A suite of maps, showing how the ranges of the majority of bird species breeding in sub-Saharan Africa could be impacted by climate change, is made available here online.
These maps, depict modeled present-day and modeled projections of future species ranges approximating to four discrete time periods: present-day (based on the mean climate between 1970–2000), 2025 (a mean of climate projections for the period 2010–2039), 2055 (mean for 2040–2069) and 2085 (mean for 2070–2099).
The maps have been developed collaboratively by BirdLife International and Durham University with data provided by the Zoological Museum of the University of Copenhagen (see here) for ‘observed’ distributional data for all terrestrial bird species breeding in sub‐Saharan Africa. These were supplemented by additional point count data for species of the Albertine Rift, generously provided by the Wildlife Conservation Society
These ranges have been prepared for 1608 species, the entire breeding avifauna of sub-Saharan Africa, minus 71 species recorded from fewer than five grid cells, for which modeling was impractical.
The “climate envelope” of a species represents the association between its present-day distribution and current climatic variables. Future distributions are then estimated by projecting this relationship onto scenarios of climate change, making the assumption that current relationships between climate and distribution are retained (see e.g. Pearson & Dawson, 2003). As such, these maps represent the distribution of areas of potential climatic suitability for a species, rather than an explicit representation of each species realized distribution. In most cases however, there is likely to be a close relationship between the modeled distribution and the species ‘observed’ distribution.
The models are based on comprehensive distributional data for all terrestrial bird species breeding in sub‐Saharan Africa, provided by ‘observed’ distributional data for all terrestrial bird species breeding in sub‐Saharan Africa. The continental landmass south of latitude 20°N is divided into 1963 1° x 1° latitude‐longitude cells, of approximately 111km x 111km at the Equator. The modeled distribution of each species is then indicated by its modeled presence or absence in these cells.
Mean monthly temperature and precipitation data for sub-Saharan Africa were obtained from a global, freely available dataset (www.worldclim.org), while projections of future climate change were derived from three General Circulation Models (GCMs) included in the IPCC’s Third Assessment Report (all GCM data are available at www.ipcc-data.org).
However, the researchers note that the time‐scale for their projections is likely to prove conservative if the current CO2 emissions trajectory continues. Emissions growth rate since 2000 has been at the upper end (and has possibly even exceeded) the most fossil‐fuel intensive of the IPCC emissions scenarios (Raupach et al., 2007), with a projected temperature increase in the range of 2.4–6.4°C, in comparison to 1.4–3.8°C for the scenario used here. Should this trend continue, then it is likely that these projections for avian turnover and persistence for 2085 will be manifest on a shorter time‐scale, perhaps as early as 2055.
The reliability of climate-envelope models has been extensively evaluated over the past two decades. They have been successfully used to model non-native/invasive species (e.g. Beerling, Huntley & Bailey, 1995; Menendez et al., 2006), re-create historical shifts in species distributions (e.g. Araujo et al., 2005; Nogues-Bravo, 2009), and to detect consequent shifts in individual species’ population trends (e.g. (Green et al., 2008; Gregory et al., 2009). However, these models are also subject to a range of assumptions and there is an acknowledged need for their continued development, improvement and testing (e.g. Araujo & Luoto, 2007; Beale, Lennon & Gimona, 2008; Elith & Graham, 2009; Guisan & Thuiller, 2005; Hijmans & Graham, 2006; Kearney & Porter, 2009; Pearson et al., 2003; Pearson et al., 2006). Any map depicting a species modeled distribution therefore needs to be interpreted carefully and judiciously. We emphasize that the maps on this website represent modeled projections of the distributional changes that could occur under climate change, not predictions of what will occur. As such they should be used as a tool to help scientists, policy-makers and other stakeholders identify and address potential adaptation needs, but within an adaptive management and decision framework that includes other independent data sources on likely climate change impacts, and that explicitly recognizes the inherent uncertainties when addressing climate change.
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Beale, C.M., Lennon, J.J., & Gimona, A. (2008) Opening the climate envelope reveals no macroscale associations with climate in European birds. Proceedings of the National Academy of Sciences of the United States of America, 105, 14908-14912.
Beerling, D.J., Huntley, B., & Bailey, J.P. (1995) Climate and the Distribution of Fallopia-Japonica - Use of an Introduced Species to Test the Predictive Capacity of Response Surfaces. Journal of Vegetation Science, 6, 269-282.
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Green, R.E., Collingham, Y.C., Willis, S.G., Gregory, R.D., Smith, K.W., & Huntley, B. (2008) Performance of climate envelope models in retrodicting recent changes in bird population size from observed climatic change. Biology Letters, 4, 599-602.
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Guisan, A. & Thuiller, W. (2005) Predicting species distribution: offering more than simple habitat models. Ecology Letters, 8, 993-1009.
Hijmans, R.J. & Graham, C.H. (2006) The ability of climate envelope models to predict the effect of climate change on species distributions. Global Change Biology, 12, 2272-2281.
Kearney, M. & Porter, W. (2009) Mechanistic niche modelling: combining physiological and spatial data to predict species' ranges. Ecology Letters, 12, 334-350.
Menendez, R., Megias, A.G., Hill, J.K., Braschler, B., Willis, S.G., Collingham, Y., Fox, R., Roy, D.B., & Thomas, C.D. (2006) Species richness changes lag behind climate change. Proceedings of the Royal Society B-Biological Sciences, 273, 1465-1470.
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Pearson, R.G., Thuiller, W., Araujo, M.B., Martinez-Meyer, E., Brotons, L., McClean, C., Miles, L., Segurado, P., Dawson, T.P., & Lees, D.C. (2006) Model-based uncertainty in species range prediction. Journal of Biogeography, 33, 1704-1711.
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