Landscape Ecology

, Volume 34, Issue 11, pp 2631–2647 | Cite as

From the ground up: microhabitat use within a landscape context frames the spatiotemporal scale of settlement and vacancy dynamics in an endemic habitat specialist

  • Danielle K. WalkupEmail author
  • Wade A. Ryberg
  • Lee A. Fitzgerald
  • Toby J. Hibbitts
Research Article



Understanding how species are distributed throughout landscapes requires knowledge of the hierarchy of habitat selection made by individuals, the resulting spatiotemporal structure of demography, and the consequent dynamics of localized populations.


We examined how patterns of habitat use, settlement, and vacancy in an endemic habitat specialist, Sceloporus arenicolus (dunes sagebrush lizard), varied within the Mescalero Monahans Sandhills ecosystem.


We used a 4-year mark-recapture dataset to develop occupancy models that identified whether microhabitat or landscape scale best predicted S. arenicolus spatiotemporal habitat use, settlement, and vacancy, in both an undisturbed and disturbed landscape.


Our results showed areas of high quality habitat were used constantly and lower quality areas were used intermittently, but repeatedly, over time in the undisturbed landscape. Habitat use in the disturbed landscape was spatiotemporally unpredictable. Microhabitat variables characterizing dune landscape topography predicted probability of use in S. arenicolus, while landscape-scale variables predicted probabilities of settlement and vacancy. In the undisturbed landscape, future settlement was predicted by presence of S. arenicolus, a pattern consistent with fine-scale source-sink dynamics already described for this species.


Our results illustrate how spatially-discrete but temporally-linked areas should be conserved at fine spatiotemporal scales to secure persistence of S. arenicolus populations under variable environmental conditions. Disturbances to habitat continuity can disrupt individual movements and create inconsistently occupied habitat patches that appear to be unoccupied and thus are threatened by further disturbances.


Mescalero Monahans Sandhill ecosystem Fragmentation Habitat use Sceloporus arenicolus Ecological scaling Habitat specialist 



Big thanks to all our field technicians, without whom this work would not have happened: Connor Adams, Jonathon Bolton, Sarah Bord, Logan Ediger, Aubany Fields, Shelby Frizzell, Aleyda Galan, Ana Hernandez, Cameron Hodges, Daniel Lay, Timmy Songer, Brooke Tolson, Scott Wahlberg, and J.M. Weidler. Thanks to Megan Young for assistance and logistics in the field. This is publication number 1620 of the Biodiversity Research and Teaching Collections at Texas A&M University.


This study was funded by the Texas Comptroller of Public Accounts and the Texas A&M University’s College of Agriculture and Life Sciences Tom Slick Graduate Fellowship.

Compliance with ethical standards

Conflict of interest

All authors that they have no conflict of interest.

Supplementary material

10980_2019_909_MOESM1_ESM.docx (5.3 mb)
Supplementary material 1 (DOCX 5458 kb)


  1. Addicott JF, Aho JM, Antolin MF, Padilla DK, Richardson JS, Soluk DA (1987) Ecological neighborhoods: scaling environmental patterns. Oikos 49:340–346Google Scholar
  2. Augustin NH, Mugglestone MA, Buckland ST (1996) An autologistic model for the spatial distribution of wildlife. J Appl Ecol 33:339–347Google Scholar
  3. Betts MG, Diamond AW, Forbes GJ, Villiard M-A, Gunn JS (2006) The importance of spatial autocorrelation, extent and resolution in predicting forest bird occurrence. Ecol Model 191:197–224Google Scholar
  4. Betts MG, Rodenhouse NL, Sillett TS, Doran PJ, Holmes RT (2008) Dynamic occupancy models reveal within-breeding season movement up a habitat quality gradient by a migratory songbird. Ecography 31:592–600Google Scholar
  5. Blevins E, With KA (2011) Landscape context matters: local habitat and landscape effects on the abundance and patch occupancy of collared lizards in managed grasslands. Landscape Ecol 26:37–850Google Scholar
  6. Buckland ST, Burnham KP, Augustin NH (1997) Model selection: an integral part of inference. Biometrics 53:603–618Google Scholar
  7. Burnham KP, Anderson DR (2002) Model selection and multimodel inference: a practical information-theoretic approach, 2nd edn. Springer, New YorkGoogle Scholar
  8. Chammem M, Selmi S, Khorchani T, Nouira S (2012) Using a capture-recapture approach for modelling the detectability and distribution of Houbra Bustard in southern Tunisia. Bird Conserv Int 22:288–298Google Scholar
  9. Cornell KL, Donovan TM (2010) Scale-dependent mechanisms of habitat selection for a migratory passerine: an experimental approach. Auk 127:899–908Google Scholar
  10. Diffendorfer JE (1998) Testing models of source-sink dynamics and balanced dispersal. Oikos 81:417–433Google Scholar
  11. Efford MG, Dawson DK (2012) Occupancy in continuous habitat. Ecosphere 34:32Google Scholar
  12. EIA. 2017. Rankings: crude oil production, November 2016 (thousand barrels). U.S. Energy Information Administration (EIA). Accessed 25 Feb 2017
  13. Eriksson O (1996) Regional dynamics of plants: a review of evidence for remnant, source-sink and metapopulations. Oikos 77:248–258Google Scholar
  14. Fiske I, Chandler R (2011) Unmarked: an R package for fitting hierarchical models of wildlife occurrence and abundance. J Stat Softw 43:1–23Google Scholar
  15. Fitzgerald LA (2012) Finding and capturing reptiles. In: McDiarmid RW, Foster MS, Guyer C, Gibbons JW, Chernoff N (eds) Measuring and monitoring biological diversity: standard methods for reptiles. University of California Press, Berkeley, pp 77–88Google Scholar
  16. Fitzgerald LA, Painter CW (2009) Dunes sagebrush lizard. In: Jones L, Lovich R (eds) Lizards of the American Southwest. Rio Nuevo, Tucson, pp 198–201Google Scholar
  17. Fitzgerald LA, Painter CW, Sias DW, Snell HW (1997) The range, distribution and habitat of Sceloporus arenicolus in New Mexico. Final Report, New Mexico Department of Game and Fish, Santa Fe, New Mexico, USAGoogle Scholar
  18. Fitzgerald LA, Walkup D, Chyn K, Buchholtz E, Angeli N, Parker M (2018) The future for reptiles: advances and challenges in the Anthropocene. In: DellaSala D, Goldstein M (eds) Encyclopedia of the Anthropocene. Elsevier, Oxford, pp 163–174Google Scholar
  19. Frey SJK, Strong AM, McFarland KP (2012) The relative contribution of local habitat and landscape context to metapopulation processes: a dynamic occupancy modeling approach. Ecography 35:581–589Google Scholar
  20. Galley JE (1958) Oil and geology in the permian basin of Texas and New Mexico: North America. Habitat of Oil, AAPG special volume, pp 395–446Google Scholar
  21. González-Megías A, Gómez JM, Sánchez-Piñero F (2005) Regional dynamics of a patchily distributed herbivore along an altitudinal gradient. Ecol Entomol 30:706–713Google Scholar
  22. Gotelli NJ, Ellison AM (2004) A primer of ecological statistics. Sinauer Associates Inc., SunderlandGoogle Scholar
  23. Haggerty J, Gude PH, Delorey M, Rasker R (2014) Long-term effects of income specialization in oil and gas extraction: the U.S. West, 1980–2011. Energ Econ 45:186–195Google Scholar
  24. Hammer Ø, Harper DAT, Ryan PD (2001) PAST: paleontological statistics software package for education and data analysis. Palaeontol Electron 4:1–9Google Scholar
  25. Herse MR, Estey ME, Moore PJ, Sandercock BK, Boyle WA (2017) Landscape context drive breeding habitat selection by an enigmatic grassland songbird. Landscape Ecol 32:2351–2364Google Scholar
  26. Hibbitts TJ, Ryberg WA, Adams CS, Fields AM, Lay D, Young ME (2013) Microhabitat selection by a habitat specialist and generalist in both fragmented and unfragmented landscapes. Herpetol Conserv Bio 8:104–113Google Scholar
  27. Hibbitts TJ, Fitzgerald LA, Walkup DK, Ryberg WA (2017) Why didn’t the lizard cross the road? Dunes sagebrush lizards exhibit road-avoidance behavior. Wildlife Res 44:194–199Google Scholar
  28. Hurme E, Mönkkönen M, Reunanen P, Nikula A, Nivala V (2008) Temporal patch occupancy dynamics of the Siberian flying squirrel in a boreal forest landscape. Ecography 31:469–476Google Scholar
  29. Jetz W, Sekercioglu CH, Watson JEM (2008) Ecological correlates and conservation implications of overestimating species geographic ranges. Conserv Biol 22:110–119PubMedGoogle Scholar
  30. Krohne DT, Burgin AB (1990) The scale of demographic heterogeneity in a population of Peromyscus leucopus. Oecologia 82:97–101PubMedGoogle Scholar
  31. Laurencio LR, Fitzgerald LA (2010) Atlas of distribution and habitat of the dunes sagebrush lizard (Sceloporus arenicolus) in New Mexico. Texas Cooperative Wildlife Collection, Department of Wildlife and Fisheries Sciences, Texas A&M University, College Station. ISBN# 978-0-615-40937-5Google Scholar
  32. Leavitt DJ, Fitzgerald LA (2013) Disassembly of a dune-dwelling lizard community due to landscape fragmentation. Ecosphere 4:97Google Scholar
  33. Levin SA (1992) The problem of pattern and scale in ecology: the Robert H. MacArthur award lecture. Ecology 73:1943–1967Google Scholar
  34. MacKenzie DI, Nichols JD, Hines JE, Knutson MG, Franklin AB (2003) Estimating site occupancy, colonization, and local extinction when a species is detected imperfectly. Ecology 84:2200–2207Google Scholar
  35. Mazerolle, MJ (2016) AICcmodavg: model selection and multimodel inferences based on (Q)AIC(c). R package version 2.1-0.
  36. McClure CJW, Hill GE (2012) Dynamic versus static occupancy: how stable are habitat associations through a breeding season? Ecosphere 3(7):60Google Scholar
  37. McClure CJW, Rolek BW, Hill GE (2012) Predicting occupancy of wintering migratory birds: is microhabitat information necessary? Condor 114:482–490Google Scholar
  38. McGarigal K, Cushman SA, Ene E (2012) FRAGSTATS v4: spatial pattern analysis program for categorical and continuous maps. Computer software program produced by the authors at the University of Massachusetts, Amherst.
  39. Merriam G (1995) Movement in spatially divided populations: responses to landscape structure. In: Lidicker WZ Jr (ed) Landscape approaches in mammalian ecology and conservation. University of Minnesota Press, Minneapolis, pp 64–77Google Scholar
  40. Michael DR, Ikin K, Crane M, Okada S, Lindenmayer DB (2017) Scale-dependent occupancy patterns in reptiles across topographically different landscapes. Ecography 40:415–424Google Scholar
  41. Pierre JP, Wolaver BD, Labay BJ, LaDuc TJ, Duran CM, Ryberg WA, Hibbitts TJ, Andrews JR (2018) Comparison of recent oil and gas, wind energy, and other anthropogenic landscape alteration factors in Texas through 2014. Environ Manage 61:805–818PubMedGoogle Scholar
  42. R Core Team (2018) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
  43. Runge CA, Martin TG, Possingham HP, Willis SG, Fuller RA (2014) Conserving mobile species. Front Ecol Environ 12:395–402Google Scholar
  44. Ryberg WA, Fitzgerald LA (2015) Sand grain size composition influences subsurface oxygen diffusion and distribution of an endemic, psammophilic lizard. J Zool 295:116–121Google Scholar
  45. Ryberg WA, Fitzgerald LA (2016) Landscape composition, not connectivity, determines metacommunity structure across multiple scales. Ecography 39:932–941Google Scholar
  46. Ryberg WA, Hill MT, Lay D, Fitzgerald LA (2012) Observations on the nesting ecology and early life history of the Dunes Sagebrush Lizard (Sceloporus arenicolus). West N Am Nat 72:582–586Google Scholar
  47. Ryberg WA, Hill MT, Painter CW, Fitzgerald LA (2013) Landscape pattern determines neighborhood size and structure within a lizard population. PLoS ONE 8:e56856PubMedPubMedCentralGoogle Scholar
  48. Ryberg WA, Hill MT, Painter CW, Fitzgerald LA (2015) Linking irreplaceable landforms in a self-organizing landscape to sensitivity of population vital rates for an ecological specialist. Conserv Biol 29:888–898PubMedGoogle Scholar
  49. Sergio F, Newton I (2003) Occupancy as a measure of territory quality. J Anim Ecol 72:857–865Google Scholar
  50. Shaver GR (2005) Spatial heterogeneity: past, present, and future. In: Lovett GM, Turner MG, Jones CG, Weathers KC (eds) Ecosystem function in heterogeneous landscapes. Springer, New York, pp 443–449Google Scholar
  51. Smolensky NL, Fitzgerald LF (2011) Population variation in dune-dwelling lizards in response to patch size, patch quality, and oil and gas development. Southwest Nat 56:315–324Google Scholar
  52. Sozio G, Mortelliti A, Boccacci F, Ranchelli E, Battisti C, Boitani L (2013) Conservation of species occupying ephemeral and patchy habitats in agricultural landscapes: the case of the Eurasian reed warbler. Landscape Urban Plan 119:9–19Google Scholar
  53. Turner MG (1990) Spatial and temporal analysis of landscape patterns. Landscape Ecol 4:21–30Google Scholar
  54. Turner MG, Chapin FS (2005) Causes and consequences of spatial heterogeneity in ecosystem function. In: Lovett GM, Turner MG, Jones CG, Weathers KC (eds) Ecosystem function in heterogeneous landscapes. Springer, New York, pp 9–30Google Scholar
  55. Walkup DK, Leavitt DJ, Fitzgerald LA (2017) Effects of habitat fragmentation on population structure of dune-dwelling lizards. Ecosphere 8:e01729Google Scholar
  56. Walkup DK, Ryberg WA, Fitzgerald LA, Hibbitts TJ (2018) Occupancy and detection of an endemic habitat specialist, the dunes sagebrush lizard (Sceloporus arenicolus). Herpetol Conserv Biol 13(3):497–506Google Scholar
  57. Webb MH, Terauds A, Tulloch A, Bell P, Stojanovic D, Heinsohn R (2017) The importance of incorporating functional habitats into conservation planning for highly mobile species in dynamic systems. Conserv Biol 31:1018–1028PubMedGoogle Scholar
  58. Wiens JA, Stenseth NC, Van Horne B, Ims RA (1993) Ecological mechanisms and landscape ecology. Oikos 66:369–380Google Scholar
  59. Wolaver BD, Pierre JP, Ikonnikova SA, Andrews JR, McDaid G, Ryberg WA, Hibbitts TJ, Duran CM, Labay BJ, LaDuc TJ (2018a) An improved approach for forecasting ecological impacts from future drilling in unconventional shale oil and gas plays. Environ Manage 62:323–333PubMedGoogle Scholar
  60. Wolaver BD, Pierre JP, Labay BJ, LaDuc TJ, Duran CM, Ryberg WA, Hibbitts TJ (2018b) An approach for evaluating changes in land-use from energy sprawl and other anthropogenic activities with implications for biotic resource management. Environ Earth Sci 77:171Google Scholar
  61. Ye X, Wang T, Skidmore AK (2013a) Spatial pattern of habitat quality modulates population persistence in fragmented landscapes. Ecol Res 28:949–958Google Scholar
  62. Ye X, Skidmore AK, Wang T (2013b) Within-patch habitat quality determines the resilience of specialist species in fragmented landscapes. Landscape Ecol 28:135–147Google Scholar
  63. Young ME, Ryberg WA, Fitzgerald LA, Hibbitts TJ (2018) Fragmentation alters home range and movements of the dunes sagebrush lizard (Sceloporus arenicolus). Can J Zool 96:905–912Google Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Natural Resources Institute, Department of Wildlife and Fisheries SciencesTexas A&M UniversityCollege StationUSA
  2. 2.Natural Resources InstituteTexas A&M UniversityCollege StationUSA
  3. 3.Biodiversity, Research and Teaching Collection, Department of Wildlife and Fisheries SciencesTexas A&M UniversityCollege StationUSA
  4. 4.Biodiversity, Research and Teaching Collection, Natural Resources Institute, Department of Wildlife and Fisheries SciencesTexas A&M UniversityCollege StationUSA

Personalised recommendations