Patchiness of macrobenthic invertebrates in homogenized intertidal habitats: hidden spatial structure at a landscape scale

Many terrestrial habitats, and certainly man-made systems such as woodland and agri- cultural habitats, are characterised by a mosaic of different habitat types. In contrast, most seafloors have a rather uniform visual appearance which is enhanced by the cryptic nature of many of their inhabitants. The present study aimed to: (1) describe landscape scale spatial patterns of benthic infauna after evaluating 3 methods for analyzing autocorrelations (Moran's I, semivariance and frac- tals), (2) compare the benthic patterns with patterns described for other organisms, and (3) highlight shared characteristics. During 4 consecutive years (2002 to 2005) we assessed spatial structuring of 4 intertidal benthic invertebrates (Cerastoderma edule, Macoma balthica, Nereis diversicolor and Nepthys hombergii) in the Wadden Sea, The Netherlands. We annually sampled ~2750 stations based on a 250 m grid, covering an area of ca. 225 km 2 . On the basis of simulated spatial distributions, we selected Moran's I to analyze spatial patterns for the following reasons: (1) due to standardization, results can be directly compared, (2) Moran's I is the least difficult to evaluate, since it is related to the familiar Pearson's correlation coefficient, and (3) significance can readily be assessed. The 4 benthic species were all spatially structured at the landscape scale, with spatial features being smaller than the physical structure of the intertidal environment, i.e. the intertidal extent. During the 4 yr, some species changed their distribution, but spatial characteristics, i.e. patch size and amplitude of auto- correlation, remained similar. Higher overall density resulted in stronger autocorrelation with no dif- ferences between species. A comparison between spatial structuring of benthic fauna with patterns encountered in other habitats, whether marine or terrestrial, was unsuccessful due to differences in extent and grain. We argue that future research should focus on spatial structure in species' distrib- utions as an ecological relevant parameter.

[1]  N. Dankers,et al.  The role of the mussel (Mytilus edulis L.) and mussel culture in the Dutch Wadden Sea , 1995 .

[2]  K. Reise.  Spatial configurations generated by motile benthic polychaetes , 1979, Helgoländer wissenschaftliche Meeresuntersuchungen.

[3]  Erik Bonsdorff,et al.  Small-scale spatial structure of Baltic Sea zoobenthos—inferring processes from patterns , 2002 .

[4]  Simon F. Thrush,et al.  Assessing the short‐term stability of spatial patterns of macrobenthos in a dynamic estuarine system , 1997 .

[5]  K. Erikstad,et al.  Seabirds and marine oil incidents: is it possible to predict the spatial distribution of pelagic seabirds? , 2002 .

[6]  Marie-Josée Fortin,et al.  Spatial autocorrelation and sampling design in plant ecology , 1989, Vegetatio.

[7]  L. Zwarts.  Bodemgesteldheid en mechanische kokkelvisserij in de Waddenzee , 2004 .

[8]  R. Pridmore,et al.  Matching patterns with processes: predicting the effect of size and mobility on the spatial distributions of the bivalves Macomona liliana and Austrovenus stutchburyi , 1996 .

[9]  Pierre Legendre,et al.  Multiscale sources of variation in ecological variables: modeling spatial dispersion, elaborating sampling designs , 1998, Landscape Ecology.

[10]  Jaap van der Meer,et al.  Sampling design of monitoring programmes for marine benthos: a comparison between the use of fixed versus randomly selected stations , 1997 .

[11]  J. Beukema,et al.  Year-to-year variability in the biomass of macrobenthic animals on tidal flats of the Wadden Sea: How predictable is this food source for birds? , 1993 .

[12]  R. Cole,et al.  Using spatial pattern analysis to distinguish causes of mortality: an example from kelp in north‐eastern New Zealand , 1999 .

[13]  Jennifer L. Dungan,et al.  Illustrations and guidelines for selecting statistical methods for quantifying spatial pattern in ecological data , 2002 .

[14]  Wenzhi Zhao,et al.  The modifiable areal unit problem of spatial heterogeneity of plant community in the transitional zone between oasis and desert using semivariance analysis , 2007, Landscape Ecology.

[15]  P. Burrough.  Fractal dimensions of landscapes and other environmental data , 1981, Nature.

[16]  A. Stewart,et al.  The world is heterogeneous: ecological consequences of living in a patchy environment , 2000 .

[17]  F. Volckaert.  Spatial pattern of soft-bottom Polychaeta off Nova Scotia, Canada , 1987 .

[18]  Bart A Nolet,et al.  Movement of foraging Tundra Swans explained by spatial pattern in cryptic food densities. , 2006, Ecology.

[19]  Jaap van der Meer,et al.  Assessing the population size of the European storm petrel (Hydrobates pelagicus) using spatial autocorrelation between counts from segments of criss-cross ship transects , 1995 .

[20]  R. Pridmore,et al.  IMPACTS ON SOFT-SEDIMENT MACROFAUNA: THE EFFECTS OF SPATIAL VARIATION ON TEMPORAL TRENDS' , 1994 .

[21]  J. Pinckney,et al.  Spatial autocorrelation analysis of meiofaunal and microalgal populations on an intertidal sandflat: Scale linkage between consumers and resources , 1990 .

[22]  R. G. Davies,et al.  Methods to account for spatial autocorrelation in the analysis of species distributional data : a review , 2007 .

[23]  D M Foster,et al.  Statistical Analysis of Spatial Pattern: A Comparison of Grid and Hierarchical Sampling Approaches , 2001, Environmental monitoring and assessment.

[24]  P. Moran.  Notes on continuous stochastic phenomena. , 1950, Biometrika.

[25]  Theunis Piersma,et al.  Shellfish Dredging Pushes a Flexible Avian Top Predator out of a Marine Protected Area , 2006, PLoS biology.

[26]  M. Araújo,et al.  Consequences of spatial autocorrelation for niche‐based models , 2006 .

[27]  Theunis Piersma,et al.  Scale and intensity of intertidal habitat use by knots Calidris canutus in the Western Wadden Sea in relation to food, friends and foes , 1993 .

[28]  S. Thrush,et al.  The effect of changing sampling scales on our ability to detect effects of large-scale processes on communities , 1998 .

[29]  F. Maestre,et al.  Spatial associations and patterns of perennial vegetation ina semi-arid steppe: a multivariate geostatistics approach , 2005, Plant Ecology.

[30]  Pierre Legendre,et al.  Untangling Multiple Factors in Spatial Distributions: Lilies, Gophers, and Rocks , 1996 .

[31]  E. Flach.  The Influence of the Cockle, Cerastoderma edule, on the Macrozoobenthic Community of Tidal Flats in the Wadden Sea , 1996 .

[32]  M. Fortin,et al.  Spatial pattern and ecological analysis , 1989, Vegetatio.

[33]  David C. Schneider,et al.  Spatial structure of bivalves in a sandflat:: Scale and generating processes , 1997 .

[34]  Leslie A. Real,et al.  Spatial pattern and process in plant-pathogen interactions , 1996 .

[35]  L. Zwarts,et al.  How the food supply harvestable by waders in the Wadden Sea depends on the variation in energy density, body weight, biomass, burying depth and behaviour of tidal-flat invertebrates , 1993 .

[36]  R. Lord,et al.  The Pattern of Animal Communities , 1967 .

[37]  C. Chocarro,et al.  Spatial patterns in seed bank and vegetation of semi-natural mountain meadows , 2006, Plant Ecology.

[38]  J. Verwey.  On the Ecology of Distribution of Cockle and Mussel in the Dutch Waddensea, Their Role in Sedimentation and the Source of Their Food Supply , 1954 .

[39]  C. Peterson.  Intertidal Zonation of Marine Invertebrates in Sand and Mud , 1991 .

[40]  A. J. Underwood,et al.  Spatial variation in soft-sediment benthos , 1992 .

[41]  M. Fortin.  Effects of sampling unit resolution on the estimation of spatial autocorrelation , 1999 .

[42]  A. Sparrow,et al.  A heterogeneity of heterogeneities. , 1999, Trends in ecology & evolution.

[43]  M. Huxham,et al.  Can postlarval bivalves select sediment type during settlement? A field test with Macoma balthica (L.) and Cerastoderma edule (L.) , 2003 .

[44]  R. Pridmore,et al.  Patterns in the spatial arrangements of polychaetes and bivalves in intertidal sandflats , 1989 .

[45]  David J. Mulla,et al.  Geostatistical Tools for Modeling and Interpreting Ecological Spatial Dependence , 1992 .

[46]  Thiago F. Rangel,et al.  Towards an integrated computational tool for spatial analysis in macroecology and biogeography , 2006 .

[47]  R. Macarthur.  The Problem of Pattern and Scale in Ecology: The Robert H. MacArthur Award Lecture , 2005 .

[48]  Elliott A. Norse,et al.  Disturbance of the Seabed by Mobile Fishing Gear: A Comparison to Forest Clearcutting , 1998 .

[49]  M. Fortin,et al.  Spatial Analysis: A Guide for Ecologists 1st edition , 2005 .

[50]  Pierre Legendre,et al.  Identifying relationships between adult and juvenile bivalves at different spatial scales , 1997 .

[51]  J. Keith Ord,et al.  Spatial Processes Models and Applications , 1981 .

[52]  S. Andelman,et al.  COMPARING MARINE AND TERRESTRIAL ECOSYSTEMS: IMPLICATIONS FOR THE DESIGN OF COASTAL MARINE RESERVES , 2003 .

[53]  R. Sokal,et al.  Spatial autocorrelation in biology: 1. Methodology , 1978 .

[54]  R. Hobbs,et al.  Key issues and research priorities in landscape ecology: An idiosyncratic synthesis , 2002, Landscape Ecology.

[55]  François Gillet,et al.  Spatial and Seasonal Patterns of Cattle Habitat use in a Mountain Wooded Pasture , 2006, Landscape Ecology.

[56]  J. Pinckney,et al.  Patch sizes and spatial patterns of meiobenthic copepods and benthic microalgae in sandy sediments: a microscale approach , 1999 .

[57]  K. Gaston,et al.  The University of Chicago Species Richness , Environmental Correlates , and Spatial Scale : A Test Using South African Birds , 2002 .

[58]  M. Jones,et al.  Detecting two-dimensional spatial structure in biological data , 1977, Oecologia.

[59]  Theunis Piersma,et al.  Long‐term indirect effects of mechanical cockle‐dredging on intertidal bivalve stocks in the Wadden Sea , 2001 .

[60]  J. Beukema,et al.  Relations of summer and winter temperatures with dynamics and growth of two bivalves, Tellina tenuis and Abra tenuis, on the northern edge of their intertidal distribution , 1999 .

[61]  Measurement of density variability in the bivalve Chione stutchburyi using spatial autocorrelation , 1989 .

[62]  C. Kraan,et al.  Dredging for edible cockles (Cerastoderma edule) on intertidal flats: short-term consequences of fisher patch-choice decisions for target and non-target benthic fauna , 2007 .

[63]  Theunis Piersma,et al.  Foraging in a tidally structured environment by Red Knots (Calidris canutus): ideal, but not free. , 2006, Ecology.

[64]  Pierre Legendre,et al.  Diversity pattern and spatial scale: a study of a tropical rain forest of Malaysia , 1994, Environmental and Ecological Statistics.

[65]  M. Palmer,et al.  Fractal geometry: a tool for describing spatial patterns of plant communities , 1988, Vegetatio.

[66]  S. Thrush.  Spatial patterns in soft-bottom communities. , 1991, Trends in ecology & evolution.