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Estimating conservation metrics from atlas data: the case of southern African endemic birds

  • ALAN T. K. LEE (a1) (a2), RES ALTWEGG (a3) (a4) and PHOEBE BARNARD (a1) (a2) (a4)


The robust assessment of conservation status increasingly requires population metrics for species that may be little-researched, with no prospect of immediate improvement, but for which citizen science atlas data may exist. We explore the potential for bird atlas data to generate population metrics of use in red data assessment, using the endemic and near-endemic birds of southern Africa. This region, defined here as South Africa, Lesotho and Swaziland, is home to a large number of endemic bird species and an active atlas project. The Southern African Bird Atlas Projects (SABAP) 1 and 2 are large-scale citizen science data sets, consisting of hundreds of thousands of bird checklists and > 10 million bird occurrence records on a grid across the subcontinent. These data contain detailed information on species’ distributions and population change. For conservationists, metrics that guide decisions on the conservation status of a species for red listing can be obtained from SABAP, including range size, range change, population change, and range connectivity (fragmentation). We present a range of conservation metrics for these bird species, focusing on population change metrics together with an associated statistical confidence metric. Population change metrics correlate with change metrics calculated from dynamic occupancy modelling for a set of 191 common species. We identify four species with neither international nor local threatened status, yet for which bird atlas data suggest alarming declines, and two species with threatened status for which our metrics suggest could be reconsidered. A standardised approach to deciding the conservation status of a species is useful so that charismatic or flagship species do not receive disproportionate attention, although ultimately conservation status of any species must always be a consultative process.


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Allan, D. G., Harrison, J. A., Navarro, R., van Wilgen, B. W. and Thompson, M. W. (1997) The impact of commercial afforestation on bird populations in Mpumalanga Province, South Africa—insights from bird-atlas data. Biol. Conserv. 79: 173185.
Altwegg, R., Wheeler, M. and Erni, B. (2008) Climate and the range dynamics of species with imperfect detection. Biol. Lett. 4: 581584.
Amar, A., Redpath, S., Sim, I. and Buchanan, G. (2010) Spatial and temporal associations between recovering populations of common raven Corvus corax and British upland wader populations. J. Appl. Ecol. 47: 253262.
Amar, A., Cloete, D. and Whittington, M. (2015) Using independent nest survey data to validate changes in reporting rates of Martial Eagles between the Southern African Bird Atlas Project 1 and 2. Ostrich 87: 15.
Barnard, P. and Villiers, M. d. (2012) Biodiversity early warning systems: South African citizen scientists monitoring change. Pretoria, South Africa: South African National Biodiversity Institute.
Bled, F., Nichols, J. D. and Altwegg, R. (2013) Dynamic occupancy models for analyzing species’ range dynamics across large geographic scales. Ecol. Evol. 3: 48964909.
Bolger, D. T., Alberts, A. C. and Soule, M. E. (1991) Occurrence patterns of bird species in habitat fragments: sampling, extinction, and nested species subsets. Am. Nat. 137: 155166.
Bussière, E. M. S., Underhill, L. G. and Altwegg, R. (2015) Patterns of bird migration phenology in South Africa suggest northern hemisphere climate as the most consistent driver of change. Global Change Biol. 21: 21792190.
Cohn, J. P. (2008) Citizen science: Can volunteers do real research? BioScience 58: 192197.
Cooper, T. J. G., Wannenburgh, A. M. and Cherry, M. I. (in press) Atlas data indicate forest dependent bird species declines in South Africa. Bird Conserv. Internat. doi: 10.1017/S095927091600040X.
Cowling, R. (1995) Fynbos: South Africa’s unique floral kingdom. Cape Town, South Africa: University of Cape Town.
Cunningham, S., Madden, C., Barnard, P. and Amar, A. (2016) Electric crows: powerlines, climate change and the emergence of a native invader. Divers. Distrib. 22: 1729.
Cunningham, S. J., Kruger, A. C., Nxumalo, M. P. and Hockey, P. A. (2013) Identifying biologically meaningful hot-weather events using threshold temperatures that affect life-history. PloS ONE 8: e82492.
de Swardt, D. H. (2010) Gurney’s Sugarbirds in the Lydenburg area. Environment - People and Conservation in Africa 2: 4245.
Gaston, K. J. (2003) The structure and dynamics of geographic ranges. Oxford, UK: Oxford University Press.
Griffioen, P. (2001) Temporal changes in the distributions of bird species in eastern Australia. PhD thesis. Budoora, Victoria, Australia: La Trobe University.
Guillera-Arroita, G., Lahoz-Monfort, J. J., Elith, J., Gordon, A., Kujala, H., Lentini, P. E., McCarthy, M. A., Tingley, R. and Wintle, B. A. (2015) Is my species distribution model fit for purpose? Matching data and models to applications. Global Ecol. Biogeogr. 24: 276292.
Harebottle, D., Smith, N., Underhill, L. and Brooks, M. (2007) Southern African Bird Atlas Project 2: instruction manual. Cape Town, South AfricA: Animal Demography Unit, University of Cape Town.
Harrison, J., Underhill, L. and Barnard, P. (2008) The seminal legacy of the Southern African bird atlas project. South Afr. J. Sci. 104: 8284.
Hockey, P., Dean, W. R. J. and Ryan, P. (2005) Roberts birds of southern Africa, 7th edition. Johannesburg, South Africa: Trustees of the John Voelcker Bird Book Fund.
Huntley, B., Altwegg, R., Barnard, P., Collingham, Y. C. and Hole, D. G. (2012) Modelling relationships between species spatial abundance patterns and climate. Global Ecol. Biogeogr. 21: 668681.
Huntley, B. and Barnard, P. (2012) Potential impacts of climatic change on southern African birds of fynbos and grassland biodiversity hotspots. Divers. Distrib. 18: 769781.
Isaac, N. J., Strien, A. J., August, T. A., Zeeuw, M. P. and Roy, D. B. (2014) Statistics for citizen science: extracting signals of change from noisy ecological data. Methods Ecol. Evol. 5: 10521060.
IUCN Standards and Petitions Subcommittee (2014) Guidelines for using the IUCN Red List categories and criteria. Version 11. Prepared by the Standards and Petitions Subcommittee. Downloadable from
Kemp, A., Herholdt, J., Whyte, I. and Harrison, J. (2001) Birds of the two largest national parks in South Africa: a method to generate estimates of population size for all species and assess their conservation ecology. South Afr. J. Sci. 97: 393403.
Leader-Williams, N. and Dublin, H. T. (2000) Charismatic megafauna as ‘flagship species’. Priorities for the conservation of mammalian diversity: has the panda had its day: 53–81.
Lee, A. T. K. and Barnard, P. (2012) Endemic Fynbos avifauna: comparative range declines a cause for concern. Ornithol. Obs. 3: 1928.
Lee, A. T. K. and Barnard, P. (2014) Aspects of the ecology and morphology of the protea seedeater, Crithagra leucopterus, a little-known fynbos endemic. Afr. Zool. 49: 295300.
Lee, A. T. K. and Barnard, P. (2015) Endemic birds of the Fynbos biome: a conservation assessment and impacts of climate change. Bird Conserv. Internatn. 26: 5268.
Loftie-Eaton, M. (2014) Geographic range dynamics of South Africa’s bird species. South Africa: Department of Biological Sciences, University of Cape Town.
Lotz, C., Allan, D., Bowie, R., Chittenden, H., Cohen, C., Dowsett, B., Gibbon, G., Hardaker, T., Marais, E., Peacock, F., Retief, E., Ryan, P., Smit-Robinson, H. and Taylor, M. (2014) BirdLife South Africa checklist of birds in South Africa. Available at:, BirdLife South Africa.
MacKenzie, D. I., Nichols, J., Royle, J., Pollock, K., Bailey, L. and Hines, J. (2006) Occupancy estimation and modeling, San Diego, California, USA: Academic Press.
Péron, G. and Altwegg, R. (2015a) Twenty-five years of change in southern African passerine diversity: nonclimatic factors of change. Global Change Biol. 21: 33473355.
Péron, G. and Altwegg, R. (2015b) The abundant centre syndrome and species distributions: insights from closely related species pairs in southern Africa. Global Ecol. Biogeogr. 24: 215225.
Péron, G. and Altwegg, R. (2015c) Low bird diversity in the Fynbos plant diversity hotspot: Quaternary legacies in the current distributions of passerine birds. Ecography: doi: 10.1111/ecog.01176.
R Core Team (2015) R: A language and environment for statistical computing . Vienna, Austria: R Foundation for Statistical Computing. URL
Robertson, A., Simmons, R. E., Jarvis, A. M. and Brown, C. J. (1995) Can bird atlas data be used to estimate population size? A case study using Namibian endemics. Biol. Conserv. 71: 8795.
Robertson, M. P., Cumming, G. S. and Erasmus, B. F. N. (2010) Getting the most out of atlas data. Divers. Distrib. 16: 363375.
Royle, J. A. and Nichols, J. D. (2003) Estimating abundance from repeated presence-absence data or point counts. Ecology 84: 777790.
Taylor, M. R., Peacock, D. S. and Wanless, R. M. (2015) The Eskom Red Data Book of birds of South Africa, Lesotho and Swaziland, Johannesburg, South Africa: BirdLife South Africa.
Underhill, L. and Bradfield, D. (1998) Introstat. Cape Town, South Africa: Juta and Company Ltd.
Underhill, L. G. and Brooks, M. (2014) Preliminary summary of changes in bird distributions between the first and second Southern African bird atlas projects (SABAP1 AND SABAP2). Ornithol. Obs. 5: 258293.
Walther, B. A. and Niekerk, A. (2014) Effects of climate change on species turnover and body mass frequency distributions of South African bird communities. Afr. J. Ecol. 53: 2535.

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Estimating conservation metrics from atlas data: the case of southern African endemic birds

  • ALAN T. K. LEE (a1) (a2), RES ALTWEGG (a3) (a4) and PHOEBE BARNARD (a1) (a2) (a4)


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