Complex animal distribution and abundance from memory-dependent kinetics

Abstract A realistic implementation of population kinetics, i.e., the transformation of individual movements to population mixing, intraspecific cohesion, site fidelity effects and other statistical mechanical aspects of population dynamics, is crucial for spatio-temporal modeling in ecology. Spatial memory effects on movements and homing are currently not realistically implemented in population dynamical modeling, which is based on an assumption of memory-free random walk and diffusion processes beyond fine-scaled behavior. We suggest a generic model where the animal relates to its familiar space strategically, by utilizing historic information for spatial memory mapping of its environment beyond its instant field of perception. Simulations illustrate how this mechanism may self-organize a scale-free, or fractal, habitat utilization even in a homogeneous environment, over a potentially large range of spatial scales. By tuning parameters for fractal dimension of step length distributions and return probability to previous locations, a continuum from a scale-free, memory-influenced displacement process to a classic, scale-specific and memory-free random walk-like process is achieved. Individual series of locations are superimposed with a varying degree of inter-connectedness to explore memory-influenced space use patterns in the context of population kinetics, i.e., by considering an ensemble of model individuals utilizing the same environment at the same time. A memory-dependent transition towards inter-individual dependency of space use is described as “intraspecific cohesion”.

[1]  Arild O. Gautestad,et al.  Fractal analysis of population ranges: methodological problems and challenges , 1994 .

[2]  Kevin J. Gaston,et al.  The geographical range structure of the holly leaf‐miner. I. Population density , 2002 .

[3]  G. C. Stevens,et al.  Spatial Variation in Abundance , 1995 .

[4]  J. Stamps,et al.  The effect of conspecifics on habitat selection in territorial species , 2004, Behavioral Ecology and Sociobiology.

[5]  L. Barrett,et al.  Random walks and the gas model: spacing behaviour of Grey-Cheeked Mangabeys , 1998 .

[6]  P. Turchin Quantitative analysis of movement : measuring and modeling population redistribution in animals and plants , 1998 .

[7]  H. Stanley,et al.  Lévy flights in random searches , 2000 .

[8]  David Saltz,et al.  Forging at Different Spatial Scales: Dorcas Gazelles Foraging for Lilies in the Negev Desert , 1994 .

[9]  P. A. Prince,et al.  Lévy flight search patterns of wandering albatrosses , 1996, Nature.

[10]  L. Taylor,et al.  Synoptic Dynamics, Migration and the Rothamsted Insect Survey: Presidential Address to the British Ecological Society, December 1984 , 1986 .

[11]  Michel Baguette,et al.  Long distance dispersal and landscape occupancy in a metapopulation of the cranberry fritillary butterfly , 2003 .

[12]  Arild O. Gautestad,et al.  The home range ghost , 1995 .

[13]  N. C. Kenkel,et al.  Fractal-Based Spatial Analysis of Radiotelemetry Data , 2001 .

[14]  Stephens,et al.  Consequences of the Allee effect for behaviour, ecology and conservation. , 1999, Trends in ecology & evolution.

[15]  Richard S. Ostfeld,et al.  Long-distance homing in meadow voles, Microtus pennsylvanicus , 1996 .

[16]  Erik Matthysen,et al.  Local recruitment of great and blue tits (Parus major, P. caeruleus) in relation to study plot size and degree of isolation , 2001 .

[17]  Ran Nathan,et al.  The challenges of studying dispersal , 2001 .

[18]  J. Michael Scott,et al.  Predicting Species Occurrences: Issues of Accuracy and Scale , 2002 .

[19]  B. Christensen,et al.  Studies on Enchytraeidae IV , 2004, Chromosoma.

[20]  J. Stamps Conspecific Attraction and Aggregation in Territorial Species , 1988, The American Naturalist.

[21]  William A. Searcy,et al.  Song repertoires and density assessment in red-winged blackbirds: further tests of the Beau Geste hypothesis , 2004, Behavioral Ecology and Sociobiology.

[22]  Travis Dispersal functions and spatial models: expanding our dispersal toolbox , 2000 .

[23]  T. Caro,et al.  Behavioral ecology and conservation biology , 1998 .

[24]  Joshua J. Millspaugh,et al.  Radio Tracking and Animal Populations , 2001 .

[25]  Johan Elmberg,et al.  Habitat selection rules in breeding mallards (Anas platyrhynchos): a test of two competing hypotheses , 1998, Oecologia.

[26]  S. Hartley,et al.  Uses and abuses of fractal methodology in ecology , 2004 .

[27]  P. Välimäki,et al.  Migration of the clouded Apollo butterfly Parnassius mnemosyne in a network of suitable habitats – effects of patch characteristics , 2003 .

[28]  Arild O. Gautestad,et al.  Are home ranges fractals? , 1994, Landscape Ecology.

[29]  Stephen R. Baillie,et al.  Patterns of natal and breeding dispersal in birds , 1998 .

[30]  S. Wright,et al.  Genetics of Natural Populations. X. Dispersion Rates in Drosophila Pseudoobscura. , 1943, Genetics.

[31]  George Salt,et al.  Studies of Wireworm Populations: II. Spatial Distribution , 1946 .

[32]  B. Cole Fractal time in animal behaviour: the movement activity of Drosophila , 1995, Animal Behaviour.

[33]  H. Pulliam,et al.  Sources, Sinks, and Habitat Selection: A Landscape Perspective on Population Dynamics , 1991, The American Naturalist.

[34]  Arild O. Gautestad,et al.  Intrinsic Scaling Complexity in Animal Dispersion and Abundance , 2004, The American Naturalist.

[35]  Juan C. Alonso,et al.  Habitat preferences of great bustard Otis tarda flocks in the arable steppes of central Spain: are potentially suitable areas unoccupied? , 2001 .

[36]  Lars Chittka,et al.  Navigation without vision: bumblebee orientation in complete darkness , 1999, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[37]  C. O. Nielsen,et al.  STUDIES ON ENCHYTRAEIDAE 3. THE MICRO-DISTRIBUTION OF ENCHYTRAEIDAE , 1954 .

[38]  G Sugihara,et al.  Applications of fractals in ecology. , 1990, Trends in ecology & evolution.

[39]  Benoit B. Mandelbrot,et al.  Fractal Geometry of Nature , 1984 .

[40]  G. Orians,et al.  Familiar neighbors enhance breeding success in birds. , 1989, Proceedings of the National Academy of Sciences of the United States of America.

[41]  C. M. Perrins,et al.  Natal dispersal in a heterogeneous environment : the case of the Great Tit in Wytham , 1996 .

[42]  J. Schieck,et al.  Breeding site fidelity in willow ptarmigan: the influence of previous reproductive success and familiarity with partner and territory , 1989, Oecologia.

[43]  Stanley,et al.  Stochastic process with ultraslow convergence to a Gaussian: The truncated Lévy flight. , 1994, Physical review letters.

[44]  H. Stanley,et al.  Optimizing the success of random searches , 1999, Nature.

[45]  Andrew T. Smith,et al.  Conspecific Attraction and the Determination of Metapopulation Colonization Rates , 1990 .

[46]  Grenfell,et al.  Inverse density dependence and the Allee effect. , 1999, Trends in ecology & evolution.

[47]  Arild O. Gautestad,et al.  Physical and biological mechanisms in animal movement processes , 1993 .

[48]  S. Healy Spatial representation in animals. , 1998 .

[49]  Bai-Lian Li,et al.  Fractal geometry applications in description and analysis of patch patterns and patch dynamics , 2000 .

[50]  T. J. Roper,et al.  Non-random dispersal in the butterfly Maniola jurtina: implications for metapopulation models , 2000, Proceedings of the Royal Society of London. Series B: Biological Sciences.