implications of accounting for clearing biases when using speciesarea relationships to guide conservation, focussing on a region of Australia undergoing rapid landscape transformation. I found that using observed thresholds from species-area models that do and do not account for landscape attributes yielded different outcomes for landscape-scale species richness conservation, given a scenario of future vegetation loss.Specifically, the number and location of landscapes that could be prioritised for conservation actions varied considerably depending on the species-area model used.This research demonstrates that the eff...

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Paying the extinction debt: woodland birds in the Mount Lofty Ranges, South Australia

Cited by 75 publications

References 31 publications

Towards modelling persistence of woodland birds: the role of genetics

Towards modelling persistence of woodland birds: the role of genetics

Why are woodland-dependent avian insectivore populations vulnerable to declines in highly-modified landscapes?

Implications of vegetation clearing biases for the interpretation of landscape-scale species-area relationships

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