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Spatial distribution of Vachellia karroo in Zimbabwean savannas (southern Africa) under a changing climate

  • Munyaradzi Davis Shekede
  • Amon Murwira
  • Mhosisi Masocha
  • Isaiah Gwitira
Original Article

Abstract

Climate change projections in southern Africa show a drier and a warmer future climate. It is not yet clear how these changes are going to affect the suitable habitat of bush encroacher woody species in southern African savannas. Maximum Entropy niche modelling technique was used to test the extent to which climate change is likely to affect the suitable habitat of Vachellia karroo in Zimbabwe based on six Global Climate Models (GCMs) from Coupled Model Intercomparison Project Phase 5 (CMIP5) and two Representative Concentration Pathways (RCPs) for the 2070s. An overlay analysis was then performed in a Geographic Information System based on the current and future bioclimatically suitable areas for the respective GCMs and RCPs. This was done to determine the potential effect of climate change on the focal species. Results show that temperature related variables are more important in explaining the spatial distribution of V. karroo than precipitation related variables. In addition, results indicate an overall increase in the modelled suitable habitat for V. karroo by the 2070s across the GCMs and RCPs considered in this study. Specifically, the suitable habitat of V. Karroo is projected to increase by a maximum of 57,594 km2 signifying a 69% increase from the current suitable habitat (83,674 km2). The suitable areas are projected to increase in eastern, western and south eastern parts of Zimbabwe. These results imply that improved understanding of the response of woody species to a changing climate is important for managing bush encroachment in savanna ecosystems.

Keywords

Climate change Global circulation models Habitat suitability MAXENT Vachellia karroo 

Notes

Acknowledgements

The authors wish to thank the National Herbarium and Botanic Garden for providing V. karroo species occurrence data.

References

  1. Akinwande MO, Hussaini GD, Agboola S (2015) Variance inflation factor: as a condition for the inclusion of suppressor variable(s) in regression analysis. Open J Stat 5:754–767.  https://doi.org/10.4236/ojs.2015.57075 CrossRefGoogle Scholar
  2. Aleman JC, Blarquez O, Gourlet-Fleury S, Bremond L, Favier C (2017) Tree cover in Central Africa: determinants and sensitivity under contrasted scenarios of global change. Sci Rep 7:41393.  https://doi.org/10.1038/srep41393 CrossRefPubMedPubMedCentralGoogle Scholar
  3. Angassa A (2014) Effects of grazing intensity and bush encroachment on herbaceous species and rangeland condition in southern Ethiopia. Land Degrad Dev 25:438–451.  https://doi.org/10.1002/ldr.2160 CrossRefGoogle Scholar
  4. Archer S, Schimel DS, Holland EA (1995) Mechanisms of shrubland expansion: land use, climate or CO2? Clim Change 29:91–99.  https://doi.org/10.1007/BF01091640 CrossRefGoogle Scholar
  5. Ay JS, Guillemot J, Martin-StPaul N, Doyen L, Leadley P (2017) The economics of land use reveals a selection bias in tree species distribution models. Global Ecol Biogeogr 26:65–77.  https://doi.org/10.1111/geb.12514 CrossRefGoogle Scholar
  6. Baldwin RA (2009) Use of maximum entropy modelling in wildlife research. Entropy 11:854–866.  https://doi.org/10.3390/e11040854 CrossRefGoogle Scholar
  7. Barnes RD, Filer DL, Milton SJ (1996) Acacia karroo:a monogram and annotated bibliography. University of Oxford, OxfordGoogle Scholar
  8. Bean WT, Robert S, Justin SB (2012) The effects of small sample size and sample bias on threshold selection and accuracy assessment of species distribution models. Ecography 35:250–258.  https://doi.org/10.1111/j.1600-0587.2011.06545.x CrossRefGoogle Scholar
  9. Beane NR, Rentch JS (2015) Using known occurrences to model suitable habitat for a rare forest type in west virginia under select climate change scenarios. Ecol Restor 33:178–189.  https://doi.org/10.2737/NRS-RP-23 CrossRefGoogle Scholar
  10. Beane NR, Rentch JS, Schuler TM (2013) Using maximum entropy modeling to identify and prioritize red spruce forest habitat in West Virginia. Research Paper NRS-23Google Scholar
  11. Buitenwerf R, Bond WJ, Stevens N, Trollope WSW (2012) Increased tree densities in South African savannas: > 50 years of data suggests CO2 as a driver. Glob Change Biol, FS 18:675–684.  https://doi.org/10.1111/j.1365-2486.2011.02561.x CrossRefGoogle Scholar
  12. Case MF, Staver AC (2017) Fire prevents woody encroachment only at higher-than-historical frequencies in a South African savanna. J Appl Ecol 54:955–962.  https://doi.org/10.1111/1365-2664.12805 CrossRefGoogle Scholar
  13. Craney TA, Surles JG (2002) Model-dependent variance inflation factor cutoff values. Qual Eng 14:391–403.  https://doi.org/10.1081/QEN-120001878 CrossRefGoogle Scholar
  14. De Wit M, Crookes D, Van Wilgen B (2001) Conflicts of interest in environmental management: estimating the costs and benefits of a tree invasion. Biol Invasions 3:167–178.  https://doi.org/10.1111/geb.12514 CrossRefGoogle Scholar
  15. Delire C, Ngomanda A, Jolly D (2008) Possible impacts of 21st century climate on vegetation in Central and West Africa. Glob Planet Change 64:3–15.  https://doi.org/10.1016/j.gloplacha.2008.01.008 CrossRefGoogle Scholar
  16. Devine AP, McDonald RA, Quaife T, Maclean IMD (2017) Determinants of woody encroachment and cover in African savannas. Oecologia 183:939–951.  https://doi.org/10.1007/s00442-017-3807-6 CrossRefPubMedPubMedCentralGoogle Scholar
  17. Dhlamini W (2010) Probabilistic spatio-temporal assessment of vegetation vulnerability to climate change in Swaziland. Glob Change Biol 17:1425–1441.  https://doi.org/10.1111/j.1365-2486.2010.02317.x CrossRefGoogle Scholar
  18. Elith J, Phillips SJ, Hastie T, Dudık M, Chee YE, Yates CJ (2011) A statistical explanation of MaxEnt for ecologists. Divers Distrib 17:43–57.  https://doi.org/10.1111/j.1472-4642.2010.00725.x CrossRefGoogle Scholar
  19. Evangelista A, Frate L, Carranza ML, Attorre F, Pelino G, Stanisci A (2016) Changes in composition, ecology and structure of high-mountain vegetation: a re-visitation study over 42 years. AoB Plants 8:plw004.  https://doi.org/10.1093/aobpla/plw004 CrossRefPubMedPubMedCentralGoogle Scholar
  20. Fandohan AB, Oduor AMO, Sode AI, Wu L, Cuni-Sanchez A, Assede E, Gouwakinnou GN (2015) Modeling vulnerability of protected areas to invasion by Chromolaena odorata under current and future climates.1. Ecosyst Health Sustain 1:1–12.  https://doi.org/10.1890/EHS15-0003.1 CrossRefGoogle Scholar
  21. Feng Z, Dyckmans J, Flessa H (2004) Effects of elevated carbon dioxide concentration on growth and N2 fixation of young Robinia pseudoacacia. Tree Physiol 24:323–330.  https://doi.org/10.1093/treephys/24.3.323 CrossRefPubMedGoogle Scholar
  22. Giannini A, Biasutti M, Held I, Sobel A (2008) A global perspective on African climate. Clim Change 90:359–383.  https://doi.org/10.1007/s10584-008-9396-y CrossRefGoogle Scholar
  23. Gottfried M, Pauli H, Futschik A, Akhalkatsi M, Barancok P, Benito Alonso JL, Coldea G, Dick J, Erschbamer B, Fernandez Calzado MR, Kazakis G, Krajci J, Larsson P, Mallaun M, Michelsen O, Moiseev D, Moiseev P, Molau U, Merzouki A, Nagy L, Nakhutsrishvili G, Pedersen B, Pelino G, Puscas M, Rossi G, Stanisci A, Theurillat J-P, Tomaselli M, Villar L, Vittoz P, Vogiatzakis I, Grabherr G (2012) Continent-wide response of mountain vegetation to climate change. Nat Clim Change 2:111–115.  https://doi.org/10.1038/nclimate1329 CrossRefGoogle Scholar
  24. Grossiord C, Sevanto S, Borrego I, Chan AM, Collins AD, Dickman LT, Hudson PJ, McBranch N, Michaletz ST, Pockman WT (2017) Tree water dynamics in a drying and warming world. Plant, Cell Environ.  https://doi.org/10.1111/pce.12991 Google Scholar
  25. Gwitira I, Murwira A, Shekede MD, Masocha M, Chapano C (2014) Precipitation of the warmest quarter and temperature of the warmest month are key to understanding the effect of climate change on plant species diversity in Southern African savannah. Afr J Ecol 52:209–216.  https://doi.org/10.1111/aje.12105 CrossRefGoogle Scholar
  26. Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005) Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25:1965–1978.  https://doi.org/10.1002/joc.1276 CrossRefGoogle Scholar
  27. Hounkpèvi A, Tosso F, Gbèmavo DSJC, Kouassi EK, Koné D, Kakaï RG (2016) Climate and potential habitat suitability for cultivation and in situ conservation of the black plum (Vitex doniana Sweet) in Benin, West Africa. Int J Agron Agric Res 8:67–80Google Scholar
  28. IPCC (2014) Climate Change 2014; impacts, adaptation, and vulnerability Part A; global and sectoral aspects. Contribution of working group II to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, CambridgeGoogle Scholar
  29. ITC (2002) Intergrated land and water information system (ILWIS). ITC, EnschedeGoogle Scholar
  30. Kgosikoma OE, Mogotsi K (2013) Understanding the causes of bush encroachment in Africa: the key to effective management of savanna grasslands. Tropical Grasslands. Forrajes Tropicales 1:215–219.  https://doi.org/10.17138/tgft(1)215-219 CrossRefGoogle Scholar
  31. Kgosikoma OE, Harvie BA (2012) Bush encroachment in relation to rangeland management systems and environmental conditions in Kalahari ecosystem of Botswana. Afr J Agric Res 7:2312–2319.  https://doi.org/10.5897/AJAR11.2374 CrossRefGoogle Scholar
  32. Kraaij T, Ward D (2006) Effects of rain, nitrogen, fire and grazing on tree recruitment and early survival in bush-encroached savanna, South Africa. Plant Ecol 186:235–246.  https://doi.org/10.1007/sl1258-006-9125-4 CrossRefGoogle Scholar
  33. Lehmann CER, Archibald SA, Hoffmann WA, Bond WJ (2011) Deciphering the distribution of the savanna biome. New Phytol 191:197–209.  https://doi.org/10.1111/j.1469-8137.2011.03689.x CrossRefPubMedGoogle Scholar
  34. Leitner M, Davies AB, Parr CL, Eggleton P, Robertson MP (2018) Woody encroachment slows decomposition and termite activity in an African savanna. Global Change Biol.  https://doi.org/10.1111/gcb.14118 Google Scholar
  35. Lenoir J, Svenning JC (2014) Climate-related range shifts—a global multidimensional synthesis and new research directions. Ecography 37:001–014.  https://doi.org/10.1111/ecog.00967 CrossRefGoogle Scholar
  36. Lesoli MS, Gxasheka M, Solomon TB, Moyo B (2013) Integrated plant invasion and bush encroachment management on Southern African Rangelands. In: Price AJ, Kelton JA (eds) Herbicides—current research and case studies in use. InTech, RijekaGoogle Scholar
  37. Lubestzky-Vilnai A, Ciol M, McCoy SW (2013a) Statistical analysis of clinical prediction rules for rehabilitation interventions: current state of literature. Arch Phys Med Rehabil 95:188–196CrossRefGoogle Scholar
  38. Lubestzky-Vilnai A, Ciol M, McCoy SW (2013b) Statistical analysis of clinical prediction rules for rehabilitation interventions: current state of literature. Arch Phys Med Rehabil 95:188–196.  https://doi.org/10.1016/j.apmr.2013.08.242 CrossRefGoogle Scholar
  39. Mapaura A, Timberlake J (2004) A checklist of Zimbabwean vascular plants Southern African Botanical Diversity Network Report No. 33 Sabonet. Pretoria and Harare: 9Google Scholar
  40. Marquardt DW (1970) Generalized inverses, ridge regression, biased linear estimation, and nonlinear estimation. Technometrics 12:591–612.  https://doi.org/10.1080/00401706.1970.10488699 CrossRefGoogle Scholar
  41. Midgley GF, Bond WJ (2015) Future of African terrestrial biodiversity and ecosystems under anthropogenic climate change. Nat Clim Change 5:823–829.  https://doi.org/10.1038/nclimate2753 CrossRefGoogle Scholar
  42. Midgley GF, Thuiller W (2011) Potential responses of terrestrial biodiversity in Southern Africa to anthropogenic climate change. Reg Environ Change 11:127–135.  https://doi.org/10.1007/s10113-010-0191-8 CrossRefGoogle Scholar
  43. Moise AF, Hudson DA (2008) Probabilistic predictions of climate change for Australia and southern Africa using the reliability ensemble average of IPCC CMIP3 model simulations. J Geophys Res Atmos 113:1–26.  https://doi.org/10.1029/2007JD009250 CrossRefGoogle Scholar
  44. Moleele NMR, Matheson W, Vanderpost C (2002) More woody plants? The status of bush encroachment in Botswana’s grazing areas. J Environ Manage 64:3–11.  https://doi.org/10.1006/jema.2001.0486 CrossRefPubMedGoogle Scholar
  45. Moss RH, Nakicenovic N, O’Neill BC (2008) Towards new scenarios for analysis of emissions, climate change, impacts, and response strategies. IPCC, GenevaGoogle Scholar
  46. Naimi B (2014) usdm: Uncertainty analysis for species distribution models, R package version 1.1-12. http://usdmr-forger-projectorgr-gisnetGoogle Scholar
  47. Nix HA (1986) A biogeographic analysis of Australian elapid snakes. In: Longmore R (ed) Atlas of Elapid Snakes of Australia. Australian Flora and Fauna Series Number 7. Australian Government Publishing Service, Canberra, pp 4–15Google Scholar
  48. O’Connor TG, Puttick JR, Hoffman MT (2014) Bush encroachment in southern Africa: changes and causes. Afr J Range For Sci 31:67–88.  https://doi.org/10.2989/10220119.2014.939996 CrossRefGoogle Scholar
  49. Oldeland J, Dorigo W, Wesuls D, Jürgens N (2010) Mapping bush encroaching species by seasonal differences in hyperspectral imagery. Remote Sens 2:1416–1438.  https://doi.org/10.3390/rs2061416 CrossRefGoogle Scholar
  50. Pauli H, Gottfried M, Dullinger S, Abdaladze O, Akhalkatsi M, Alonso JLB, Coldea G, Dick J, Erschbamer B, Calzado RF, Ghosn D, Holten JI, Kanka R, Kazakis G, Kollár J, Larsson P, Moiseev P, Moiseev D, Molau U, Mesa JM, Nagy L, Pelino G, Puşcaş M, Rossi G, Stanisci A, Syverhuset AO, Theurillat J-P, Tomaselli M, Unterluggauer P, Villar L, Vittoz P, Grabherr G (2012) Recent plant diversity changes on Europe’s mountain summits. Science 336:353–355.  https://doi.org/10.1126/science.1219033 CrossRefPubMedGoogle Scholar
  51. Pearson RG, Raxworthy CJ, Nakamura M, Townsend Peterson A (2007) Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar. J Biogeogr 34:102–117.  https://doi.org/10.1111/j.1365-2699.2006.01594.x CrossRefGoogle Scholar
  52. Pellegrini AF, Staver AC, Hedin LO, Charles-Dominique T, Tourgee A (2016) Aridity, not fire, favors nitrogen-fixing plants across tropical savanna and forest biomes. Ecology 97:2177–2183.  https://doi.org/10.1002/bes2.1261 CrossRefPubMedGoogle Scholar
  53. Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Model 190:231–259.  https://doi.org/10.1016/j.ecolmodel.2005.03.026 CrossRefGoogle Scholar
  54. Pradhan P (2016) Strengthening MaxEnt modelling through screening of redundant explanatory bioclimatic variables with variance inflation factor analysis. Researcher.  https://doi.org/10.7537/marsrsj08051605 Google Scholar
  55. Prather CM, Huynh A, Pennings SC (2017) Woody structure facilitates invasion of woody plants by providing perches for birds. Ecol Evol 7:8032–8039.  https://doi.org/10.1002/ece3.3314 CrossRefPubMedPubMedCentralGoogle Scholar
  56. Rogers A, Gibon Y, Stitt M, Morgan PB, Bernacchi CJ, Ort DR, Long SP (2006) Increased C availability at elevated carbon dioxide concentration improves N assimilation in a legume. Plant Cell Environ 29:1651–1658.  https://doi.org/10.1111/j.1365-3040.2006.01549.x CrossRefPubMedGoogle Scholar
  57. Rutherford MC, Midgley GF, Bond WJ, Powrie LW, Roberts R, Allsopp J (2000) Plant biodiversity: vulnerability and adaptation assessment. In: Kiker G (ed) Climate change impacts in Southern Africa. Report to the National Climate Change Committee Department of Environmental Affairs and Tourism, PretoriaGoogle Scholar
  58. Sankaran M, Ratnam J, Hanan NP (2004) Tree grass coexistence in savannas revisited insights from an examination of assumptions and mechanisms invoked in existing models. Ecol Lett 7:480–490.  https://doi.org/10.1111/j.1461-0248.2004.00596.x CrossRefGoogle Scholar
  59. Sankaran M, Ratnam J, Hanan NP (2008) Woody cover in African savannas: the role of resources, fire and herbivory. Global Ecol Biogeogr 17:236–245.  https://doi.org/10.1111/j.1461-0248.2004.00596.x CrossRefGoogle Scholar
  60. Scholes RJ (2015) Response of three semi-arid savannas on contrasting soils to the removal of the woody component. University of Witwatersrand, JohannesburgGoogle Scholar
  61. Scholes R, Archer S (1997) Tree-grass interactions in savannas. Annu Rev Ecol Syst 28:517–544.  https://doi.org/10.1146/annurev.ecolsys.28.1.517 CrossRefGoogle Scholar
  62. Shanahan TM, Hughen KA, McKay NP, Overpeck JT, Scholz CA, Gosling WD, Miller CS, Peck JA, King JW, Heil CW (2016) CO2 and fire influence tropical ecosystem stability in response to climate change. Sci Rep 6:29587CrossRefPubMedPubMedCentralGoogle Scholar
  63. Shekede MD, Murwira A, Masocha M, Zengeya FM (2016) Decadal changes in mean annual rainfall drive long-term changes in bush-encroached southern African savannas. Austral Ecol.  https://doi.org/10.1111/aec.12358 Google Scholar
  64. Skowno AL, Thompson MW, Hiestermann J, Ripley B, West AG, Bond WJ (2017) Woodland expansion in South African grassy biomes based on satellite observations (1990–2013): general patterns and potential drivers. Global Change Biol 23:2358–2369.  https://doi.org/10.1111/gcb.13529 CrossRefGoogle Scholar
  65. Stine RA (1995) The graphical interpretation of variance inflation factors. Am Stat 49(1):53–56.  https://doi.org/10.1080/00031305.1995.10476113 Google Scholar
  66. Tews J, Jeltsch F (2004) Modelling the impact of climate change on woody plant population dynamics in South African savanna. BMC Ecol 4:4–17.  https://doi.org/10.1186/1472-6785-4-17 CrossRefGoogle Scholar
  67. Tews J, Alexandra E, Sue JM, Florian J (2006) Linking a population model with an ecosystem model: assessing the impact of land use and climate change on savanna shrub cover dynamics. Ecol Model 195:219–228.  https://doi.org/10.1016/j.ecolmodel.2005.11.025 CrossRefGoogle Scholar
  68. Tietjen B, Jeltsch F, Zehe E, Classen N, Groengroeft A, Schiffers K, Oldeland J (2010) Effects of climate change on the coupled dynamics of water and vegetation in drylands. Ecohydrology 3:226–237.  https://doi.org/10.1002/Eco.70 Google Scholar
  69. Trisuart Y, Fajendra S, Kjelgren RK (2011) Plant Species vulnerability to climate change in peninsular Thailand. Appl Geogr 31(3):1106–1114.  https://doi.org/10.1016/j.apgeog.2011.02.007 CrossRefGoogle Scholar
  70. van Vuuren DP, Edmonds J, Kainuma M, Riahi K, Thomson A, Hibbard K, Hurtt GC, Kram T, Krey V, Lamarque J-F, Masui T, Meinshausen M, Nakicenovic N, Smith SJ, Rose SK (2011) The representative concentration pathways: an overview. Clim Change 109:5.  https://doi.org/10.1007/s10584-011-0148-z CrossRefGoogle Scholar
  71. Wang J, Xiao X, Qin Y, Doughty RB, Dong J, Zou Z (2018) Characterizing the encroachment of juniper forests into sub-humid and semi-arid prairies from 1984 to 2010 using PALSAR and Landsat data. Remote Sens Environ 205:166–179CrossRefGoogle Scholar
  72. Wigley B, Bond W, Hoffman M (2009) Bush encroachment under three contrasting land-use practices in a mesic South African savanna. Afr J Ecol 47:62–70.  https://doi.org/10.1111/j.1365-2028.2008.01051.x CrossRefGoogle Scholar
  73. Willis KJ, Bennett KD, Burrough SL, Macias-Fauria M, Tovar C (2013) Determining the response of African biota to climate change: using the past to model the future. Philos Trans R Soc B 368:20120491.  https://doi.org/10.1098/rstb.2012.0491 CrossRefGoogle Scholar
  74. Woodward FI (1987) Climate and plant distribution. Cambridge University Press, CambridgeGoogle Scholar
  75. Zelazowski P, Malhi Y, Huntingford C, Sitch S, Fisher JB (2011) Changes in the potential distribution of humid tropical forests on a warmer planet. Philos Trans R Soc A 369:137–160.  https://doi.org/10.1098/rsta.2010.0238 CrossRefGoogle Scholar
  76. Zhang L, Liu S, Sun P, Wang T, Wang G, Zhang X, Wang L (2015) Consensus forecasting of species distributions: the effects of Niche model performance and Niche properties. PLoS One 10:e0120056.  https://doi.org/10.1371/journal.pone.0120056 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© The Ecological Society of Japan 2018

Authors and Affiliations

  • Munyaradzi Davis Shekede
    • 1
  • Amon Murwira
    • 1
  • Mhosisi Masocha
    • 1
  • Isaiah Gwitira
    • 1
  1. 1.Department of Geography and Environmental ScienceUniversity of ZimbabweHarareZimbabwe

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