2020
DOI: 10.1007/s10531-020-01994-8
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Differential responses of heather and red grouse to long-term spatio-temporal variation in sheep grazing

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Cited by 2 publications
(13 citation statements)
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“…Conversely, the relative evidence for the two models containing a buzzard effect increased (with biannual assessments, for instance, by the post‐breeding assessment in 2018 the combined weight of the two buzzard models was 0.88 versus 0.11 for the model with harrier effects only), which strongly favors the killing hypothesis over the scavenging one. The inclusion of habitat as a factor limiting pre‐breeding grouse density in three out of the seven models in each model set tested the hypothesis that habitat, either on its own (baseline + habitat model) or in combination with other factors (non‐protected predator + habitat model, buzzard + habitat model), was an important determinant of grouse numbers in the counted areas during the period of the study. Heather cover at Langholm fell by a third between 1997 and 2009 before starting to recover (Ludwig, Aebischer, Richardson, et al, 2020; Figure 3a), and superficially the counts of red grouse during the long‐term study (Figure 1) appeared to follow the same pattern. However, the two simple habitat models (baseline + habitat, NPP + habitat) were rapidly downweighted in the model comparison process across all three model sets (Figure 6).…”
Section: Discussionmentioning
confidence: 85%
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“…Conversely, the relative evidence for the two models containing a buzzard effect increased (with biannual assessments, for instance, by the post‐breeding assessment in 2018 the combined weight of the two buzzard models was 0.88 versus 0.11 for the model with harrier effects only), which strongly favors the killing hypothesis over the scavenging one. The inclusion of habitat as a factor limiting pre‐breeding grouse density in three out of the seven models in each model set tested the hypothesis that habitat, either on its own (baseline + habitat model) or in combination with other factors (non‐protected predator + habitat model, buzzard + habitat model), was an important determinant of grouse numbers in the counted areas during the period of the study. Heather cover at Langholm fell by a third between 1997 and 2009 before starting to recover (Ludwig, Aebischer, Richardson, et al, 2020; Figure 3a), and superficially the counts of red grouse during the long‐term study (Figure 1) appeared to follow the same pattern. However, the two simple habitat models (baseline + habitat, NPP + habitat) were rapidly downweighted in the model comparison process across all three model sets (Figure 6).…”
Section: Discussionmentioning
confidence: 85%
“…The non‐breeding‐season models predicted pre‐breeding counts (Dpret$$ {D}_{\mathrm{pre}}^t $$) as a function of the previous post‐breeding count (Dpostt1$$ {D}_{\mathrm{post}}^{t-1} $$), the bag density from fall shooting ( B t −1 ), and summer and winter survival (Ssad,Sw$$ {S}_s^{\mathrm{ad}},{S}_w $$; Appendix S1: Table S1). We structured models as basic “BIDE” (births, immigration, deaths, and emigration) models of population growth, although we ignored immigration and emigration because our study site was isolated from other grouse moors and regarded as effectively closed from a population dynamics perspective (Ludwig, Aebischer, Bubb, Roos, & Baines, 2018; Ludwig, Aebischer, Richardson, et al, 2020). In all years, demographic parameters derived from Langholm Moor were influenced by multiple factors whose effects we sought to evaluate (Figure 1).…”
Section: Methodsmentioning
confidence: 99%
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