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Aberystwyth University Spatial Scales of Variance in Abundance View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Aberystwyth Research Portal Aberystwyth University Spatial scales of variance in abundance of intertidal species: effects of region, dispersal mode, and trophic level Burrows, Michael T.; Harvey, Robin; Robb, Linda; Poloczanska, Elvira S.; Mieszkowska, Nova; Moore, P.; Leaper, Rebecca; Hawkins, Stephen J.; Beneddetti-Cecchi, Lisandro Published in: Ecology DOI: 10.1890/08-0206.1 Publication date: 2009 Citation for published version (APA): Burrows, M. T., Harvey, R., Robb, L., Poloczanska, E. S., Mieszkowska, N., Moore, P., ... Beneddetti-Cecchi, L. (2009). Spatial scales of variance in abundance of intertidal species: effects of region, dispersal mode, and trophic level. Ecology, 90(5), 1242-1252. https://doi.org/10.1890/08-0206.1 General rights Copyright and moral rights for the publications made accessible in the Aberystwyth Research Portal (the Institutional Repository) are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the Aberystwyth Research Portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the Aberystwyth Research Portal Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. tel: +44 1970 62 2400 email: [email protected] Download date: 03. Oct. 2019 Ecology, 90(5), 2009, pp. 1242–1254 Ó 2009 by the Ecological Society of America Spatial scales of variance in abundance of intertidal species: effects of region, dispersal mode, and trophic level 1,5 1 1 1,2 2 MICHAEL T. BURROWS, ROBIN HARVEY, LINDA ROBB, ELVIRA S. POLOCZANSKA, NOVA MIESZKOWSKA, 2 2 2,3 4 PIPPA MOORE, REBECCA LEAPER, STEPHEN J. HAWKINS, AND LISANDRO BENEDETTI-CECCHI 1Ecology Department, Scottish Association for Marine Science, Dunstaffnage Marine Laboratory, Oban PA37 1QA United Kingdom 2Marine Biological Association of the United Kingdom, The Laboratory, Citadel Hill, Plymouth, Devon PL1 2PB United Kingdom 3Bangor University, Bangor, Gwynedd LL57 2UW United Kingdom 4University of Pisa, Dipartimento di Biologia, Via A. Volta 6, I-56126 Pisa, Italy Abstract. Determination of the pattern of variation in population abundance among spatial scales offers much insight into the potential regulating factors. Here we offer a method of quantifying spatial variance on a range of scales derived by sampling of irregularly spaced sites along complex coastlines. We use it to determine whether the nature of spatial variance depends on the trophic level or the mode of dispersal of the species involved and the role of the complexity of the underlying habitat. A least-cost distance model was used to determine distances by sea between all pairs of sites. Ordination of this distance matrix using multidimensional scaling allowed estimation of variance components with hierarchical ANOVA at nested spatial scales using spatial windows. By repeatedly moving these spatial windows and using a second set of spatial scales, average variance scale functions were derived for 50þ species in the UK rocky intertidal. Variance spectra for most species were well described by the inverse power law (1/f b) for noise spectra, with values for the exponent ranging from 0 to 1.1. At higher trophic levels (herbivores and carnivores), those species with planktonic dispersal had significantly higher b values, indicating greater large- than small-scale variability, as did those on simpler coastlines (southwestern England and Wales vs. western Scotland). Average abundance and proportional incidence of species had the strongest influence on b values, with those of intermediate abundance and incidence having much greater large-scale variance (b ’ 0.5) than rare or ubiquitous species (b ’ 0). Key words: dispersal mode; habitat complexity; population connectivity; spatial scale; trophic level; variance. INTRODUCTION Hierarchical ANOVA independently quantifies variance on each spatial scale (Underwood and Chapman 1996), Analysis of spatial patterns contributes much to allowing significance testing. Tests against simulated understanding processes structuring biological commu- data have shown that nested ANOVA does much better nities. Quantifying the relative magnitude of variance than semivariograms in detecting significant compo- (s2) at different scales, the variance spectrum, can be nents of spatial variation (Davidson and Csillag 2003). done with a variety of methods (Platt and Denman 1975, Power functions are often found to describe the Horne and Schneider 1994, 1995). For irregularly spaced pattern of variance with spatial scale very well. Variance data the two most commonly used are 1) semi-vario- spectra are commonly described by the inverse power grams, based on variance between pairs of data law, where variance scales by 1/f b, where f is the spatial separated by different distances, and 2) hierarchical frequency and 1/f is proportional to the spatial analysis of variance with smaller spatial scales nested wavelength, also commonly fitted to temporal variation within larger ones. Each approach offers different (Vasseur and Yodzis 2004). The exponent of this advantages and disadvantages (Rossi et al. 1992, Hoef function, b, is a useful description of the spectrum, with et al. 1993, Davidson and Csillag 2003). Pairwise use of values used to express environmental ‘‘noise color’’ (2, data points for variograms removes artifacts introduced red; 1, pink; and 0, white). The value of b has proved through arbitrary imposition of predefined spatial more useful than measures of single characteristic scales scales, but calculated variance includes variation up to of variation (Denny et al. 2004). The form of the and including the spatial scale of separation of points. variance spectrum, s2 as a function of f, is distinct from Variograms also assume that mean values of the that of spectral density (s2/f ): if s2 is proportional to b 2 (bþ1) response are the same across the spatial domain. 1/f , then s /f is proportional to 1/f . Populations in fragmented habitats with barriers to Manuscript received 30 January 2008; revised 5 August 2008; spread or connected by complex corridors, such as rivers accepted 13 August 2008. Corresponding Editor: S. G. Morgan. and streams, make application of variance scale methods 5 E-mail: [email protected] difficult, since evaluating distance between sites must 1242 May 2009 SCALE AND VARIANCE OF INTERTIDAL SPECIES 1243 take account of these barriers to properly represent the numerically to high food supply on small scales over spatial structure of the data. This applies particularly to short timescales (Fischer-Piette 1935, Hughes and sites on convoluted coastlines and islands. Simple Burrows 1993), all processes injecting variance on small geographical coordinates are not representative: sites scales. Comparing variance spectra for rocky-shore on opposite sides of an isthmus may be geographically species at different trophic levels allowed us to test the close (,10 km), but distant from each other by sea generality of the hypothesis that higher-trophic-level (.100 km). Such problems can be overcome using least- species have flatter variance spectra. cost distance models (e.g., Adriaensen et al. 2003) to The mode of reproductive dispersal of an organism determine shortest routes between sites through biolog- also affects its variability over different spatial scales. ically feasible connections; we use this approach in this Short-distance dispersal can result in greater small-scale paper. variability (Johnson et al. 2001) than long-range Application of this method has allowed us to test dispersal. The latter may reduce small-scale variability hypotheses about the general form of variance spectra of by synchronizing population fluctuations in neighboring abundance of species within their geographical ranges. sites (Burrows et al. 2002), by stabilizing interactions Our first hypothesis was that variance spectra for species between strongly interacting species (Hassell et al. 1994), distributions reflect underlying variance in habitat quality and by regularly reestablishing populations in small or quantity over different spatial scales. Species from areas where stochastic processes may otherwise lead to topographically more complex habitats should show extinction. By comparing variance spectra of short- greater variability on smaller scales than those from more distance dispersers with spectra of long-distance dis- uniform habitats, since habitat-related effects on abun- persers, we tested our third hypothesis: that long- dance vary more on smaller scales in complex habitats distance dispersal leads to less variability on smaller than in homogeneous habitats. For intertidal habitats, spatial scales. straight, uniform coasts should have less small-scale The final pattern may depend upon the balance variability than indented or fragmented coasts made up between intrinsic (such as behaviour and population of shores of varying soft and hard substrata. Around the dynamics) and extrinsic (responses to environment and United Kingdom, the fjordic landscape of west Scotland is other species) influences on scales of
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