Advertisement

Landscape Ecology

, Volume 26, Issue 3, pp 371–379 | Cite as

Connectivity of agroecosystems: dispersal costs can vary among crops

  • Bradley J. Cosentino
  • Robert L. Schooley
  • Christopher A. Phillips
Research Article

Abstract

Knowledge of how habitat heterogeneity affects dispersal is critical for conserving connectivity in current and changing landscapes. However, we generally lack an understanding of how dispersal costs and animal movements vary among crops characteristic of agroecosystems. We hypothesized that a physiological constraint, desiccation risk, influences movement behavior among crops and other matrix habitats (corn, soybean, forest, prairie) in Ambystoma tigrinum (tiger salamander) in Illinois, USA. In a desiccation experiment, salamanders were added to enclosures in four replicate plots of each matrix habitat, and water loss was measured every 12 h for 48 h. Changes in water loss were examined using a linear mixed model. Water loss varied among treatments, over time, and there was a significant treatment-time interaction. Water loss was greater in corn and prairie than in forest and soybean. To assess whether salamanders move through matrix habitats that minimize desiccation, we tracked movements of individuals released on edges between habitats for two treatment combinations: soybean–corn, and soybean–prairie. As predicted based on our desiccation experiment, movements were oriented towards soybean in both cases. Thus, variation in desiccation risk among matrix habitats likely influenced movement decisions by salamanders, although other factors such as predation risk could have contributed to habitat choice. We argue that conceptualizing dispersal cost as uniformly high in all crop types is too simplistic. Estimating crop-specific dispersal costs and movement patterns may be necessary for constructing effective measures of landscape connectivity in agroecosystems.

Keywords

Agriculture Amphibian Connectivity Cost-distance Dispersal Illinois Landscape matrix Least-cost Salamander Spatial ecology 

Notes

Acknowledgments

Funding was provided by the American Museum of Natural History, Chicago Herpetological Society, University of Illinois, and Illinois State Academy of Science. We thank J. Wolff and S. Zec for assistance with fieldwork. S. Buck, T. Moyer and B. Towey provided invaluable logistical support, and we are grateful to the Richardson Wildlife Foundation for facilitating this research. G. Batzli, E. Heske, and the Schooley lab group provided helpful comments on the manuscript. Scientific permit authorization was granted by the Illinois Department of Natural Resources under 110 ILC 425/20, and animal care and handling was covered by IACUC protocol 09026.

References

  1. Adriaensen F, Chardon JP, De Blust G, Swinnen E, Villalba S, Gulinck H, Matthysen E (2003) The application of ‘least-cost’ modeling as a functional landscape model. Landsc Urban Plann 64:233–247CrossRefGoogle Scholar
  2. Baguette M, Van Dyck H (2007) Landscape connectivity and animal behavior: functional grain as a key determinant for dispersal. Landscape Ecol 22:1117–1129CrossRefGoogle Scholar
  3. Beier P, Majka DR, Newell SL (2009) Uncertainty analysis of least-cost modeling for designing wildlife linkages. Ecol Appl 19:2067–2077CrossRefPubMedGoogle Scholar
  4. Chan-McLeod ACA (2003) Factors affecting the permeability of clearcuts to red-legged frogs. J Wildlife Manage 67:663–671CrossRefGoogle Scholar
  5. Charney ND, Letcher BH, Haro A, Warren PS (2009) Terrestrial passive integrated transponder antennae for tracking small animal movements. J Wildlife Manage 73:1245–1250CrossRefGoogle Scholar
  6. Church DR, Bailey LL, Wilbur HM, Kendall WL, Hines JE (2007) Iteroparity in the variable environment of the salamander Ambystoma tigrinum. Ecology 88:891–903CrossRefPubMedGoogle Scholar
  7. Clobert J, Danchin E, Dhondt AA, Nichols JD (eds) (2001) Dispersal. Oxford University Press, New YorkGoogle Scholar
  8. Compton BW, McGarigal K, Cushman SA, Gamble LR (2007) A resistant-kernel model of connectivity for amphibians that breed in vernal pools. Conserv Biol 21:788–799CrossRefPubMedGoogle Scholar
  9. Gentz EJ (2007) Medicine and surgery of amphibians. ILAR J 48:255–259PubMedGoogle Scholar
  10. Gotelli NJ, Ellison AM (2004) A primer of ecological statistics. Sinauer, SunderlandGoogle Scholar
  11. Graeter GJ, Rothermel BB, Whitfield Gibbons J (2008) Habitat selection and movement of pond-breeding amphibians in experimentally fragmented pine forests. J Wildlife Manage 72:473–482CrossRefGoogle Scholar
  12. Hanski I, Gilpin ME (eds) (1997) Metapopulation biology: ecology, genetics, and evolution. Academic Press, San DiegoGoogle Scholar
  13. Harrison S, Taylor AD (1997) Empirical evidence for metapopulation dynamics. In: Hanski I, Gilpin ME (eds) Metapopulation biology: ecology, genetics, and evolution. Academic Press, San Diego, pp 27–42Google Scholar
  14. Janin A, Léna J-P, Ray N, Delacourt C, Allemand P, Joly P (2009) Assessing landscape connectivity with calibrated cost-distance modelling: predicting common toad distribution in a context of spreading agriculture. J Appl Ecol 46:833–841CrossRefGoogle Scholar
  15. Lande R (1988) Genetics and demography in biological conservation. Science 241:1455–1460CrossRefPubMedGoogle Scholar
  16. Magle SB, Theobald DM, Crooks KR (2009) A comparison of metrics predicting landscape connectivity for a highly interactive species along an urban gradient in Colorado, USA. Landscape Ecol 24:267–280CrossRefGoogle Scholar
  17. Mazerolle MJ, Desrochers A (2005) Landscape resistance to frog movements. Can J Zool 83:455–464CrossRefGoogle Scholar
  18. Mazerolle MJ, Vos CC (2006) Choosing the safest route: frog orientation in an agricultural landscape. J Herpetol 40:435–441CrossRefGoogle Scholar
  19. McRae BH, Dickson BG, Keitt TH, Shah VB (2008) Using circuit theory to model connectivity in ecology, evolution, and conservation. Ecology 89:2712–2724CrossRefPubMedGoogle Scholar
  20. Opdam P, Wascher D (2004) Climate change meets habitat fragmentation: linking landscape and biogeographical scale levels in research and conservation. Biol Conserv 117:285–297CrossRefGoogle Scholar
  21. Petranka JW (1998) Salamanders of the United States and Canada. Smithsonian Institute Press, WashingtonGoogle Scholar
  22. Phillips CA (1989) Breeding pond fidelity, population structure, and phylogeography in the spotted salamander, Ambystoma maculatum. Dissertation, Washington University, St. LouisGoogle Scholar
  23. Pough FH, Wilson RE (1970) Natural daily temperature stress, dehydration, and acclimation in juvenile Ambystoma maculatum (Shaw) (Amphibia: Caudata). Physiol Zool 43:194–205Google Scholar
  24. Preest MR, Pough FH (1989) Interaction of temperature and hydration on locomotion of toads. Funct Ecol 3:693–699CrossRefGoogle Scholar
  25. Prugh LR, Hodges KE, Sinclair ARE, Brashares JS (2008) Effect of habitat area and isolation on fragmented animal populations. Proc Natl Acad Sci 105:20770–20775CrossRefPubMedGoogle Scholar
  26. Rayfield B, Fortin M, Fall A (2010) The sensitivity of least-cost habitat graphs to relative cost surface values. Landscape Ecol 25:519–532CrossRefGoogle Scholar
  27. Ricketts TH (2001) The matrix matters: effective isolation in fragmented landscapes. Am Nat 158:87–99CrossRefPubMedGoogle Scholar
  28. Rittenhouse TAG, Semlitsch RD (2006) Grasslands as movement barriers for a forest-associated salamander: migration behavior of adult and juvenile salamanders at a distinct habitat edge. Biol Conserv 131:14–22CrossRefGoogle Scholar
  29. Rittenhouse TAG, Harper EB, Rehard LR, Semlitsch RD (2008) The role of microhabitats in the desiccation and survival of anurans in recently harvested oak-hickory forest. Copeia 2008:807–814CrossRefGoogle Scholar
  30. Rittenhouse TAG, Semlitsch RD, Thompson FR III (2009) Survival costs associated with wood frog breeding migrations: effects of timber harvest and drought. Ecology 90:1620–1630CrossRefPubMedGoogle Scholar
  31. Rizkalla CE, Swihart RK (2007) Explaining movement decisions of forest rodents in fragmented landscapes. Biol Conserv 140:339–348CrossRefGoogle Scholar
  32. Rohr JR, Madison DM (2003) Dryness increases predation risk in efts: support for an amphibian decline hypothesis. Oecologia 135:657–664PubMedGoogle Scholar
  33. Rothermel BB, Luhring TM (2005) Burrow availability and desiccation risk of mole salamanders (Ambystoma talpoideum) in harvested versus unharvested forest stands. J Herpetol 39:619–626CrossRefGoogle Scholar
  34. Rothermel BB, Semlitsch RD (2002) An experimental investigation of landscape resistance of forest versus old-field habitats to emigrating juvenile amphibians. Conserv Biol 16:1324–1332CrossRefGoogle Scholar
  35. Saumure RA, Herman TB, Titman RD (2007) Effects of haying and agricultural practices on a declining species: the North American wood turtle, Glyptemys insculpta. Biol Conserv 135:565–575CrossRefGoogle Scholar
  36. Schadt S, Knauer F, Kaczensky P, Revilla E, Wiegand T, Trepl L (2002) Rule-based assessment of suitable habitat and patch connectivity for the Eurasian lynx. Ecol Appl 12:1469–1483CrossRefGoogle Scholar
  37. Schooley RL, Wiens JA (2005) Spatial ecology of cactus bugs: area constraints and patch connectivity. Ecology 86:1627–1639CrossRefGoogle Scholar
  38. Semlitsch RD (2008) Differentiating migration and dispersal processes for pond-breeding amphibians. J Wildl Manage 72:260–267CrossRefGoogle Scholar
  39. Sinsch U (1990) Migration and orientation in anuran amphibians. Ethol Ecol Evol 2:65–79CrossRefGoogle Scholar
  40. Stevens VM, Polus E, Wesselingh RA, Schtickzelle N, Baguette M (2004) Quantifying functional connectivity: experimental evidence for patch-specific resistance in the Natterjack toad (Bufo calamita). Landscape Ecol 19:829–842CrossRefGoogle Scholar
  41. Stevens VM, Leboulengé É, Wesselingh RA, Baguette M (2006) Quantifying functional connectivity: experimental assessment of boundary permeability for the natterjack toad (Bufo calamita). Oecologia 150:161–171CrossRefPubMedGoogle Scholar
  42. USDA NASS [U.S. Department of Agriculture National Agricultural Statistics Service] (2007) 2007 Census of Agriculture. Available from http://www.agcensus.usda.gov/Publications/2007/Full_Report/usv1.pdf. Accessed April 2010
  43. Wiens JA (1997) Metapopulation dynamics and landscape ecology. In: Hanski I, Gilpin ME (eds) Metapopulation biology: ecology, genetics, and evolution. Academic Press, San Diego, pp 43–62Google Scholar
  44. Zar JH (1984) Biostatistical analysis. Prentice-Hall, Englewood CliffsGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Bradley J. Cosentino
    • 1
  • Robert L. Schooley
    • 2
  • Christopher A. Phillips
    • 3
  1. 1.Program in Ecology, Evolution, and Conservation BiologyUniversity of IllinoisUrbanaUSA
  2. 2.Department of Natural Resources and Environmental SciencesUniversity of IllinoisUrbanaUSA
  3. 3.Illinois Natural History SurveyUniversity of IllinoisChampaignUSA

Personalised recommendations