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Surface metrics for landscape ecology: a comparison of landscape models across ecoregions and scales

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Abstract

Context

The patch-mosaic model is lauded for its conceptual simplicity and ease with which conventional landscape metrics can be computed from categorical maps, yet many argue it is inconsistent with ecological theory. Gradient surface models (GSMs) are an alternative for representing landscapes, but adoption of surface metrics for analyzing spatial patterns in GSMs is hindered by several factors including a lack of meaningful interpretations.

Objectives

We investigate the performance and applicability of surface metrics across a range of ecoregions and scales to strengthen theoretical foundations for their adoption in landscape ecology.

Methods

We examine metric clustering across scales and ecoregions, test correlations with patch-based metrics, and provide ecological interpretations for a variety of surface metrics with respect to forest cover to support the basis for selecting surface metrics for ecological analyses.

Results

We identify several factors complicating the interpretation of surface metrics from a landscape perspective. First, not all surface metrics are appropriate for landscape analyses. Second, true analogs between surface metrics and patch-based, landscape metrics are rare. Researchers should focus instead on how surface measures can uniquely measure spatial patterns. Lastly, scale dependencies exist for surface metrics, but relationships between metrics do not appear to change considerably with scale.

Conclusions

Incorporating gradient surfaces into landscape ecological analyses is challenging, and many surface metrics may not have patch analogs or be ecologically relevant. For this reason, surface metrics should be considered in terms of the set of pattern elements they represent that can then be linked to landscape characteristics.

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References

  • Barbato G, Carneiro K, Cuppini D, Garnaes J, Gori G, Hughes G, Jensen CP, Jorgensen JF, Jusko O, Livi S, McQuoid H, Nielsen L, Picotto GB, Wilening G (1995) Scanning tunnelling microscopy methods for the characterization of roughness and micro hardness measurements. Synthesis report for research contract with the European Union under its programme for applied metrology. European Commission Catalogue number: CD-NA-16145 EN-C Brussels Luxemburg

  • Coulston JW, Jacobs DM, King CR, Elmore IC (2013) The influence of multi-season imagery on models of canopy cover: a case study. Photogramm Eng Remote Sens 79(5):469–477

    Article  Google Scholar 

  • Coulston JW, Moisen GG, Wilson BT, Finco MV, Cohen WB, Brewer CK (2012) Modeling percent tree canopy cover: a pilot study. Photogramm Eng Remote Sens 78(7):715–727

    Article  Google Scholar 

  • Cushman SA, Gutzweiler K, Evans JS, McGarigal K (2010) The gradient paradigm: a conceptual and analytical framework for landscape ecology. In: Spatial complexity, informatics, and wildlife conservation. Springer, Japan, pp 83–108

  • Cushman SA, McGarigal K, Neel MC (2008) Parsimony in landscape metrics: strength, universality, and consistency. Ecol Indic 8(5):691–703

    Article  Google Scholar 

  • Fischer J, Lindenmayer DB (2006) Beyond fragmentation: the continuum model for fauna research and conservation in human-modified landscapes. Oikos 112(2):473–480

    Article  Google Scholar 

  • Forman RTT (1995) Some general principles of landscape and regional ecology. Landscape Ecol 10(3):133–142

    Article  Google Scholar 

  • Frazier AE (2014) A new data aggregation technique to improve landscape metric downscaling. Landscape Ecol 29(7):1261–1276

    Article  Google Scholar 

  • Frazier AE (2015) Landscape heterogeneity and scale considerations for super-resolution mapping. Int J Remote Sens 36(9):2395–2408

    Article  Google Scholar 

  • Frazier AE (2016) Surface metrics: scaling relationships and downscaling behavior. Landscape Ecol 31(2):351–363

    Article  Google Scholar 

  • Frazier AE, Kedron P (2017a) Landscape metrics: past progress and future directions. Curr Land Ecol Rev 2(3):63–72

    Article  Google Scholar 

  • Frazier AE, Kedron P (2017b) Comparing forest fragmentation in Eastern US forests using patch-mosaic and gradient surface models. Ecol Inform 41:108–115

    Article  Google Scholar 

  • Frazier AE, Wang L (2013) Modeling landscape structure response across a gradient of land cover intensity. Landscape Ecol 28(2):233–246

    Article  Google Scholar 

  • Gadelmawla ES, Koura MM, Maksoud TMA, Elewa IM, Soliman HH (2002) Roughness parameters. J Mater Process Tech 123(1):133–145

    Article  Google Scholar 

  • Gallardo-Cruz JA, Hernandez-Stefanoni JL, Moser D, Martinez-Yrizar A, Llobet S, Meave JA (2018) Relating species richness to the structure of continuous landscapes: alternative methodological approaches. Ecosphere 9(5):1–15

    Article  Google Scholar 

  • Homer CG, Dewitz JA, Yang L, Jin S, Danielson P, Xian G, Megown K (2015) Completion of the 2011 national land cover database for the conterminous United States-representing a decade of land cover change information. Photogramm Eng Rem S 81(5):345–354

    Google Scholar 

  • Image Metrology (2017) User’s guide. http://www.imagemet.com/WebHelp6/Default.htm. Accessed 7 Feb 2017

  • Kent M (2009) Biogeography and landscape ecology: the way forward—gradients and graph theory. Prog Phys Geog 33(3):424–436

    Article  Google Scholar 

  • Lausch A, Blaschke T, Haase D, Herzog F, Syrbe RU, Tischendorf L, Walz U (2015) Understanding and quantifying landscape structure–a review on relevant process characteristics, data models and landscape metrics. Ecol Model 295:31–41

    Article  Google Scholar 

  • Li H, Wu J (2004) Use and misuse of landscape indices. Landscape Ecol 19(4):389–399

    Article  Google Scholar 

  • Manning AD, Lindenmayer DB, Nix HA (2004) Continua and Umwelt: novel perspectives on viewing landscapes. Oikos 104(3):621–628

    Article  Google Scholar 

  • McGarigal K, Cushman SA (2005) The gradient concept of landscape structure. In: Wiens J, Moss M (eds) Issues and perspectives in landscape ecology. Cambridge University Press, Cambridge, pp 112–119

    Chapter  Google Scholar 

  • McGarigal K, Cushman S, Stafford SG (2000) Multivariate statistics for wildlife and ecology research. Springer, New York

    Book  Google Scholar 

  • McGarigal K, Tagil S, Cushman SA (2009) Surface metrics: an alternative to patch metrics for the quantification of landscape structure. Landscape Ecol 24(3):433–450

    Article  Google Scholar 

  • McGarigal K, Cushman SA, Ene E (2012) FRAGSTATS v4: spatial pattern analysis program for categorical and continuous maps. University of Massachusetts, Amherst

    Google Scholar 

  • McIntyre S, Barrett GW (1992) Habitat variegation, an alternative to fragmentation. Conserv Biol 6(1):146–147

    Article  Google Scholar 

  • McIntyre S, Hobbs R (1999) A framework for conceptualizing human effects on landscapes and its relevance to management and research models. Conserv Biol 13(6):1282–1292

    Article  Google Scholar 

  • Moniem HEMA, Holland JD (2013) Habitat connectivity for pollinator beetles using surface metrics. Landscape Ecol 28(7):1251–1267

    Article  Google Scholar 

  • Omernik JM (1987) Ecoregions of the conterminous United States. Ann Assoc Am Geogr 77(1):118–125

    Article  Google Scholar 

  • Radeloff VC, Hammer RB, Stewart SI, Fried JS, Holcomb SS, McKeefry JF (2005) The wildland–urban interface in the United States. Ecol Appl 15(3):799–805

    Article  Google Scholar 

  • Riitters KH, Coulston JW, Wickham JD (2012) Fragmentation of forest communities in the eastern United States. Forest Ecol Manag 263:85–93

    Article  Google Scholar 

  • Saura S, Torne J (2009) Conefor Sensinode 2.2: a software package for quantifying the importance of habitat patches for landscape connectivity. Environ Modell Softw 24(1):135–139

  • Schindler S, Poirazidis K, Wrbka T (2008) Towards a core set of landscape metrics for biodiversity assessments: a case study from Dadia National Park, Greece. Ecol Indic 8(5):502–514

    Article  Google Scholar 

  • Scown MW, Thoms MC, De Jager NR (2015) Measuring floodplain spatial patterns using continuous surface metrics at multiple scales. Geomorph 245:87–101

    Article  Google Scholar 

  • SPIP™ The scanning probe image processor. Image Metrology A/S, Lyngby. http://www.imagemet.com/

  • Stein SM, McRoberts RE, Mahal LG, Carr MA, Alig RJ, Comas SJ, David MT, Cundiff A (2009) Private forests, public benefits: increased housing density and other pressures on private forest contributions. General Technical Report-Pacific Northwest Research Station, USDA Forest Service PNW-GTR-795

  • Steward M (1990) A new approach to the use of bearing area curve. Society of manufacturing engineers technical papers, international honing technologies and applications, May 1–3, 1990, Novi, MI

  • Stout KJ, Sullivan PJ, Dong WP, Mainsah E, Lou N, Mathia T, Zahouani H (1994) The development of methods for the characterization of roughness on three dimensions. Publication no EUR 15178 EN of the Commission of the European Communities, Luxembourg

  • Tipton J, Moisen G, Patterson P, Jackson TA, Coulston J (2012) Sampling intensity and normalizations: exploring cost-driving factors in nationwide mapping of tree canopy cover. In: McWilliams W, Roesch FA (eds) Monitoring across borders: 2010 joint meeting of the forest inventory and analysis (FIA) symposium and the southern mensurationists. e-Gen. Tech. Rep. SRS-157. Asheville, NC: US Department of Agriculture, Forest Service, Southern Research Station: 201–208

  • Turner MG (2005) Landscape ecology: what is the state of the science? Annu Rev Ecol Evol Syst 36:319–344

    Article  Google Scholar 

  • Turner MG, O’Neill RV, Gardner RH, Milne BT (1989) Effects of changing spatial scale on the analysis of landscape pattern. Landscape Ecol 3(3–4):153–162

    Article  Google Scholar 

  • Villarrubia JS (1997) Algorithm for scanned probe microscope image simulation, surface reconstruction, and tip estimation. J Res Natl Inst Stan 102:425–454

    Article  CAS  Google Scholar 

  • Wu J (2004) Effects of changing scale on landscape pattern analysis: scaling relations. Landscape Ecol 19(2):125–138

    Article  Google Scholar 

  • Wu Q, Guo F, Li H, Kang J (2017) Measuring landscape pattern in three dimensional space. Landsc Urban Plan 167:49–59

    Article  Google Scholar 

  • Zhang Z, Zinda JA, Yang Z, Yin M, Ou Z, Xu Q, Yu Q (2018) Effects of topographic attributes on landscape pattern metrics based on redundancy ordination gradient analysis. Landsc Ecol Eng 14(1):67–77

    Article  Google Scholar 

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Acknowledgements

This work was funded by a grant to A. Frazier and P. Kedron from the National Science Foundation (#SBE-1561021) on Data Complexity and Spatial Scaling: Prediction Accuracy for Emerging Landscape Paradigms.

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Authors and Affiliations

  1. Department of Geography, Center for Applications of Remote Sensing, Oklahoma State University, Stillwater, OK, USA

    Peter J. Kedron, Amy E. Frazier, Gustavo A. Ovando-Montejo & Jing Wang

  2. School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ, USA

    Peter J. Kedron & Amy E. Frazier

Authors
  1. Peter J. Kedron
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  2. Amy E. Frazier
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  3. Gustavo A. Ovando-Montejo
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  4. Jing Wang
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Corresponding author

Correspondence to Amy E. Frazier.

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Kedron, P.J., Frazier, A.E., Ovando-Montejo, G.A. et al. Surface metrics for landscape ecology: a comparison of landscape models across ecoregions and scales. Landscape Ecol 33, 1489–1504 (2018). https://doi.org/10.1007/s10980-018-0685-1

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  • DOI: https://doi.org/10.1007/s10980-018-0685-1

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