Using distribution models to test alternative hypotheses about a species’ environmental limits and recovery prospects

Anderson, Barbara J.; Arroyo, Beatriz; Collingham, Yvonne C.; Etheridge, Brian; Fernandez-de-Simon, Javier; Gillings, Simon; Gregory, Richard D.; Leckie, Fiona; Sim, Innes M.W.; Thomas, Chris D.; Travis, Justin M. J.; Redpath, Stephen M.

doi:10.1016/j.biocon.2008.10.036

Cited by 51 publications

(57 citation statements)

References 44 publications

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“…The 12 breeding pairs recorded in 2010 represent only c. 4% of the potential population size in England, implying that harriers are absent from most of their suitable range (Anderson et al 2009). Annual population monitoring of harriers in England suggests that numbers ranged from 12 and 24 territorial pairs between 2004 and 2010, with the majority of these pairs located in the Forest of Bowland Area of Outstanding Natural Beauty.…”

Section: )) Within Thementioning

confidence: 99%

“…Fielding et al 2011) to be updated to analyse national and regional changes in Hen Harrier abundance up to 2010 at a finer scale in relation to grouse moor management and muirburn intensity. Such models have used the extent and distribution of muirburn as a surrogate for grouse moor distribution (Anderson et al 2009, Fielding et al 2011, Amar et al 2011b, 2012. Anderson et al (2009) found the distribution of muirburn explained the discrepancy between recent Hen Harrier distribution (Gibbons et al 1993) and the distribution as would be predicted by climate and habitat suitability (Anderson et al 2009).…”

Section: )) Within Thementioning

confidence: 99%

“…A substantial body of research suggests that illegal persecution is the principle factor limiting Hen Harrier population growth in parts of the UK, particularly in areas where heather moorland is managed for driven Red Grouse Lagopus lagopus scoticus shooting (Etheridge et al 1997, Redpath & Thirgood 1997, Stott 1998, Redpath & Thirgood 1999, Holmes et al 2000, Summers et al 2003, Anderson et al 2009, Fielding et al 2011. Fielding et al (2011) estimated that in the absence of illegal persecution the Hen Harrier population in the UK could be as high as 2514-2653 pairs, more than three times the 2004 level.…”

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confidence: 99%

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The status of the Hen Harrier,Circus cyaneus, in the UK and Isle of Man in 2010

Hayhow

Eaton

Bladwell³

et al. 2013

Bird Study

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Section: )) Within Thementioning

confidence: 99%

Section: )) Within Thementioning

confidence: 99%

mentioning

confidence: 99%

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The status of the Hen Harrier,Circus cyaneus, in the UK and Isle of Man in 2010

Hayhow

Eaton

Bladwell³

et al. 2013

Bird Study

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“…Many recent uses of SDMs are to make two types of predictions of practical use to conservation: predictions of where species may be present but unrecorded (or indeed, where they might be found if human activities had not eliminated them [6]), and predictions of where species may be in the future as environmental change alters distributions [7]. The first predictions are essentially spatial interpolation and extrapolation, whereas the second uses a space for time substitution to make extrapolations into the future, based on projections of climate (and/or landuse) change.…”

Section: Introductionmentioning

confidence: 99%

Incorporating uncertainty in predictive species distribution modelling

Beale

Lennon

2012

Phil. Trans. R. Soc. B

251

232

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Motivated by the need to solve ecological problems (climate change, habitat fragmentation and biological invasions), there has been increasing interest in species distribution models (SDMs). Predictions from these models inform conservation policy, invasive species management and disease-control measures. However, predictions are subject to uncertainty, the degree and source of which is often unrecognized. Here, we review the SDM literature in the context of uncertainty, focusing on three main classes of SDM: niche-based models, demographic models and processbased models. We identify sources of uncertainty for each class and discuss how uncertainty can be minimized or included in the modelling process to give realistic measures of confidence around predictions. Because this has typically not been performed, we conclude that uncertainty in SDMs has often been underestimated and a false precision assigned to predictions of geographical distribution. We identify areas where development of new statistical tools will improve predictions from distribution models, notably the development of hierarchical models that link different types of distribution model and their attendant uncertainties across spatial scales. Finally, we discuss the need to develop more defensible methods for assessing predictive performance, quantifying model goodness-of-fit and for assessing the significance of model covariates.

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“…Ecological niche models have been widely applied in conservation biology to predict the potential distributions of species using correlative models that exploit a species-environment relationship (Anderson et al, 2009;Chefaoui et al, 2005;De Siqueira et al, 2009;Peterson, 2001;Raxworthy et al, 2007;Rushton et al, 2004;Titeux et al, 2007). Ecological niche models require occurrence records and a set of environmental predictor variables in order to predict a species' potential distribution (Gaubert et al, 2006;Peterson, 2001).…”

Section: Introductionmentioning

confidence: 99%