Hostname: page-component-7479d7b7d-qs9v7 Total loading time: 0 Render date: 2024-07-12T01:56:58.052Z Has data issue: false hasContentIssue false
  • English
  • Français

Quantification of motility of carabid beetles in farmland

Published online by Cambridge University Press:  12 February 2015

A.B. Allema ,
W. van der Werf ,
J.C.J. Groot ,
L. Hemerik ,
G. Gort ,
W.A.H. Rossing  and
J.C. van Lenteren
A.B. Allema
Affiliation:
Farming Systems Ecology Group, Wageningen University, Droevendaalsesteeg 1, 6708PB Wageningen, The Netherlands
W. van der Werf*
Affiliation:
Centre for Crop Systems Analysis, Wageningen University, Droevendaalsesteeg 1, 6708PB Wageningen, The Netherlands
J.C.J. Groot
Affiliation:
Farming Systems Ecology Group, Wageningen University, Droevendaalsesteeg 1, 6708PB Wageningen, The Netherlands
L. Hemerik
Affiliation:
Biometris, Wageningen University, Droevendaalsesteeg 1, 6708PB Wageningen, The Netherlands
G. Gort
Affiliation:
Biometris, Wageningen University, Droevendaalsesteeg 1, 6708PB Wageningen, The Netherlands
W.A.H. Rossing
Affiliation:
Farming Systems Ecology Group, Wageningen University, Droevendaalsesteeg 1, 6708PB Wageningen, The Netherlands
J.C. van Lenteren
Affiliation:
Laboratory of Entomology, Wageningen University, Droevendaalsesteeg 1, 6708PB Wageningen, The Netherlands
*
*Author for correspondence Phone: +31 317 484765 Fax: +31 317 485572 E-mail: wopke.vanderwerf@wur.nl
Get access Rights & Permissions [Opens in a new window]

Abstract

Quantification of the movement of insects at field and landscape levels helps us to understand their ecology and ecological functions. We conducted a meta-analysis on movement of carabid beetles (Coleoptera: Carabidae), to identify key factors affecting movement and population redistribution. We characterize the rate of redistribution using motility μ (L2 T−1), which is a measure for diffusion of a population in space and time that is consistent with ecological diffusion theory and which can be used for upscaling short-term data to longer time frames. Formulas are provided to calculate motility from literature data on movement distances. A field experiment was conducted to measure the redistribution of mass-released carabid, Pterostichus melanarius in a crop field, and derive motility by fitting a Fokker–Planck diffusion model using inverse modelling. Bias in estimates of motility from literature data is elucidated using the data from the field experiment as a case study. The meta-analysis showed that motility is 5.6 times as high in farmland as in woody habitat. Species associated with forested habitats had greater motility than species associated with open field habitats, both in arable land and woody habitat. The meta-analysis did not identify consistent differences in motility at the species level, or between clusters of larger and smaller beetles. The results presented here provide a basis for calculating time-varying distribution patterns of carabids in farmland and woody habitat. The formulas for calculating motility can be used for other taxa.

Keywords

carabid beetlesmovementdispersalmotilitymeta-analysisPterostichus melanariusmark-recaptureFokker–Planck diffusion
Type
Research Papers
Information
Bulletin of Entomological Research , Volume 105 , Issue 2 , April 2015 , pp. 234 - 244
Check for updates
Copyright
Copyright © Cambridge University Press 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Allema, A.B., van der Werf, W., van Lenteren, J.C., Hemerik, L. & Rossing, W.A.H. (2014) Movement behaviour of the carabid beetle Pterostichus melanarius in crops and at a habitat interface explains patterns of population redistribution in the field. PLoS ONE, 9(12): e115751. doi:10.1371/journal.pone.0115751.CrossRefGoogle Scholar
Baars, M.A. (1979 a) Patterns of movement of radioactive carabid beetles. Oecologia 44, 125–140.CrossRefGoogle ScholarPubMed
Baars, M.A. (1979 b) Catches in pitfall traps in relation to mean densities of carabid beetles. Oecologia 41, 25–46.CrossRefGoogle ScholarPubMed
Bartoń, K. (2014) Multi-model inference. R package version 1.10.5. Available online at http://CRAN.R-project.org/package=MuMIn Google Scholar
Benjamin, R., Cedric, G. & Pablo, I. (2008) Modeling spatially explicit population dynamics of Pterostichus melanarius Ill. (Coleoptera: Carabidae) in response to changes in the composition and configuration of agricultural landscapes. Landscape and Urban Planning 84, 191–199.Google Scholar
Bertoncelj, I. & Dolman, P.M. (2013) The matrix affects trackway corridor suitability for an arenicolous specialist beetle. Journal of Insect Conservation 17, 503–510.Google Scholar
Bolker, B.M. (2008) Ecological Models and Data in R. Princeton, NJ, Princeton University Press.Google Scholar
Bommarco, R. & Fagan, W.F. (2002) Influence of crop edges on movement of generalist predators: a diffusion approach. Agricultural and Forest Entomology 4, 21–30.Google Scholar
Brouwers, N.C. & Newton, A.C. (2009) Movement rates of woodland invertebrates: a systematic review of empirical evidence. Insect Conservation and Diversity 2, 10–22.CrossRefGoogle Scholar
Charrier, S., Petit, S. & Burel, F. (1997) Movements of Abax parallelepipedus (Coleoptera, Carabidae) in woody habitats of a hedgerow network landscape: a radio-tracing study. Agriculture Ecosystems & Environment 61, 133–144.Google Scholar
Codling, E.A., Plank, M.J. & Benhamou, S. (2008) Random walk models in biology. Journal of the Royal Society Interface 5, 813–834.Google Scholar
Drach, A. & Cancela Da Fonseca, J.P. (1990) Experimental and theoretical approach of the locomotory activity of forest carabid beetle. Revue d'Ecologie et de Biologie du Sol 27, 61–71.Google Scholar
Firle, S., Bommarco, R., Ekbom, B. & Natiello, M. (1998) The influence of movement and resting behavior on the range of three carabid beetles. Ecology 79, 2113–2122.Google Scholar
Fox, J. & Weisberg, S. (2011) An R Companion to Applied Regression. 2nd edn. Thousand Oaks, CA, Sage, URL: http://socserv.socsci.mcmaster.ca/jfox/Books/Companion Google Scholar
Gordon, P.L. & McKinlay, R.G. (1986) Dispersal of ground beetles in a potato crop; a mark-release study. Entomologia Experimentalis et Applicata 40, 104–105.CrossRefGoogle Scholar
Greenslade, P.J.M. (1964) Pitfall trapping as a method for studying populations of Carabidae (Coleoptera). Journal of Animal Ecology 33, 301–310.Google Scholar
Groot, J.C.J., Jellema, A. & Rossing, W.A.H. (2010) Designing a hedgerow network in a multifunctional agricultural landscape: balancing trade-offs among ecological quality, landscape character and implementation costs. European Journal of Agronomy 32, 112–119.CrossRefGoogle Scholar
Hilborn, R. & Mangel, M. (1997) The Ecological Detective: Confronting Models with Data. Princeton, NJ, Princeton University Press.Google Scholar
Holland, J.M., Begbie, M., Birkett, T., Southway, S., Thomas, S.R., Alexander, C.J. & Thomas, C.F.G. (2004) The spatial dynamics and movement of Pterostichus melanarius and P. madidus (Carabidae) between and within arable fields in the UK. International Journal of Ecology and Environmental Sciences 30, 35–53.Google Scholar
Hothorn, T., Bretz, F. & Westfall, P. (2008) Simultaneous inference in general parametric models. Biometrical Journal 50, 346–363.Google Scholar
Joyce, K.A., Holland, J.M. & Doncaster, C.P. (1999) Influences of hedgerow intersections and gaps on the movement of carabid beetles. Bulletin of Entomological Research 89, 523–531.Google Scholar
Kennedy, P.J. (1994) The distribution and movement of ground beetles in relation to set-aside arable land. pp. 439–444 in Desender, K., Dufrêne, M., Loreau, M., Luff, M.L. & Maelfait, J.-P. (Eds) Carabid Beetles Ecology and Evolution. Dordrecht, Boston, London, Kluwer Academic Publishers.CrossRefGoogle Scholar
Kromp, B. (1999) Carabid beetles in sustainable agriculture: a review on pest control efficacy, cultivation impacts and enhancement. Agriculture Ecosystems & Environment 74, 187–228.Google Scholar
Lys, J.-A. & Nentwig, W. (1991) Surface-activity of carabid beetles inhabiting cereal fields – seasonal phenology and the influence of farming operations on five abundant species. Pedobiologia 35, 129–138.CrossRefGoogle Scholar
Lys, J.-A. & Nentwig, W. (1992) Augmentation of beneficial arthropods by strip-management. Oecologia 92, 373–382.Google Scholar
Mols, P.J.M. (1993) Walking to Survive: Searching, Feeding and Egg Production of the Carabid Beetle (Pterostichus coerulescens L. (=Poecilus versicolor Sturm). Wageningen, Wageningen University.Google Scholar
Nathan, R., Getz, W.M., Revilla, E., Holyoak, M., Kadmon, R., Saltz, D. & Smouse, P.E. (2008) A movement ecology paradigm for unifying organismal movement research. Proceedings of the National Academy of Sciences of the United States of America 105, 19052–19059.Google Scholar
Negro, M., Casale, A., Migliore, L., Palestrini, C. & Rolando, A. (2008) Habitat use and movement patterns in the endangered ground beetle species, Carabus olympiae (Coleoptera: Carabidae). European Journal of Entomology 105, 105–112.CrossRefGoogle Scholar
Ovaskainen, O. (2008) Analytical and numerical tools for diffusion-based movement models. Theoretical Population Biology 73, 198–211.CrossRefGoogle ScholarPubMed
Petit, S. (1994) Diffusion of forest carabid beetles in hedgerow network landscapes. in Desender, K., Dufrêne, M., Loreau, M., Luff, M. & Maelfait, J.P. (Eds) Carabid Beetles Ecology and Evolution. Dordrecht, Boston, London, Kluwer Academic Publishers Google Scholar
Petit, S. & Burel, F. (1993) Movement of Abax ater (Col. Carabidae): do forest species survive in hedgerow networks? Vie et Milieu 43, 119–124.Google Scholar
Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D. & R Core Team (2014) Linear and nonlinear mixed effects models. R package version 3.1-117, Available online at URL: http://CRAN.R-project.org/package=nlme Google Scholar
Press, W.H., Teukolsky, S.A., Vetterling, W.T. & Flannery, B.P. (2007) Numerical Recipes: The Art of Scientific Computing. New York, Cambridge University Press.Google Scholar
Rykken, J.J., Jepson, P.C. & Moldenke, A.R. (2011) Ground-dwelling arthropod distribution and movement across a fragmented riparian forest. Northwest Science 85, 527–541.Google Scholar
R Core Team (2014) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL: http://www.R-project.org/.Google Scholar
Saska, P., van der Werf, W., Hemerik, L., Luff, M.L., Hatten, T.D. & Honĕk, A. (2012) Temperature effects on pitfall catches of epigeal arthropods: a model and method for bias correction. Journal of Applied Ecology 50, 181–189. doi: 10.1111/1365-2664.12023 Google Scholar
Schellhorn, N.A., Bianchi, F.J.J.A. & Hsu, C.L. (2014) Movement of entomophagous arthropods in agricultural landscapes: links to pest suppression. Annual Review of Entomology 59, 559–581.Google Scholar
Sherratt, T.N. & Jepson, P.C. (1993) A metapopulation approach to modelling the long-term impact of pesticides on invertebrates. Journal of Applied Ecology 30, 696–705.Google Scholar
Storn, R. & Price, K. (1997) Differential evolution – a simple and efficient heuristic for global optimization over continuous spaces. Journal of Global Optimization 11, 341–359.CrossRefGoogle Scholar
Sunderland, K.D. (2002) Invertebrate pest control by carabids. pp. 165–214 in Holland, J.M. (Ed.) The Agroecology of Carabid Beetles. Andover, Intercept.Google Scholar
Thiele, H.U. (1977) Carabid Beetles in their Environments. Berlin, Heidelberg, New York, Springer-Verlag Google Scholar
Thomas, C.F.G., Parkinson, L. & Marshall, E.J.P. (1998) Isolating the components of activity-density for the carabid beetle Pterostichus melanarius in farmland. Oecologia 116, 103–112.CrossRefGoogle ScholarPubMed
Turchin, P. (1998) Quantitative Analysis of Movement. Sunderland, MA, Sinauer Associates, Inc. Google Scholar
Turchin, P. & Thoeny, W.T. (1993) Quantifying dispersal of southern pine beetles with mark-recapture experiments and a diffusion model. Ecological Applications 3, 187–198.Google Scholar
Van den Hoeven, N., Hemerik, L. & Jansen, P.A. (2005) Balancing statistics and ecology: lumping experimental data for model selection. pp. 233–265 in Reydon, T.A.C. & Hemerik, L. (Eds) Current Themes in Theoretical Biology. Netherlands, Springer.CrossRefGoogle Scholar
Wallin, H. & Ekbom, B. (1994) Influence of hungry level and prey densities on movement patterns in three species of Pterostichus beetles (Coleoptera, Carabidae). Environmental Entomology 23, 1171–1181.Google Scholar
Wallin, H. & Ekbom, B.S. (1988) Movements of carabid beetles (Coleoptera, Carabidae) inhabiting cereal fields – a field tracing study. Oecologia 77, 39–43.Google Scholar
Westerberg, L., Ostman, O. & Wennergren, U. (2005) Movement effects on equilibrium distributions of habitat generalists in heterogeneous landscapes. Ecological Modelling 188, 432–447.Google Scholar
Zhang, J., Drummond, F.A., Liebman, M. & Hartke, A. (1997) Phenology and dispersal of Harpalus rufipes DeGeer (Coleoptera: Carabidae) in agroecosystems in Maine. Journal of Agricultural Entomology 14, 171–186.Google Scholar
Zuur, A.F., Ieno, E.N., Walker, N., Saveliev, A.A. & Smith, G.M. (2009) Mixed Effects Models and Extensions in Ecology with R. New York, Springer.Google Scholar
Supplementary material: File

Allema supplementary material

Appendix A

Download Allema supplementary material(File)
File 48.6 KB
Supplementary material: PDF

Allema supplementary material

Appendix B

Download Allema supplementary material(PDF)
PDF 178.4 KB
Supplementary material: PDF

Allema supplementary material

Appendix C

Download Allema supplementary material(PDF)
PDF 302.9 KB