Abstract
Every species experiences the landscape as a unique pattern of resource quality and heterogeneity. This subsequently affects aspects of life from the individual scale (fitness, home range size), to social group scale, up to landscape characteristics such as source–sink dynamics, connectivity and species diversity. Correctly characterising the quality and spatial pattern of resources is therefore key in modelling species’ persistence and spread. However, although many measures of heterogeneity are available for binary and ordinal landscape patterns, few are directly applicable to landscapes with a continuous description of landscape quality. Lacunarity is a measure of the structure of gaps in the landscape, first used to describe properties of fractal landscapes. We develop lacunarity analysis to allow the direct comparison of pattern in binary and continuous landscapes with differing mean quality. Using simulated landscapes with varying degrees of spatial autocorrelation and resource distribution broadly describing the spectrum of resource quality experienced by specialists and generalists, we show how the measurement of spatial pattern changes when different distributions are used to describe landscape quality. Our metric indicates the scale of measurement at which the pattern is most different from random, and thus informs the choice of scale for modelled processes in the model landscape, and the appropriate extent for landscape study. Our metric can be used to distinguish between any spatial pattern or resource description, from a simple parametric distribution for landscape quality to the variety of resources likely to be encountered in real landscapes.
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References
Allain C, Cloitre M (1991) Characterizing the lacunarity of random and deterministic fractal sets. Phys Rev A 44:3552–3558
Atwood TC (2006) The influence of habitat patch attributes on coyote group size and interaction in a fragmented landscape. Can J Zool 84:80–87
Blackwell PG (2007) Heterogeneity, patchiness and correlation of resources. Ecol. Model. 207:349–355
Carroll C, Phillips MS, Schumaker NH, Smith DW (2003) Impacts of landscape change on wold restoration success: planning a reintroduction program based on static and dynamic models. Conserv Biol 17:526–548
Chapman DS, Dytham C, Oxford GS (2007) Landscape and fine-scale movements of a leaf beetle: the importance of boundary behaviour. Oecologica 154:55–64
Dale MRT (2000) Lacunarity analysis of spatial pattern: a comparison. Landscape Ecol 15:467–478
Denoël M, Lehmann A (2006) Multi-scale effect of landscape processes and habitat quality on newt abundance: implications for conservation. Biol Conserv 130:495–504
Fahrig L (1998) When does fragmentation of breeding habitat affect population survival? Ecol Model 105:273–292
Feagin RA, Wu XB, Feagin T (2007) Edge effects in lacunarity analysis. Ecol Model 201:262–268
Fortin MJ, Dale MRT, ver Hoef J (2002) Spatial analysis in ecology. In: El-Shaarawi AH, Piegorsch WW (eds), Encyclopedia of environmetrics. Wiley, Colchester, pp 2051–2058
Fournier A, Fussel D, Carpenter L (1982) Computer rendering of stochastic models. Commun ACM 25:371–384
Greig-Smith P (1952) The use of random and contiguous quadrats in the study of the structure of plant communities. Ann Bot 16:293–316
Gustafson EJ (1998) Quantifying landscape spatial pattern: what is the state of the art? Ecosystems 1:143–156
Hamilton GS, Mather PB, Wilson JC (2006) Habitat heterogeneity influences connectivity in a spatially structured pest population. J App Ecol 43:219–226
Hargis CD, Bissonette JA, David JL (1998) The behaviour of landscape metrics commonly used in the study of habitat fragmentation. Landscape Ecol 13:167–186
Hill JK, Hamer KC (2004) Determining impacts of habitat modification on diversity of tropical forest fauna: the importance of spatial scale. J Appl Ecol 41:744–754
Holland EP, Aegerter JN, Dytham C, Smith GC (2007a) Landscape as a model: the importance of geometry. PLoS Comput Biol 10:e200
Holland EP, Aegerter JN, Smith GC (2007b) Spatial sensitivity of a generic population model, using wild boar (Sus scrofa) as a test case. Ecol Model 205:146–158
Holzkämper A, Lausch A, Seppelt R (2006) Optimizing landscape configuration to enhance habitat suitability for species with contrasting habitat requirements. Ecol Model 198:277–292
Johnson D, Macdonald D (2003) Sentenced without trial: reviling and revamping the resource dispersion hypothesis. Oikos 101:433–440
Johnson DDP, Kays R, Blackwell PG, Macdonald DW (2002) Does the resource dispersion hypothesis explain group living? TREE 17:563–570
King AW, With KA (2002) Dispersal success on spatially structured landscapes: when do spatial pattern and dispersal behavior really matter? Ecol Model 147:23–39
Kshatriya M, Cosner C (2002) A continuum formulation of the ideal free distribution and its implications for population dynamics. Theor Popul Biol 61:277–284
Law R, Murrell DJ, Dieckmann U (2003) Population growth in space and time: spatial logistic equations. Ecology 84:252–262
Malanson GP (2003) Dispersal across continuous and binary representations of landscapes. Ecol Model 169:17–24
McInerny G, Travis JMJ, Dytham C (2007) Range shifting on a fragmented landscape. Ecol Inf 2:1–8
Minor ES, McDonald RI, Treml EA, Urban DL (2008) Uncertainty in spatially explicit population models. Biol Conserv 141:956–970
Mitchell MS, Powell RA (2004) A mechanistic home range model for optimal use of spatially distributed resources. Ecol Model 177:209–232
Plotnick RE, Gardner RH (2002) A general model for simulating the effects of landscape heterogeneity and disturbance for community patterns. Ecol Model 147:171–197
Plotnick RE, Gardner RH, O’Niell RV (1993) Lacunarity indices as measures of landscape texture. Landscape Ecol 8:201–211
Plotnick RE, Gardner RH, Hargrove WW, Prestegaard K, Perlmutter M (1996) Lacunarity analysis—a general technique for the analysis of spatial patterns. Phys Rev E 53:5461–5468
Söndgerath D, Schröder B (2002) Population dynamics and habitat connectivity affecting the spatial spread of populations—a simulation study. Landscape Ecol 17:57–70
Topping CJ, Hansen TS, Jensen TS, Jepsen JU, Nikolajsen F, Odderskaer P (2003) ALMaSS, an agent-based model for animals in temperate European landscapes. Ecol Model 167:65–82
Walters S (2001) Landscape pattern and productivity effects on source–sink dynamics of deer populations. Ecol Model 143:17–32
Westerberg L, Östman Ö, Wennergren U (2005) Movement effects on equilibrium distributions of habitat generalists in heterogeneous landscapes. Ecol Model 188:432–447
Wiegand T, Knauer F, Kaczensky P, Naves J (2004) Expansion of brown bears (Ursus arctos) into the eastern Alps: a spatially explicit population model. Biodivers Cons 13:79–114
With KA, King AW (1999) Dispersal success on fractal landscapes: a consequence of lacunarity thresholds. Landscape Ecol 14:73–82
Wu BM, Subbarao KV, Ferrandino FJ, Hao JJ (2006) Spatial analysis based on variance of moving window averages. J Phytopathol 156:349–360
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Holland, E.P., Aegerter, J.N. & Dytham, C. Comparing resource representations and choosing scale in heterogeneous landscapes. Landscape Ecol 24, 213–227 (2009). https://doi.org/10.1007/s10980-008-9300-1
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DOI: https://doi.org/10.1007/s10980-008-9300-1