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Landscape Ecology

, Volume 34, Issue 1, pp 105–117 | Cite as

Separating the effects of habitat amount and fragmentation on invertebrate abundance using a multi-scale framework

  • Laura BoscoEmail author
  • Ho Yi Wan
  • Samuel A. Cushman
  • Raphaël Arlettaz
  • Alain Jacot
Research Article

Abstract

Context

Herbicide treatments in viticulture can generate highly contrasting mosaics of vegetated and bare vineyards, of which vegetated fields often provide better conditions for biodiversity. In southern Switzerland, where herbicides are applied at large scales, vegetated vineyards are limited in extent and isolated from one another, potentially limiting the distribution and dispersal ability of organisms.

Objectives

We tested the separate and interactive effects of habitat amount and fragmentation on invertebrate abundance using a multi-scale framework, along with additional environmental factors. We identified which variables at which scales were most important in predicting patterns of invertebrate abundance.

Methods

We used a factorial design to sample across a gradient of habitat amount (area of vegetated vineyards, measured as percentage of landscape PLAND) and fragmentation (number of vegetated patches, measured as patch density PD). Using 10 different spatial scales, we identified the factors and scales that most strongly predicted invertebrate abundance and tested potential interactions between habitat amount and fragmentation.

Results

Habitat amount (PLAND index) was most important in predicting invertebrate numbers at a field scale (50 m radius). In contrast, we found a negative effect of fragmentation (PD) at a broad scale of 450 m radius, but no interactive effect between the two.

Conclusions

The spatial scales at which habitat amount and fragmentation affect invertebrates differ, underpinning the importance of spatially explicit study designs in disentangling the effects between habitat amount and configuration. We showed that the amount of vegetated vineyards has more influence on invertebrate abundance, but that fragmentation also contributed substantially. This suggests that efforts for augmenting the area of vegetated vineyards is more beneficial for invertebrate numbers than attempts to connect them.

Keywords

Agriculture Conservation Habitat amount hypothesis Patch density Vineyard 

Notes

Acknowledgements

We thank all farmers and the VITIVAL (Valais association for viticulture) groups for their collaboration and allowing us to do this study on their vineyards. We are grateful to Valentin Moser for field and lab assistance and Luca Chiaverini for help with GIS analyses. We further thank both reviewers for their valuable comments and inputs which improved the quality of this paper substantially. This study was supported by the Swiss National Science Foundation, grant 31003A_149780 to Alain Jacot.

Supplementary material

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Supplementary material 1 (DOCX 118 kb)
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Supplementary material 2 (DOCX 18 kb)
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Supplementary material 3 (DOCX 1526 kb)
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Supplementary material 4 (DOCX 16 kb)

References

  1. Arlettaz R, Maurer ML, Mosimann-Kampe P, Nusslé S, Abadi F, Braunisch V, Schaub M (2012) New vineyard cultivation practices create patchy ground vegetation, favouring woodlarks. J Ornithol 153:229–238CrossRefGoogle Scholar
  2. Bartón K (2016) Mumin: Multi-model inference. R package version 1.10.6. https://cran.R-project.Org/package=mumin
  3. Bates D, Maechler M, Bolker B, Walker S (2015) Fitting linear mixed-effects models using lme4. J Stat Softw 67:1–48CrossRefGoogle Scholar
  4. Bivand R, Piras G (2015) Comparing implementations of estimation methods for spatial econometrics. J Stat Softw 63:1–36Google Scholar
  5. Bolker BM, Brooks ME, Clark CJ, Geange SW, Poulsen JR, Stevens MHH, White JSS (2009) Generalized linear mixed models: a practical guide for ecology and evolution. Trends Ecol Evol 24:127–135CrossRefGoogle Scholar
  6. Bowman J, Jaeger JAG, Fahrig L (2002) Dispersal distance of mammals is proportional to home range size. Ecology 83:2049–2055CrossRefGoogle Scholar
  7. Braaker S, Ghazoul J, Obrist M, Moretti M (2014) Habitat connectivity shapes urban arthropod communities: the key role of green roofs. Ecology 95:1010–1021CrossRefGoogle Scholar
  8. Burnham KP, Anderson DR (2002) Model selection and multimodel inference: a practical information-theoretic approach. Springer, New YorkGoogle Scholar
  9. Chambers CL, Cushman SA, Medina-Fitoria A, Martínez-Fonseca J, Chávez-Velásquez M (2016) Influences of scale on bat habitat relationships in a forested landscape in Nicaragua. Landscape Ecol 31:299–1318CrossRefGoogle Scholar
  10. Coxwell CC, Bock CE (1995) Spatial variation in diurnal surface temperatures and the distribution and abundance of an alpine grasshopper. Oecologia 104:433–439CrossRefGoogle Scholar
  11. Cushman SA, Gutzweiler K, Evans JS, McGarigal K (2010) The gradient paradigm: a conceptual and analytical framework for landscape ecology. Spatial complexity, informatics, and wildlife conservation. Springer, New York, pp 83–108CrossRefGoogle Scholar
  12. Cushman SA, McGarigal K, Neel MC (2008) Parsimony in landscape metrics: strength, universality, and consistency. Ecol Indic 8:691–703CrossRefGoogle Scholar
  13. Cushman SA, Shirk AJ, Landguth EL (2013) Landscape genetics and limiting factors. Conserv Genet 14:263–274CrossRefGoogle Scholar
  14. Debinski DM, Holt RD (2000) A survey and overview of habitat fragmentation experiments. Conserv Biol 14:342–355CrossRefGoogle Scholar
  15. Dormann CF, Elith J, Bacher S, Buchmann C, Carl G, Carré G, Diekötter T, García Márquez J, Gruber B, Lafourcade B, Leitão P, Münkemüller T, McClean C, Osborne P, Reineking B, Schröder B, Skidmore A, Zurell D, Lautenbach S (2012) Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36:27–46CrossRefGoogle Scholar
  16. Eigenbrod F, Hecnar SJ, Fahrig L (2008) Accessible habitat: an improved measure of the effects of habitat loss and roads on wildlife populations. Landscape Ecol 23:159–168CrossRefGoogle Scholar
  17. ESRI (2015) Arcgis 10.3.1 for desktop. In: Institute E. S. R. (ed). Redlands, CaliforniaGoogle Scholar
  18. Evans JS, Oakleaf J, Cushman SA, Theobald D (2014) An arcgis toolbox for surface gradient and geomorphometric modeling, version 2.0–0Google Scholar
  19. Ewers RM, Didham RK (2008) Pervasive impact of large-scale edge effects on a beetle community. Proc Natl Acad Sci USA 105:5426–5429CrossRefGoogle Scholar
  20. Fahrig L (2003) Effects of habitat fragmentation on biodiversity. Ann Rev Ecol Evol Syst 34:487–515CrossRefGoogle Scholar
  21. Fahrig L (2013) Rethinking patch size and isolation effects: the habitat amount hypothesis. J Biogeogr 40:1649–1663CrossRefGoogle Scholar
  22. Fahrig L, Rytwinski T (2009) Effects of roads on animal abundance: An empirical review and synthesis. Ecol and Soc 14: 21. http://www.ecologyandsociety.org/vol14/iss1/art21/
  23. Flather CH, Bevers M (2002) Patchy reaction-diffusion and population abundance: the relative importance of habitat amount and arrangement. Am Nat 159:40–56CrossRefGoogle Scholar
  24. Foley JA, Ramankutty N, Brauman KA, Cassidy ES, Gerber JS, Johnston M, Mueller ND, O’Connell C, Ray DK, West PC, Balzer C, Bennett EM, Carpenter SR, Hill J, Monfreda C, Polasky S, Rockstrom J, Sheehan J, Siebert S, Tilman D, Zaks DPM (2011) Solutions for a cultivated planet. Nature 478:337–342CrossRefGoogle Scholar
  25. Gelman A, Su Y-S (2015) Arm: data analysis using regression and multilevel/hierarchical models. http://CRAN.R-project.org/package=arm
  26. Grand J, Buonaccorsi J, Cushman SA, Griffin CR, Neel MC (2004) A multiscale landscape approach to predicting bird and moth rarity hotspots in a threatened pitch pine–scrub oak community. Conserv Biol 18:1063–1077CrossRefGoogle Scholar
  27. Haddad NM, Gonzalez A, Brudvig LA, Burt MA, Levey DJ, Damschen EI (2017) Experimental evidence does not support the habitat amount hypothesis. Ecography 40:48–55CrossRefGoogle Scholar
  28. Hanski I (2015) Habitat fragmentation and species richness. J Biogeogr 42:989–993CrossRefGoogle Scholar
  29. Holland J, Fahrig L (2000) Effect of woody borders on insect density and diversity in crop fields: a landscape-scale analysis. Agric Ecosyst Environ 78:115–122CrossRefGoogle Scholar
  30. Holland JD, Fahrig L, Cappuccino N (2005) Body size affects the spatial scale of habitat–beetle interactions. Oikos 110:101–108CrossRefGoogle Scholar
  31. Jaeger JA (2000) Landscape division, splitting index, and effective mesh size: new measures of landscape fragmentation. Landscape Ecol 15:115–130CrossRefGoogle Scholar
  32. Korner-Nievergelt F (2015) Bayesian data analysis in ecology using linear models with R, Bugs, and Stan. Academic Press, AmsterdamGoogle Scholar
  33. Krebs JR, Wilson JD, Bradbury RB, Siriwardena GM (1999) The second silent spring? Nature 400:611–612CrossRefGoogle Scholar
  34. Laforge MP, Vander Wal E, Brook RK, Bayne EM, McLoughlin PD (2015) Process-focussed, multi-grain resource selection functions. Ecol Modell 305:10–21CrossRefGoogle Scholar
  35. Lawton JH (1995) Extinction risks. In: Lawton JH, May RM (eds) Population dynamics principles. Oxford University Press, Oxford, pp 147–163Google Scholar
  36. Legendre P, Legendre L (1998) Numerical ecology. Elsevier, AmsterdamGoogle Scholar
  37. Levin SA (1992) The problem of pattern and scale in ecology. Ecology 73:1943–1967CrossRefGoogle Scholar
  38. Martin AE, Fahrig L (2012) Measuring and selecting scales of effect for landscape predictors in species-habitat models. Ecol Appl 22:2277–2292CrossRefGoogle Scholar
  39. McGarigal K, Cushman SA (2002) Comparative evaluation of experimental approaches to the study of habitat fragmentation effects. Ecol Appl 12:335–345CrossRefGoogle Scholar
  40. McGarigal K, Cushman SA, Ene E (2012) Fragstats v4: spatial pattern analysis program for categorical and continuous maps. v4 edn, pp. Computer software program produced by the authors at the University of Massachusetts, Amherst http://www.umass.edu/landeco/research/fragstats/fragstats.html
  41. McGarigal K, Wan HY, Zeller KA, Timm BC, Cushman SA (2016) Multi-scale habitat selection modeling: a review and outlook. Landsc Ecol 31:1161–1175CrossRefGoogle Scholar
  42. Melo GL, Sponchiado J, Caceres NC, Fahrig L (2017) Testing the habitat amount hypothesis for south American small mammals. Biol Conserv 209:304–314CrossRefGoogle Scholar
  43. Mendenhall CD, Karp DS, Meyer CFJ, Hadly EA, Daily GC (2014) Predicting biodiversity change and averting collapse in agricultural landscapes. Nature 509:213–217CrossRefGoogle Scholar
  44. Miguet P, Jackson HB, Jackson ND, Martin AE, Fahrig L (2016) What determines the spatial extent of landscape effects on species? Landscape Ecol 31:1177–1194CrossRefGoogle Scholar
  45. Mortelliti A, Amori G, Capizzi D, Cervone C, Fagiani S, Pollini B, Boitani L (2011) Independent effects of habitat loss, habitat fragmentation and structural connectivity on the distribution of two arboreal rodents. J Appl Ecol 48:153–162CrossRefGoogle Scholar
  46. Neel MC, McGarigal K, Cushman SA (2004) Behavior of class-level landscape metrics across gradients of class aggregation and area. Landscape Ecol 19:435–455CrossRefGoogle Scholar
  47. Pedro ARS, Simonetti JA (2015) The relative influence of forest loss and fragmentation on insectivorous bats: does the type of matrix matter? Landscape Ecol 30:1561–1572CrossRefGoogle Scholar
  48. R Development Core Team (2018) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. http://www.R-project.org/
  49. Radford JQ, Bennett AF (2007) The relative importance of landscape properties for woodland birds in agricultural environments. J Appl Ecol 44:737–747CrossRefGoogle Scholar
  50. Rybicki J, Hanski I (2013) Species-area relationships and extinctions caused by habitat loss and fragmentation. Ecol Lett 16(Suppl 1):27–38CrossRefGoogle Scholar
  51. Schüepp C, Herzog F, Entling MH (2014) Disentangling multiple drivers of pollination in a landscape-scale experiment. Proc R Soc B 281:20132667.  https://doi.org/10.1098/rspb.2013.2667 CrossRefGoogle Scholar
  52. Seibold S, Bässler C, Brandl R, Fahrig L, Förster B, Heurich M, Hothorn T, Scheipl F, Thorn S, Müller J (2017) An experimental test of the habitat-amount hypothesis for saproxylic beetles in a forested region. Ecology 98:1613–1622CrossRefGoogle Scholar
  53. Trzcinski MK, Fahrig L, Merriam G (1999) Independent effects of forest cover and fragmentation on the distribution of forest breeding birds. Ecol Appl 9:586–593CrossRefGoogle Scholar
  54. Wan HY, McGarigal K, Ganey JL, Lauret V, Timm BC, Cushman SA (2017) Meta-replication reveals non-stationarity in multi-scale habitat selection of Mexican spotted owl. Condor 119:641–658CrossRefGoogle Scholar
  55. Wiens JA (1989) Spatial scaling in ecology. Funct Ecol 3:385–397CrossRefGoogle Scholar
  56. Winter S, Bauer T, Strauss P et al (2018) Effects of vegetation management intensity on biodiversity and ecosystem services in vineyards: a meta-analysis. J Appl Ecol 55:2484–2495CrossRefGoogle Scholar
  57. Wu J, David JL (2002) A spatially explicit hierarchical approach to modeling complex ecological systems: theory and applications. Ecol Model 153:7–26CrossRefGoogle Scholar
  58. Zeller KA, McGarigal K, Beier P, Cushman SA, Vickers TW, Boyce WM (2014) Sensitivity of landscape resistance estimates based on point selection functions to scale and behavioral state: Pumas as a case study. Landscape Ecol 29:541–557CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Division of Conservation Biology, Institute of Ecology and EvolutionUniversity of BernBernSwitzerland
  2. 2.Swiss Ornithological InstituteSionSwitzerland
  3. 3.School of Public and Community Health SciencesUniversity of MontanaMissoulaUSA
  4. 4.USDA Forest ServiceRocky Mountain Research StationFlagstaffUSA

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