Skip to main content
SpringerLink
Log in

Estimating the spatial scales of landscape effects on abundance

  • Research Article
  • Published:
Landscape Ecology Aims and scope Submit manuscript

Abstract

Context

Spatial variation in abundance is influenced by local- and landscape-level environmental variables, but modeling landscape effects is challenging because the spatial scales of the relationships are unknown. Current approaches involve buffering survey locations with polygons of various sizes and using model selection to identify the best scale. The buffering approach does not acknowledge that the influence of surrounding landscape features should diminish with distance, and it does not yield an estimate of the unknown scale parameters.

Objectives

The purpose of this paper is to present an approach that allows for statistical inference about the scales at which landscape variables affect abundance.

Methods

Our method uses smoothing kernels to average landscape variables around focal sites and uses maximum likelihood to estimate the scale parameters of the kernels and the effects of the smoothed variables on abundance. We assessed model performance using a simulation study and an avian point count dataset.

Results

The simulation study demonstrated that estimators are unbiased and produce correct confidence interval coverage except in the rare case in which there is little spatial autocorrelation in the landscape variable. Canada warbler abundance was more highly correlated with site-level measures of NDVI than landscape-level NDVI, but the reverse was true for elevation. Canada warbler abundance was highest when elevation in the surrounding landscape, defined by an estimated Gaussian kernel, was between 1300 and 1400 m.

Conclusions

Our method provides a rigorous way of formally estimating the scales at which landscape variables affect abundance, and it can be embedded within most classes of statistical models.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Banerjee S, Carlin BP, Gelfand AE (2014) Hierarchical modeling and analysis for spatial data. CRC Press, Boca Raton

    Google Scholar 

  • Best NG, Ickstadt K, Wolpert RL (2000) Spatial Poisson regression for health and exposure data measured at disparate resolutions. J Am Stat Assoc 95(452):1076–1088

    Article  Google Scholar 

  • Betts MG, Fahrig L, Hadley AS, Halstead KE, Bowman J, Robinson WD, Weins J, Lindenmayer DB (2014) A species-centered approach for uncovering generalities in organism responses to habitat loss and fragmentation. Ecography 37(6):517–527

    Article  Google Scholar 

  • Bowman J, Jaeger JAG, Fahrig L (2002) Dispersal distance of mammals is proportional to home range size. Ecology 83(7):2049–2055

    Article  Google Scholar 

  • Brennan JM, Bender DJ, Contreras TA, Fahrig L (2002) Focal patch landscape studies for wildlife management: optimizing sampling effort across scales. In: Liu J, Taylor WW (eds) Integrating landscape ecology into natural resource management, Cambridge University Press, Cambridge, pp 68–91

    Google Scholar 

  • Chandler RB, Clark JD (2014) Spatially explicit integrated population models. Methods Ecol Evol 5(12):1351–1360

    Article  Google Scholar 

  • Chandler RB, King DI, DeStefano S (2009) Scrub-shrub bird habitat associations at multiple spatial scales in beaver meadows in Massachusetts. Auk 126(1):186–197

    Article  Google Scholar 

  • Chandler RB, Muths E, Sigafus BH, Schwalbe CR, Jarchow CJ (2015) Spatial occupancy models for predicting metapopulation dynamics and viability following reintroduction. J Appl Ecol 52(5):1325–1333

    Article  Google Scholar 

  • Cushman SA, McGarigal K (2004) Hierarchical analysis of forest bird species-environment relationships in the Oregon Coast Range. Ecol Appl 14(4):1090–1105

    Article  Google Scholar 

  • de Knegt HJ, van Langevelde F, Coughenour MB, Skidmore AK, De Boer WF, Heitkönig IMA, Knox NM, Slotow R, Van der Waal C, Prins HHT (2010) Spatial autocorrelation and the scaling of species–environment relationships. Ecology 91(8):2455–2465

    Article  PubMed  Google Scholar 

  • Diggle PJ (2013) Statistical analysis of spatial and spatio-temporal point patterns. CRC Press, Boca Raton

    Google Scholar 

  • Fortin MJ, Dale MRT (2005) Spatial analysis: a guide for ecologists. Cambridge University Press, Cambridge

    Google Scholar 

  • Gotway CA, Young LJ (2002) Combining incompatible spatial data. J Am Stat Assoc 97(458):632–648

    Article  Google Scholar 

  • Hanski I (1998) Metapopulation dynamics. Nature 396(6706):41–49

    Article  CAS  Google Scholar 

  • Higdon D (2002) Space and space-time modeling using process convolutions. In: Anderson CW, Barnett V, Chatwin PC, El-Shaarawi AH (eds) Quantitative methods for current environmental issues. Springer, New York, pp 37–56

    Chapter  Google Scholar 

  • Holland JD, Bert DG, Fahrig L (2004) Determining the spatial scale of species’ response to habitat. BioScience 54(3):227–233

    Article  Google Scholar 

  • Jackson HB, Fahrig L (2012) What size is a biologically relevant landscape? Landscape Ecol 27(7):929–941

    Article  Google Scholar 

  • Jackson HB, Fahrig L (2015) Are ecologists conducting research at the optimal scale? Glob Ecol Biogeogr 24(1):52–63

    Article  Google Scholar 

  • Johnson DH (1980) The comparison of usage and availability measurements for evaluating resource preference. Ecology 6(1):65–71

    Article  Google Scholar 

  • Laseter SH, Ford CR, Vose JM, Swift LW (2012) Long-term temperature and precipitation trends at the Coweeta Hydrologic Laboratory, Otto, North Carolina, USA. Hydrol Res 43(6):890

    Article  Google Scholar 

  • Lechner AM, Langford WT, Jones SD, Bekessy SA, Gordon A (2012) Investigating species-environment relationships at multiple scales: differentiating between intrinsic scale and the modifiable areal unit problem. Ecol Complex 11:91–102

    Article  Google Scholar 

  • Mashintonio AF, Pimm SL, Harris GM, van Aarde RJ, Russell GJ (2014) Data-driven discovery of the spatial scales of habitat choice by elephants. PeerJ 2:e504. doi:10.7717/peerj.504

    Article  PubMed  PubMed Central  Google Scholar 

  • Moilanen A, Hanski I (2001) On the use of connectivity measures in spatial ecology. Oikos 95(1):147–151

    Article  Google Scholar 

  • Moilanen A, Nieminen M (2002) Simple connectivity measures in spatial ecology. Ecology 83(4):1131–1145

    Article  Google Scholar 

  • Parrish MC, Hepinstall-Cymerman J (2012) Associations between multiscale landscape characteristics and breeding bird abundance and diversity across urban-rural gradients in Northeastern Georgia, USA. Urban Ecosyst 15:559–580

    Article  Google Scholar 

  • Robinson WS (1950) Ecological correlations and the behavior of individuals. Am Sociol Rev 15:351–357

    Article  Google Scholar 

  • Royle JA (2004) N-Mixture models for estimating population size from spatially replicated counts. Biometrics 60(1):108–115

    Article  PubMed  Google Scholar 

  • Royle JA, Dorazio RM (2008) Hierarchical modeling and inference in ecology: the analysis of data from populations, metapopulations and communities. Academic Press, New York

    Google Scholar 

  • Royle JA, Chandler RB, Sollmann R, Gardner B (2014) Spatial capture-recapture. Academic Press, New York

    Google Scholar 

  • Sillett TS, Chandler RB, Royle JA, Kéry M, Morrison SA (2012) Hierarchical distance-sampling models to estimate population size and habitat-specific abundance of an island endemic. Ecol Appl 22(7):1997–2006

    Article  PubMed  Google Scholar 

  • Soudani K, François C, Le Maire G, Le Dantec V, Dufrêne E (2006) Comparative analysis of IKONOS, SPOT, and ETM+ data for leaf area index estimation in temperate coniferous and deciduous forest stands. Remote Sens Environ 102(1):161–175

    Article  Google Scholar 

  • Stouffer PC, Bierregaard RO Jr, Strong C, Lovejoy TE (2006) Long-term landscape change and bird abundance in Amazonian rainforest fragments. Conserv Biol 20(4):1212–1223

    Article  PubMed  Google Scholar 

  • Thornton DH, Fletcher RJ Jr (2014) Body size and spatial scales in avian response to landscapes: a meta-analysis. Ecography 37(5):454–463

    Google Scholar 

  • Wakefield J (2004) A critique of statistical aspects of ecological studies in spatial epidemiology. Environ Ecol Stat 11(1):31–54

    Article  Google Scholar 

  • Wheatley M, Johnson C (2009) Factors limiting our understanding of ecological scale. Ecol Complex 6(2):150–159

    Article  Google Scholar 

  • Wiens JA (1989) Spatial scaling in ecology. Funct Ecol 3(4):385–397

    Article  Google Scholar 

  • Wolpert RL, Ickstadt K (1998) Poisson/gamma random field models for spatial statistics. Biometrika 85(2):251–267

    Article  Google Scholar 

  • 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(3):541–557

    Article  Google Scholar 

Download references

Acknowledgments

We thank Samuel Merker and Anna Joy Lehmicke for collecting the point count data. Paige Howell provided useful suggestions and comments on a previous version of the manuscript. Two anonymous reviewers provided insightful comments that improved the manuscript. Permission to conduct research within and around the Coweeta Basin Hydrologic Laboratory was granted by the Coweeta Hydrologic Laboratory, the USDA Forest Service, and the North Carolina Wildlife Resources Commission. JHC was supported by the Coweeta LTER, NSF Grant DEB-0823293.

Author information

Authors and Affiliations

  1. Warnell School of Forestry and Natural Resources, University of Georgia, 180 E. Green Street, Athens, GA, 30602-2152, USA

    Richard Chandler & Jeffrey Hepinstall-Cymerman

Authors
  1. Richard Chandler
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jeffrey Hepinstall-Cymerman
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Richard Chandler.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (R 4 kb)

Below is the link to the electronic supplementary material.

Supplementary material 2 (PDF 51 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chandler, R., Hepinstall-Cymerman, J. Estimating the spatial scales of landscape effects on abundance. Landscape Ecol 31, 1383–1394 (2016). https://doi.org/10.1007/s10980-016-0380-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10980-016-0380-z

Keywords

Search

Navigation