Appendix 1: Sources and references for vulnerability assessment
1.1 Evidence for exposure (references)
1.1.1 Current impacts attributed to climate change:
Great Skua 1 - Hotter summers result in increased heat stress in adults and chicks. Adults more frequently desert the nest to thermoregulate, which results in higher chick mortality from both direct and indirect causes (see increase in avian predation).- Oswald, Stephen A., et al. “Heat stress in a high-latitude seabird: effects of temperature and food supply on bathing and nest attendance of great skuas Catharacta skua.” Journal of Avian Biology 39.2 (2008): 163-169. In hot summers nesting adults need to bath more regularly to thermoregulate. This results in lower fledgling rates as chicks are unattended for longer and left vulnerable to heat stress and predation. Study was conducted on Foula, Shetlands.
- Oswald, Stephen A., et al. “Heat stress in a high-latitude seabird: effects of temperature and food supply on bathing and nest attendance of great skuas Catharacta skua.” Journal of Avian Biology 39.2 (2008): 163-169. In hot summers nesting adults need to bath more regularly to thermoregulate. This results in lower fledgling rates as chicks are unattended for longer and left vulnerable to heat stress and predation. Study was conducted on Foula, Shetlands.
- Oswald, Stephen A., et al. “Heat stress in a high-latitude seabird: effects of temperature and food supply on bathing and nest attendance of great skuas Catharacta skua.” Journal of Avian Biology 39.2 (2008): 163-169. Lower food availability (particularly sandeels) means adults must forage for longer, resulting in the same problem as for heat stress: chicks are left unattended and vulnerable. Study on Foula, Shetlands.
- Descamps, Sébastien, et al. “Climate change impacts on wildlife in a High Arctic archipelago–Svalbard, Norway.” Global Change Biology 23.2 (2017): 490-502. Great skuas were first observed breeding on Svalbard in 1970, and their numbers have increased rapidly in recent years. This is most likely driven by range shifts in prey species and because of general warming of the climate.
- Virkkala, R. & Rajasärkkä, A. 2011: Northward density shift of bird species in boreal protected areas due to climate change. Boreal Env. Res. 16 (suppl. B): 2–13 Long-tailed skuas have drastically reduced in range and density in Finland due to climate change, density is now <50% of what it was in censuses carried out 1981–1999. Seems to be part of a range shift north. Exact mechanism unknown, probably related to prey availability or heat stress.
- Perkins, Allan, et al. “Combined bottom-up and top-down pressures drive catastrophic population declines of Arctic skuas in Scotland.” Journal of Animal Ecology 87.6 (2018): 1573-1586. Arctic skuas in Scotland are declining drastically, there are multiple potential causes behind this. One likely driver is the decline of other seabirds due to climate change, which are important sources of food for skuas (usually by stealing their prey). Study looks at multiple colonies across Shetlands and Orkney Islands.
- Perkins, Allan, et al. “Combined bottom-up and top-down pressures drive catastrophic population declines of Arctic skuas in Scotland.” Journal of Animal Ecology 87.6 (2018): 1573-1586. Great skuas are increasing in number and have swapped their diet from predominantly fish to predominantly predating other birds. Greater numbers of great skua lead to lower fledgling survival rate in arctic skuas. Study looks at multiple colonies across Shetlands and Orkney Islands.
- Dawson, Neil M., et al. “Interactions with Great Skuas Stercorarius skua as a factor in the long-term decline of an Arctic Skua Stercorarius parasiticus population.” Ibis 153.1 (2011): 143-153. Arctic skua range is contracting across the Shetlands as great skua populations grow and expand. The overall decline in Arctic skua seems to be driven by this and lower density of sandeels, and both patterns are partially driven by climate change.
1.1.2 Change in European range size between present day and 2100:
Using a species distribution model (SDM) we correlated species occurrence during the breeding season with a number of terrestrial and marine environmental variables. Species range data came from the European Breeding Bird Atlas (EBBA2) database. Present-day and 2100 terrestrial data were downloaded from the WorldClim database. We used data from the MRI-ESM2 general circulation model (GCM), which is a high-performing model over Europe. Present-day and 2100 marine data were downloaded from the Bio-Oracle database which averages predictions of marine variables from several different atmospheric-oceanic general circulation models (AOGCMS; for full details see Assis et al., 2017). For the map presented in the summary we used representative concentration pathway (RCP) 4.5, which is an “intermediate” emissions scenario. All data were at 5-minute resolution.
- For Great Skua, and Arctic Jaeger we included the following terrestrial variables: Mean temperature of the warmest month, precipitation during breeding season, isolation of landmass, area of landmass, distance to sea
- For Long-tailed Jaeger we included the following terrestrial variables: Mean temperature of the warmest month, precipitation during breeding season, distance to sea
- For Great Skua, and Arctic Jaeger we included the following marine variables: Sea surface temperature (during the winter), salinity, maximum chlorophyll concentration, bathymetry (depth and variance)
After running our model we generated a present-day map where every grid-cell is given a habitat suitability score between 0 and 1, where 1 is very suitable habitat and 0 is not at all suitable. We then compared this with a corresponding map built with 2100 data, and highlighted currently inhabitated areas where 1) suitability drops sharply (i.e. by more than 0.1) and 2) suitability drops below a probability threshold set by the model. Conversely we also highlighted areas where suitability rose sharply and above a given threshold. While a drop in habitat suitability is likely to result in population declines, it is not a certainty, and it does not mean that a population will be extinct in 2100 or that a population is doomed to extinction. With conservation action and careful management, along with changes in human behaviour, such declines may be mitigated or in some cases prevented. For a full explanation of the model see the accompanying ‘Methodology’ document.
Underlying data were downloaded from:- Keller, V., Herrando, S., Voríšek, P., Franch, M., Kipson, M., Milanesi, P., Martí, D., Anton, M., Klvanová, A., Kalyakin, M.V., Bauer, H.-G. & Foppen, R.P.B. (2020). European Breeding Bird Atlas 2: Distribution, Abundance and Change. European Bird Census Council & Lynx Edicions, Barcelona. Source of range data
- Fick, S. E., & Hijmans, R. J. (2017). Worldclim 2: New 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology. http://worldclim.org/version2. Source of present-day and 2100 terrestrial data.
- Assis, J., Tyberghein, L., Bosch, S., Verbruggen, H., Serrão, E. A., & De Clerck, O. (2018). Bio-ORACLE v2.0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277–284. https://doi.org/10.1111/geb.12693. Source of present-day and 2100 marine data
1.1.3 Changes in key prey species:
We first identified the key prey species for each species. This can be variable across a species range, but if available evidence suggested at least one major population is highly dependent on a particular prey species, then typically this species would be included. Lists of prey species were compiled from published sources, then verified and expanded following consultation with conservation practitioners. Afterwards we compiled current and projected maps of prey ranges to assess where key prey species may disappear in the near future. If any of the key species are predicted to vanish or drastically reduce in abundance in the current foraging range a given species, we marked this on the summary map. We used several sources to collate range information, but for preference we used data from COPERNICUS as they include projected abundance. For species where this was not available we used habitat suitability instead. In all cases we used RCP 4.5, which is an “intermediate” emissions scenario. For species in the COPERNICUS database we used the 0.6 maximum sustainable yield parameter, which assumes international co-operation to work towards fish-stock sustainability. Our assessment is therefore relatively conservative in terms of changes in prey species.
Great Skua key prey species: whiting (Merlangius merlangus), blue whiting (Micromesistius poutassou), haddock (Melanogrammus aeglefinus) and pout (Trisopterus esmarkii). Some populations rely heavily on predation of other seabirds (such as fulmars, kittiwakes and puffins) and on fishery discards. These were not included in our prey assessment. Prey species list was compiled from:- Jones, Trevor, et al. “Breeding performance and diet of Great Skuas Stercorarius skua and Parasitic Jaegers (Arctic Skuas) S. parasiticus on the west coast of Scotland.” Bird Study 55.3 (2008): 257-266.
- Votier, Stephen C., et al. “Predation by great skuas at a large Shetland seabird colony.” Journal of Applied Ecology 41.6 (2004): 1117-1128.
- Dekorte, J., and J. Wattel. “Food and breeding success of the long-tailed skua at Scoresby Sund, Northeast Greenland.” Ardea 76.1 (1988): 27-41.
- Andersson, Malte. “Population ecology of the long-tailed skua (Stercorarius longicaudus Vieill.).” The Journal of Animal Ecology (1976): 537-559.
- Phillips, R. A., R. W. G. Caldow, and R. W. Furness. “The influence of food availability on the breeding effort and reproductive success of Arctic Skuas Stercorarius parasiticus.” Ibis 138.3 (1996): 410-419.
- COPERNICUS. (2021). Fish abundance and catch data for the Northwest European Shelf and Mediterranean Sea from 2006 to 2098 derived from climate projections. https://doi.org/10.24381/cds.39c97304
- Kesner-Reyes, K., Kaschner, K., Kullander, S., Garilao, C., Barile, J., & Froese., R. (2019). AquaMaps: Predicted range maps for aquatic species. In R. Froese & D. Pauly (Eds.), FishBase. https://www.aquamaps.org
1.1.4 Climate change impacts outside of Europe
Long-tailed Jaeger Skuas have been heavily affected by climate change in Greenland, in particular due to lack of prey and increased predation due to other species prey-switching.- Schmidt, Niels M., et al. “Response of an arctic predator guild to collapsing lemming cycles.” Proceedings of the Royal Society B: Biological Sciences 279.1746 (2012): 4417-4422.
- Barraquand, Frédéric, et al. “Demographic responses of a site-faithful and territorial predator to its fluctuating prey: long-tailed skuas and arctic lemmings.” Journal of Animal Ecology 83.2 (2014): 375-387.
1.2 Sensitivity (references)
We used a list of candidate traits based on that in Foden & Young (2016) that indicate high sensitivity and identified which, if any, skuas possessed. In brief, we consulted published literature as well as expert knowledge and online databases such as Birdlife (http://datazone.birdlife.org/) and Birds of the World (https://birdsoftheworld.org), to assess whether skuas have either 1) Specialised habitat and/or microhabitat requirement 2) Environmental tolerances or thresholds (at any life stage) that are likely to be exceeded due to climate change 3) Dependence on environmental triggers that are likely to be disrupted by climate change, 4) Dependence on interspecific interactions that are likely to be disrupted by climate change or 5) High rarity.
For more detail and a full list of traits see:- Foden, W. B., & Young, B. E. (2016). IUCN SSC guidelines for assessing species’ vulnerability to climate change. Version 1.0 (Occasional paper of the IUCN Species Survival Commission No. 59)
1.3 Adaptive capacity (references)
We used a list of candidate traits based on that in Foden & Young (2016) that indicate adaptive capacity and identified which, if any, skuas possessed. In brief, we consulted published literature as well as expert knowledge and online databases such as Birdlife (http://datazone.birdlife.org/) and Birds of the World (https://birdsoftheworld.org), to assess whether skuas have either: 1) High phenotypic plasticity. 2) High dispersal ability or 3) High evolvability.
For more detail and a full list of traits see:- Foden, W. B., & Young, B. E. (2016). IUCN SSC guidelines for assessing species’ vulnerability to climate change. Version 1.0 (Occasional paper of the IUCN Species Survival Commission No. 59)