Appropriate spatial scale for potential woody cover observation in Texas savanna

  • Xuebin YangEmail author
  • Kelley Crews
  • Amy E. Frazier
  • Peter Kedron
Research Article



Potential woody cover, the upper bound of woody plant cover in savanna ecosystems, represents the end-point of woody plant encroachment and is highly relevant to the dynamics of savanna ecosystems.


This study aims to identify the appropriate spatial scale for potential woody cover observation in the savanna of central Texas, USA.


The upper bound of woody plant cover was modeled over the east–west precipitation gradient of Texas savanna, at four different spatial scales respectively (30 m, 100 m, 250 m, and 500 m).


The estimated upper bound of woody plant cover demonstrates a three-segment pattern across the precipitation gradient at all the four observation scales. The pattern begins with a low stable level and ends at a high stable level, with a linear transitional level in between. The magnitude of the upper bound under given precipitation conditions decreases with spatial scale, but stabilizes by 250 m scale.


A spatial scale between 250 and 500 m is recommended for potential woody cover observation. Water availability plays a more important role in limiting woody plant cover at larger spatial scales in savanna ecosystems. In addition, the scale dependency of upper bound woody plant cover is more pronounced in the arid region.


Savanna Potential woody cover Scale dependency Encroachment Precipitation gradient Quantile regression 



Authors were supported by a grant to Kelley Crews from the National Science Foundation (BCS-0964596), a grant to Peter Kedron from the National Science Foundation EPSCoR program (OIA-1301789), and a grant to Amy Frazier and Peter Kedron from the NSF (BCS-1561021). Many thanks to the editor and reviewers, whose comments and suggestions greatly improved this manuscript.


  1. Alofs KM, Fowler NL (2010) Habitat fragmentation caused by woody plant encroachment inhibits the spread of an invasive grass. J Appl Ecol 47:338–347CrossRefGoogle Scholar
  2. Alofs KM, Fowler NL (2013) Loss of native herbaceous species due to woody plant encroachment facilitates the establishment of an invasive grass. Ecology 94:751–760PubMedCrossRefPubMedCentralGoogle Scholar
  3. Anadón JD, Sala OE, Turner BL, Bennett EM (2014) Effect of woody-plant encroachment on livestock production in North and South America. Proc Natl Acad Sci USA 111:12948–12953PubMedCrossRefPubMedCentralGoogle Scholar
  4. Archer S (1989) Have southern Texas savannas been converted to woodlands in recent history? Am Nat 134:545–561CrossRefGoogle Scholar
  5. Blaser WJ, Shanungu GK, Edwards PJ, Olde Venterink H (2014) Woody encroachment reduces nutrient limitation and promotes soil carbon sequestration. Ecol Evol 4:1423–1438PubMedPubMedCentralCrossRefGoogle Scholar
  6. Brown JR, Archer S (1988) Woody plant seed dispersal and gap formation in a North American subtropical savanna woodland: the role of domestic herbivores. Vegetatio 73:73–80CrossRefGoogle Scholar
  7. Bucini G, Hanan NP (2007) A continental-scale analysis of tree cover in African savannas. Glob Ecol Biogeogr 16:593–605CrossRefGoogle Scholar
  8. Cade BS, Noon BR (2003) A gentle introduction to quantile regression for ecologists. Front Ecol Environ 1:412–420CrossRefGoogle Scholar
  9. Cade BS, Terrell JW, Schroeder RL (1999) Estimating effects of limiting factors with regression quantiles. Ecology 80:311–323CrossRefGoogle Scholar
  10. Chidumayo EN (2001) Climate and phenology of savanna vegetation in southern Africa. J Veg Sci 12:347–354CrossRefGoogle Scholar
  11. Creamer CA, Filley TR, Olk DC, Stott DE, Dooling V, Boutton TW (2013) Changes to soil organic N dynamics with leguminous woody plant encroachment into grasslands. Biogeochemistry 113(1–3):307–321CrossRefGoogle Scholar
  12. Cushman SA, Gutzweiler K, Evans JS, McGarigal K (2010) The gradient paradigm: a conceptual and analytical framework for landscape ecology. In: Cushman SA, Huettmann F (eds) Spatial complexity, informatics, and wildlife conservation. Springer, Tokyo, pp 83–108CrossRefGoogle Scholar
  13. de Dantas VL, Hirota M, Oliveira RS, Pausas JG (2016) Disturbance maintains alternative biome states. Ecol Lett 19:12–19CrossRefGoogle Scholar
  14. DiMiceli CM, Carroll ML, Sohlberg RA, Huang C, Hansen MC, Townshend JRG (2017) Annual global automated MODIS vegetation continuous fields (MOD44B) at 250 m spatial resolution for data years beginning day 65, 2000–2010, collection 5 percent tree cover. University of Maryland, College ParkGoogle Scholar
  15. Doll JC (2011) Predicting biological impairment from habitat assessments. Environ Monit Assess 182:259–277PubMedCrossRefPubMedCentralGoogle Scholar
  16. Fensham RJ, Fairfax RJ, Archer SR (2005) Rainfall, land use and woody vegetation cover change in semi-arid Australian savanna. J Ecol 93:596–606CrossRefGoogle Scholar
  17. Fernandez-Illescas CP, Rodriguez-Iturbe I (2003) Hydrologically driven hierarchical competition–colonization models: the impact of interannual climate fluctuations. Ecol Monogr 73:207–222CrossRefGoogle Scholar
  18. Fornaroli R, Cabrini R, Sartori L, Marazzi F, Vracevic D, Mezzanotte V, Annala M, Canobbio S (2015) Predicting the constraint effect of environmental characteristics on macroinvertebrate density and diversity using quantile regression mixed model. Hydrobiologia 742(1):153–167CrossRefGoogle Scholar
  19. Fowler NL, Simmons MT (2009) Savanna dynamics in central Texas: just succession? Appl Veg Sci 12:23–31CrossRefGoogle Scholar
  20. Frazier AE (2014) A new data aggregation technique to improve landscape metric downscaling. Landsc Ecol 29:1261–1276CrossRefGoogle Scholar
  21. Frazier AE, Kedron P (2017) Comparing forest fragmentation in Eastern US forests using patch-mosaic and gradient surface models. Ecol Inf 41:108–115CrossRefGoogle Scholar
  22. Frost CC, Walker J, Peet RK (1986) Fire-dependent savannas and prairies of the Southeast: original extent, preservation status, and management problems. In: Kulhavy DL, Conner RN (eds) Wilderness and natural areas in the eastern United States: a management challenge. Stephen F Austin State University, School of Forestry, Center for Applied Studies, Nacogdoches, TX, pp 348–357Google Scholar
  23. Gillson L (2004) Evidence of hierarchical patch dynamics in an east African savanna? Landsc Ecol 19:883–894CrossRefGoogle Scholar
  24. González AV (2010) Dynamics of woody plant encroachment in Texas savannas: density dependence, environmental heterogeneity, and spatial patternsGoogle Scholar
  25. Goodman R, Kish L (1950) Controlled selection—a technique in probability sampling. J Am Stat Assoc 45:350–372Google Scholar
  26. Grace J, José JS, Meir P, Miranda HS, Montes RA (2006) Productivity and carbon fluxes of tropical savannas. J Biogeogr 33(3):387–400CrossRefGoogle Scholar
  27. Greenberg JA, Santos MJ, Dobrowski SZ, Vanderbilt VC, Ustin SL (2015) Quantifying environmental limiting factors on tree cover using geospatial data. PLoS ONE 10(2):e0114648PubMedPubMedCentralCrossRefGoogle Scholar
  28. Higgins SI, Bond WJ, Trollope WS (2000) Fire, resprouting and variability: a recipe for grass–tree coexistence in savanna. J Ecol 88:213–229CrossRefGoogle Scholar
  29. Homer C, Dewitz J, Yang L, Jin S, Danielson P, Xian G, Coulston J, Herold N, Wickham J, Megown K (2015) Completion of the 2011 National Land Cover Database for the conterminous United States–representing a decade of land cover change information. Photogramm Eng Remote Sens 81(5):345–354Google Scholar
  30. House JI, Archer S, Breshears DD, Scholes RJ (2003) Conundrums in mixed woody–herbaceous plant systems. J Biogeogr 30:1763–1777CrossRefGoogle Scholar
  31. Koenker R (2005) Quantile regression. Cambridge University Press, New YorkCrossRefGoogle Scholar
  32. Koenker R, Bassett G Jr (1978) Regression quantiles. Econometrica 46:33–50CrossRefGoogle Scholar
  33. Kothari CR (2004) Research methodology: methods and techniques. New Age International, New DelhiGoogle Scholar
  34. Li Q, Staver AC, Weinan E, Levin SA (2019) Spatial feedbacks and the dynamics of savanna and forest. Theor Ecol 12(2):237–262CrossRefGoogle Scholar
  35. Lyons RK, Owens MK, Machen RV (2009) Juniper biology and management in Texas. Texas FARMER Collection, College StationGoogle Scholar
  36. Manning AD, Lindenmayer DB, Nix HA (2004) Continua and Umwelt: novel perspectives on viewing landscapes. Oikos 104:621–628CrossRefGoogle Scholar
  37. McGarigal K, Cushman S, Regan C (2005) Quantifying terrestrial habitat loss and fragmentation: a protocol. University of Massachusetts, Department of Natural Resources Conservation, Amherst, MA. 113 pGoogle Scholar
  38. Meyer KM, Wiegand K, Ward D (2009) Patch dynamics integrate mechanisms for savanna tree–grass coexistence. Basic Appl Ecol 10:491–499CrossRefGoogle Scholar
  39. Mishra NB, Crews KA (2014) Estimating fractional land cover in semi-arid central Kalahari: the impact of mapping method (spectral unmixing vs. object-based image analysis) and vegetation morphology. Geocarto Int 29:860–877CrossRefGoogle Scholar
  40. Mistry J, Beradi A (2014) World savannas: ecology and human use. Routledge, LondonCrossRefGoogle Scholar
  41. Mitchard ET, Saatchi SS, Lewis SL, Feldpausch TR, Woodhouse IH, Sonké B, Rowland C, Meir P (2011) Measuring biomass changes due to woody encroachment and deforestation/degradation in a forest–savanna boundary region of central Africa using multi-temporal L-band radar backscatter. Remote Sens Environ 115(11):2861–2873CrossRefGoogle Scholar
  42. Nassiuma DK (2000) Survey sampling: theory and methods. University of Nairobi press, NairobiGoogle Scholar
  43. Nobre CA, Borma LDS (2009) ‘Tipping points’ for the Amazon forest. Curr Opin Environ Sustain 1:28–36CrossRefGoogle Scholar
  44. Oliveras I, Malhi Y (2016) Many shades of green: the dynamic tropical forest–savannah transition zones. Philos Trans R Soc B 371:20150308CrossRefGoogle Scholar
  45. Pachauri RK, Allen MR, Barros VR, Broome J, Cramer W, Christ R, Church JA, Clarke L, Dahe Q, Dasgupta P, Dubash NK (2014) Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the fifth assessment report of the Intergovernmental Panel on Climate Change. IPCCGoogle Scholar
  46. Paolucci LN, Schoereder JH, Brando PM, Andersen AN (2017) Fire-induced forest transition to derived savannas: cascading effects on ant communities. Biol Cons 214:295–302CrossRefGoogle Scholar
  47. Poulter B, Frank D, Ciais P, Myneni RB, Andela N, Bi J, Broquet G, Canadell JG, Chevallier F, Liu YY, Running SW (2014) Contribution of semi-arid ecosystems to interannual variability of the global carbon cycle. Nature 509(7502):600PubMedCrossRefPubMedCentralGoogle Scholar
  48. Ramankutty N, Foley JA (1999) Estimating historical changes in global land cover: croplands from 1700 to 1992. Global Biogeochem Cycles 13:997–1027CrossRefGoogle Scholar
  49. Ratajczak Z, Nippert JB, Collins SL (2012) Woody encroachment decreases diversity across North American grasslands and savannas. Ecology 93:697–703PubMedCrossRefPubMedCentralGoogle Scholar
  50. Riitters K, Costanza JK, Buma B (2017) Interpreting multiscale domains of tree cover disturbance patterns in North America. Ecol Ind 80:147–152CrossRefGoogle Scholar
  51. Rodriguez-Iturbe I, Chen Z, Stave AC, Levin SA (2019) Tree clusters in savannas result from islands of soil moisture. Proc Natl Acad Sci USA 116:6679–6683PubMedCrossRefPubMedCentralGoogle Scholar
  52. Sala OE, Parton WJ, Joyce LA, Lauenroth WK (1988) Primary production of the central grassland region of the United States. Ecology 69:40–45CrossRefGoogle Scholar
  53. Sala OE, Chapin FS, Armesto JJ, Berlow E, Bloomfield J, Dirzo R, Huber-Sanwald E, Huenneke LF, Jackson RB, Kinzig A, Leemans R (2000) Global biodiversity scenarios for the year 2100. Science 287(5459):1770–1774PubMedCrossRefPubMedCentralGoogle Scholar
  54. Salazar A, Goldstein G, Franco AC, Miralles-Wilhelm F (2011) Timing of seed dispersal and dormancy, rather than persistent soil seed-banks, control seedling recruitment of woody plants in Neotropical savannas. Seed Sci Res 21:103–116CrossRefGoogle Scholar
  55. 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 7:480–490CrossRefGoogle Scholar
  56. Sankaran M, Hanan NP, Scholes RJ, Ratnam J, Augustine DJ, Cade BS, Gignoux J, Higgins SI, Le Roux X, Ludwig F, Ardo J (2005) Determinants of woody cover in African savannas. Nature 438(7069):846–849PubMedCrossRefPubMedCentralGoogle Scholar
  57. Sankaran M, Ratnam J, Hanan N (2008) Woody cover in African savannas: the role of resources, fire and herbivory. Glob Ecol Biogeogr 17:236–245CrossRefGoogle Scholar
  58. Schmid JA (1969) The wild landscape of the Edwards Plateau of south central Texas: a study of developing livelihood patterns and ecological change. PhD Thesis, University of ChicagoGoogle Scholar
  59. Scholes RJ, Archer SR (1997) Tree-grass interactions in savannas. Annu Rev Ecol Syst 28(1):517–544CrossRefGoogle Scholar
  60. Sexton JO, Song X-P, Feng M, Noojipady P, Anand A, Huang C, Kim DH, Collins KM, Channan S, DiMiceli C, Townshend JR (2013) Global, 30-m resolution continuous fields of tree cover: landsat-based rescaling of MODIS vegetation continuous fields with lidar-based estimates of error. Int J Digital Earth 6(5):427–448CrossRefGoogle Scholar
  61. Solbrig OT, Medina E, Silva JF (2013) Biodiversity and savanna ecosystem processes: a global perspective. Springer Science & Business Media, BerlinGoogle Scholar
  62. Staver AC, Archibald S, Levin SA (2011) The global extent and determinants of savanna and forest as alternative biome states. Science 334:230–232PubMedCrossRefPubMedCentralGoogle Scholar
  63. Staver AC, Asner GP, Rodriguez-Iturbe I, Levin SA, Smit IPJ (2019) Spatial patterning among savanna trees in high-resolution, spatially extensive data. Proc Natl Acad Sci USA 116(22):10681–10685PubMedCrossRefPubMedCentralGoogle Scholar
  64. Stevens N, Lehmann CE, Murphy BP, Durigan G (2017) Savanna woody encroachment is widespread across three continents. Glob Change Biol 23:235–244CrossRefGoogle Scholar
  65. Taylor CA Jr (2008) Ecological consequences of using prescribed fire and herbivory to manage Juniperus encroachment. In: Van Auken OW (ed) Western North American Juniperus Communities. Springer, New York, pp 239–252CrossRefGoogle Scholar
  66. Tjørve KM, Tjørve E (2017) The use of Gompertz models in growth analyses, and new Gompertz-model approach: an addition to the Unified-Richards family. PLoS ONE 12:e0178691PubMedPubMedCentralCrossRefGoogle Scholar
  67. Turner MG, Gardner RH, O’neill RV (2001) Landscape ecology in theory and practice. Springer, BerlinGoogle Scholar
  68. Van Auken OW (2009) Causes and consequences of woody plant encroachment into western North American grasslands. J Environ Manag 90:2931–2942CrossRefGoogle Scholar
  69. Van Wijk MT, Rodriguez-Iturbe I (2002) Tree-grass competition in space and time: insights from a simple cellular automata model based on ecohydrological dynamics. Water Resour Res 38:1179Google Scholar
  70. Walter H, Mueller-Dombois D (1971) Ecology of tropical and subtropical vegetation. Oliver & Boyd, EdinburghGoogle Scholar
  71. Wiegand K, Saltz D, Ward D (2006) A patch-dynamics approach to savanna dynamics and woody plant encroachment–insights from an arid savanna. Perspect Plant Ecol Evol Syst 7:229–242CrossRefGoogle Scholar
  72. Wiens JA (1989) Spatial scaling in ecology. Funct Ecol 3:385–397CrossRefGoogle Scholar
  73. Wu J (2007) Scale and scaling: a cross-disciplinary perspective. Key topics in landscape ecology. Cambridge University Press, Cambridge, pp 115–142CrossRefGoogle Scholar
  74. Wu J, Hobbs R (2002) Key issues and research priorities in landscape ecology: an idiosyncratic synthesis. Landsc Ecol 17:355–365CrossRefGoogle Scholar
  75. Yang X (2019) Woody plant cover estimation in Texas savanna from MODIS products. Earth Interact. CrossRefGoogle Scholar
  76. Yang X, Crews K (2019a) Fractional woody cover mapping of Texas savanna at landsat scale. Land 8:9CrossRefGoogle Scholar
  77. Yang X, Crews K (2019b) Applicability analysis of MODIS tree cover product in Texas savanna. Int J Appl Earth Obs Geoinf 81:186–194CrossRefGoogle Scholar
  78. Yang X, Crews KA, Yan B (2016) Analysis of the pattern of potential woody cover in Texas savanna. Int J Appl Earth Obs Geoinf 52:527–531CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of Plant PathologyKansas State UniversityManhattanUSA
  2. 2.Department of Geography and the EnvironmentThe University of Texas at AustinAustinUSA
  3. 3.Spatial Analysis Research Center (SPARC), School of Geographical Sciences and Urban Planning, Arizona State UniversityTempeUSA

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