SEARCH

SEARCH BY CITATION

References

  • Addley, R.C. 1993. A mechanistic approach to modeling habitat needs of drift-feeding salmonids. M.Sc. thesis. Logan, UT: Utah State University, 141 pp.
  • Addley, R.C. 2006. Habitat modeling of river ecosystems: multidimensional spatially explicit and dynamic habitat templates at scales relevant to fish. Ph.D. thesis. Logan, UT: Utah State University, 206 pp.
  • Ahmadi Nedushan, B., St-Hilaire, A., Berube, M., Robichaud, E., Thiemonge, N. & Bobee, B. 2006. A review of statistical methods for the evaluation of aquatic habitat suitability for instream flow assessment. River Research and Applications 22: 503523.
  • Alfredsen, K., Borsanyi, P., Harby, A., Fjeldstad, H.P. & Wersland, S.E. 2004. Application of habitat modelling in river rehabilitation and artificial habitat design. Hydroécologie Appliquée 14: 105117.
  • Allendorf, F. & Luikart, G. 2007. Conservation and the genetics of populations. Malden, MA: Wiley-Blackwell. 664 pp.
  • Almodovar, A., Nicola, G.G. & Elvira, B. 2006. Spatial variation in brown trout production: the role of environmental factors. Transactions of the American Fisheries Society 135: 13481360.
  • Anderson, K., Paul, A., McCauley, E., Jackson, L., Post, J. & Nisbet, R. 2006. Instream flow needs in streams and rivers: the importance of understanding ecological dynamics. Frontiers in Ecology and the Environment 4: 309318.
  • Anderson, C.D., Epperson, B.K., Fortin, M.J., Holderegger, R., James, P.M.A., Rosenberg, M.S., Scribner, K.T. & Spear, S. 2010. Considering spatial and temporal scale in landscape-genetic studies of gene flow. Molecular Ecology 19: 35653575.
  • Angers, B., Magnan, P., Plante, M. & Bernatchez, L. 1999. Canonical correspondence analysis for estimating spatial and environmental effects on microsatellite gene diversity in brook charr (Salvelinus fontinalis). Molecular Ecology 8: 10431053.
  • Antunes, A., Faria, R., Johnson, W., Guyomard, R. & Alexandrino, P. 2006. Life on the edge: the long-term persistence and contrasting spatial genetic structure of distinct brown trout life histories at their ecological limits. Journal of Heredity 97: 193205.
  • Apostolidis, A., Karakousis, Y. & Triantaphyllidis, C. 1996. Genetic divergence and phylogenetic relationships among Salmo trutta L (brown trout) populations from Greece and other European countries. Heredity 76: 551560.
  • Apostolidis, A., Madeira, M., Hansen, M. & Machordom, A. 2008. Genetic structure and demographic history of brown trout (Salmo trutta) populations from the southern Balkans. Freshwater Biology 53: 15551566.
  • Araneda, C., Neira, R. & Iturra, P. 2005. Identification of a dominant SCAR marker associated with colour traits in Coho salmon (Oncorhynchus kisutch). Aquaculture 247: 6773.
  • Armstrong, J., Kemp, P., Kennedy, G., Ladle, M. & Milner, N. 2003. Habitat requirements of Atlantic salmon and brown trout in rivers and streams. Fisheries Research 62: 143170.
  • Aurelle, D. & Berrebi, P. 1998. Microsatellite markers and management of brown trout Salmo trutta fario populations in southwestern France. Genetics Selection Evolution 30: S75S90.
  • Ayllon, F., Moran, P. & Garcia-Vazquez, E. 2006. Maintenance of a small anadromous subpopulation of brown trout (Salmo trutta L.) by straying. Freshwater Biology 51: 351358.
  • Ayllon, D., Almodovar, A., Nicola, G. & Elvira, B. 2010. Modelling brown trout spatial requirements through physical habitat simulations. River Research and Applications 26: 10901102.
  • Balkenhol, N., Gugerli, F., Cushman, S.A., Waits, L.P., Coulon, A., Arntzen, J.W., Holderegger, R. & Wagner, H.H. 2009a. Identifying future research needs in landscape genetics: where to from here? Landscape Ecology 24: 455463.
  • Balkenhol, N., Waits, L.P. & Dezzani, R.J. 2009b. Statistical approaches in landscape genetics: an evaluation of methods for linking landscape and genetic data. Ecography 32: 818830.
  • Balloux, F. 2001. EASYPOP (version 1.7): a computer program for population genetics simulations. Journal of Heredity 92: 301302.
  • Baran, P., Delacoste, M., Dauba, F., Lascaux, J.M., Belaud, A. & Lek, S. 1995. Effects of reduced flow on brown trout (Salmo trutta L.) populations downstream dams in French Pyrenees. Regulated Rivers: Research & Management 10: 347361.
  • Baran, P., Lek, S., Delacoste, M. & Belaud, A. 1996. Stochastic models that predict trout population density or biomass on a mesohabitat scale. Hydrobiologia 337: 19.
  • Barnard, S., Wyatt, R.J. & Milner, N.J. 1995. The development of habitat models for stream salmonids, and their application to fisheries management. Bulletin Français de la Pêche et de la Pisciculture 337–9: 375385.
  • Bartholow, J. 1996. Sensitivity of a salmon population model to alternative formulations and initial conditions. Ecological Modelling 88: 215226.
  • Beaumont, M.A., Zhang, W.Y. & Balding, D.J. 2002. Approximate Bayesian computation in population genetics. Genetics 162: 20252035.
  • Beerli, P. 2006. Comparison of bayesian and maximum-likelihood inference of population genetic parameters. Bioinformatics 22: 341345.
  • Beerli, P. & Felsenstein, J. 2001. Maximum likelihood estimation of a migration matrix and effective population sizes in n subpopulations by using a coalescent approach. Proceedings of the National Academy of Sciences of the United States of America 98: 45634568.
  • Belaud, A., Chaveroche, P., Lim, P. & Sabaton, C. 1989. Probability-of-use curves applied to brown trout (Salmo trutta fario L.) in rivers of southern France. Regulated Rivers: Research & Management 3: 321336.
  • Belkhir, K., Borsa, P., Chikhi, L., Raufaste, N. & Bonhomme, F. 2004. GENETIX 4.05, logiciel sous Windows TM pour la génétique des populations. Montpellier, France: Université de Montpellier II. Available at: http://www.genetix.univ-montp2.fr.
  • Bell, V., Elliott, J. & Moore, R. 2000. Modelling the effects of drought on the population of brown trout in Black Brows Beck. Ecological Modelling 127: 141159.
  • Bernatchez, L. 2001. The evolutionary history of brown trout (Salmo trutta L.) inferred from phylogeographic, nested clade, and mismatch analyses of mitochondrial DNA variation. Evolution 55: 351379.
  • Berthier, P., Beaumont, M.A., Cornuet, J.M. & Luikart, G. 2002. Likelihood-based estimation of the effective population size using temporal changes in allele frequencies: a genealogical approach. Genetics 160: 741751.
  • Bertorelle, G., Benazzo, A. & Mona, S. 2010. ABC as a flexible framework to estimate demography over space and time: some cons, many pros. Molecular Ecology 19: 26092625.
  • Beverton, R. & Holt, S. 1957. On the dynamics of exploited fish populations, vol. XIX of II. London: Fishery Investment. 533 pp.
  • Bolker, B.M. 2008. Ecological models and data in R. Princeton, NJ: Princeton University Press. 408 pp.
  • Booker, D. & Dunbar, M. 2004. Application of physical habitat simulation (PHABSIM) modelling to modified urban river channels. River Research and Applications 20: 167183.
  • Booker, D., Dunbar, M. & Ibbotson, A. 2004. Predicting juvenile salmonid drift-feeding habitat quality using a three-dimensional hydraulic-bioenergetic model. Ecological Modelling 177: 157177.
  • Borg, D. & Roy, A. 2006. Physical habitat simulation predicts good news for Pretty Valley aquatic biota. Proceedings of the 9th International Riversymposium, 4–7 September, Brisbane, Australia.
  • Borsuk, M., Reichert, P., Peter, A., Schager, E. & Burkhardt-Holm, P. 2006. Assessing the decline of brown trout (Salmo trutta) in Swiss rivers using a Bayesian probability network. Ecological Modelling 192: 224244.
  • Bouza, C., Arias, J., Castro, J., Sanchez, L. & Martinez, P. 1999. Genetic structure of brown trout, Salmo trutta L., at the southern limit of the distribution range of the anadromous form. Molecular Ecology 8: 19912001.
  • Bouza, C., Castro, J., Sanchez, L. & Martinez, P. 2001. Allozymic evidence of parapatric differentiation of brown trout (Salmo trutta L.) within an Atlantic river basin of the Iberian Peninsula. Molecular Ecology 10: 14551469.
  • Bovee, K. 1982. A guide to stream habitat analysis using the instream flow incremental methodology, U.S. Fish and Wildlife Service, Instream Flow Information Paper 12, Report FWS/OBS-82/26, 248 pp.
  • Bovee, K. 1986. Development and evaluation of habitat suitability criteria for use in the instream flow incremental methodology. U.S. Fish and Wildlife Service, Instream Flow Information Paper 21, Biological Report 86: 7, 235 pp.
  • Bovee, K., Lamb, B., Bartholow, J., Stalnaker, C., Taylor, J. & Henriksen, J. 1998. Stream habitat analysis using the instream flow incremental methodology, U.S. Geological Survey, Biological Resources Division, Information and Technology Report USGS/BRD-1998-0004, 131 pp.
  • Braaten, P.J., Dey, P.D. & Annear, T.C. 1997. Development and evaluation of bioenergetic-based habitat suitability criteria for trout. Regulated Rivers: Research & Management 13: 345356.
  • Brannas, E., Jonsson, S. & Lundqvist, H. 2003. Influence of food abundance on individual behaviour strategy and growth rate in juvenile brown trout (Salmo trutta). Canadian Journal of Zoology 81: 684691.
  • Breckling, B. 2002. Individual-based modelling: potentials and limitations. Scientific World Journal 2: 10441062.
  • Breckling, B., Muller, F., Reuter, H., Holker, F. & Franzle, O. 2005. Emergent properties in individual-based ecological models: introducing case studies in an ecosystem research context. Ecological Modelling 186: 376388.
  • Breckling, B., Middelhoff, U. & Reuter, H. 2006. Individual-based models as tools for ecological theory and application: understanding the emergence of organisational properties in ecological systems. Ecological Modelling 194: 102113.
  • Broquet, T. & Petit, E.J. 2009. Molecular estimation of dispersal for ecology and population genetics. Annual Review of Ecology Evolution and Systematics 40: 193216.
  • Bruggeman, D., Wiegand, T. & Fernandez, N. 2010. The relative effects of habitat loss and fragmentation on population genetic variation in the red-cockaded woodpecker (Picoides borealis). Molecular Ecology 19: 36793691.
  • Buckland, S. & Elston, D. 1993. Empirical-models for the spatial-distribution of wildlife. Journal of Applied Ecology 30: 478495.
  • Buckland, S., Newman, K., Thomas, L. & Koesters, N. 2004. State-space models for the dynamics of wild animal populations. Ecological Modelling 171: 157175.
  • Buckland, S., Newman, K., Fernandez, C., Thomas, L. & Harwood, J. 2007. Embedding population dynamics models in inference. Statistical Science 22: 4458.
  • Budy, P., Thiede, G., McHugh, P., Hansen, E. & Wood, J. 2008. Exploring the relative influence of biotic interactions and environmental conditions on the abundance and distribution of exotic brown trout (Salmo trutta) in a high mountain stream. Ecology of Freshwater Fish 17: 554566.
  • Burkhardt-Holm, P. 2008. Decline of brown trout (Salmo trutta) in Switzerland – How to assess potential causes in a multi-factorial cause-effect relationship? Marine Environmental Research 66: 181182.
  • Butts, C. 2008. Network: a package for managing relational data in R. Journal of Statistical Software 24: 136.
  • Butts, C., Handcock, M. & Hunter, D. 2008. Network: classes for relational data. Irvine, CA. R package version 1.4-1, http://statnet.org.
  • Campos, J.L., Posada, D. & Moran, P. 2006. Genetic variation at MHC, mitochondrial and microsatellite loci in isolated populations of brown trout (Salmo trutta). Conservation Genetics 7: 515530.
  • Campos, J.L., Posada, D., Caballero, P. & Moran, P. 2007. Spatio-temporal genetic variability in sea trout (Salmo trutta) populations from north-western Spain. Freshwater Biology 52: 510524.
  • Capra, H., Sabaton, C., Gouraud, V., Souchon, Y. & Lim, P. 2003. A population dynamics model and habitat simulation as a tool to predict brown trout demography in natural and bypassed stream reaches. River Research and Applications 19: 551568.
  • Carlsson, J. 2007. The effect of family structure on the likelihood for kin-biased distribution: an empirical study of brown trout populations. Journal of Fish Biology 71: 98110.
  • Carlsson, J. & Nilsson, J. 2000. Population genetic structure of brown trout (Salmo trutta L.) within a northern boreal forest stream. Hereditas 132: 173181.
  • Carlsson, J., Olsen, K., Nilsson, J., Overli, O. & Stabell, O. 1999. Microsatellites reveal fine-scale genetic structure in stream-living brown trout. Journal of Fish Biology 55: 12901303.
  • Carvalho, G.R. & Hauser, L. 1998. Advances in the molecular analysis of fish population structure. The Italian Journal of Zoology 65: 2133.
  • Castric, V., Bernatchez, L., Belkhir, K. & Bonhomme, F. 2002. Heterozygote deficiencies in small lacustrine populations of brook charr Salvelinus Fontinalis Mitchill (Pisces, Salmonidae): a test of alternative hypotheses. Heredity 89: 2735.
  • Caswell, H. 2001. Matrix population models: construction, analysis and interpretation, 2nd Revised edn. Sunderland, MA: Sinauer Associates. 722 pp.
  • Cattaneo, F., Lamouroux, N., Breil, P. & Capra, H. 2002. The influence of hydrological and biotic processes on brown trout (Salmo trutta) population dynamics. Canadian Journal of Fisheries and Aquatic Sciences 59: 1222.
  • Cattaneo, F., Hugueny, B. & Lamouroux, N. 2003. Synchrony in brown trout, Salmo trutta, population dynamics: a Moran effect on early-life stages. Oikos 100: 4354.
  • Caudron, A., Champigneulle, A., Guyomard, R. & Largiader, C.R. 2010. Assessment of three strategies practiced by fishery managers for restoring native brown trout (Salmo trutta) populations in Northern French Alpine Streams. Ecology of Freshwater Fish. DOI: 10.1111/j.1600-0633.2010.00458.x.
  • Cercueil, A., Bellemain, E. & Manel, S. 2002. PARENTE: computer program for parentage analysis. Journal of Heredity 93: 458459.
  • Chakraborty, R., Haag, M., Ryman, N. & Stahl, G. 1982. Hierarchical gene diversity analysis and its application to brown trout population-data. Hereditas 97: 1721.
  • Charles, S., Bravo de la Parra, R., Mallet, J.P., Persat, H. & Auger, P. 1998. Population dynamics modelling in an hierarchical arborescent river network: an attempt with Salmo trutta. Acta Biotheoretica 46: 223234.
  • Charles, S., Bravo de la Parra, R., Mallet, J.P., Persat, H. & Auger, P. 2000. Annual spawning migrations in modelling brown trout population dynamics inside an arborescent river network. Ecological Modelling 133: 1531.
  • Charlesworth, B. 2009. Effective population size and patterns of molecular evolution and variation. Nature Reviews Genetics 10: 195205.
  • Chen, C., Durand, E., Forbes, F. & François, O. 2007. Bayesian clustering algorithms ascertaining spatial population structure: a new computer program and a comparison study. Molecular Ecology Notes 7: 747756.
  • Clark, J., Rizzo, D., Watzin, M. & Hession, W. 2008. Spatial distribution and geomorphic condition of fish habitat in streams: an analysis using hydraulic modelling and geostatistics. River Research and Applications 24: 885899.
  • Clausen, B., Jowett, I., Biggs, B. & Moeslund, B. 2004. Stream ecology and flow management, Elsevier, chap. 10: Hydrological drought: processes and estimation methods for streamflow and groundwater, pp. 411453.
  • Coombs, J., Letcher, B. & Nislow, K. 2010. PEDAGOG: software for simulating eco-evolutionary population dynamics. Molecular Ecology Resources 10: 558563.
  • Corander, J. & Marttinen, P. 2006. Bayesian identification of admixture events using multilocus molecular markers. Molecular Ecology 15: 28332843.
  • Cornuet, J., Piry, S., Luikart, G., Estoup, A. & Solignac, M. 1999. New methods employing multilocus genotypes to select or exclude populations as origins of individuals. Genetics 153: 19892000.
  • Cornuet, J.M., Santos, F., Beaumont, M.A., Robert, C.P., Marin, J.M., Balding, D.J., Guillemaud, T. & Estoup, A. 2008. Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation. Bioinformatics 24: 27132719.
  • Cortey, M., Vera, M., Pla, C. & Garcia-Marin, J.L. 2009. Northern and Southern expansions of Atlantic brown trout (Salmo trutta) populations during the Pleistocene. Biological Journal of the Linnean Society 97: 904917.
  • Corujo, M., Blanco, G., Vazquez, E. & Sanchez, J.A. 2004. Genetic structure of Northwestern Spanish brown trout (Salmo trutta L.) populations, differences between microsatellite and allozyme loci. Hereditas 141: 258271.
  • Costello, A., Down, T., Pollard, S., Pacas, C. & Taylor, E. 2003. The influence of history and contemporary stream hydrology on the evolution of genetic diversity within species: an examination of microsatellite DNA variation in bull trout, Salvelinus confluentus (Pisces: Salmonidae). Evolution 57: 328344.
  • Coulson, T., Tuljapurkar, S. & Childs, D. 2010. Using evolutionary demography to link life history theory, quantitative genetics and population ecology. Journal of Animal Ecology 79: 12261240.
  • Cowx, I. & Gerdeaux, D. 2004. The effects of fisheries management practises on freshwater ecosystems. Fisheries Management and Ecology 11: 145151.
  • Creque, S.M., Rutherford, E.S. & Zorn, T.G. 2005. Use of GIS-derived landscape-scale habitat features to explain spatial patterns of fish density in Michigan rivers. North American Journal of Fisheries Management 25: 14111425.
  • Csilléry, K., Blum, M.G.B., Gaggiotti, O.E. & François, O. 2010. Approximate Bayesian Computation (ABC) in practice. Trends in Ecology & Evolution 25: 410418.
  • Cucherousset, J., Aymes, J., Santoul, F. & Cereghino, R. 2007. Stable isotope evidence of trophic interactions between introduced brook trout Salvelinus fontinalis and native brown trout Salmo trutta in a mountain stream of south-west France. Journal of Fish Biology 71: 210223.
  • Currat, M., Ray, N. & Excoffier, L. 2004. SPLATCHE: a program to simulate genetic diversity taking into account environmental heterogeneity. Molecular Ecology Notes 4: 139142.
  • Daufresne, M. & Renault, O. 2006. Population fluctuations, regulation and limitation in stream-living brown trout. Oikos 113: 459468.
  • Dauwalter, D. & Rahel, F. 2008. Distribution modelling to guide stream fish conservation: an example using the mountain sucker in the Black Hills National Forest, USA. Aquatic Conservation: Marine and Freshwater Ecosystems 18: 12631276.
  • Dawson, M.N., Louie, K.D., Barlow, M., Jacobs, D.K. & Swift, C.C. 2002. Comparative phylogeography of sympatric sister species, Clevelandia ios and Eucyclogobius newberryi (Teleostei, Gobiidae), across the California Transition Zone. Molecular Ecology 11: 10651075.
  • DeAngelis, D. & Mooij, W. 2005. Individual-based modeling of ecological and evolutionary processes. Annual Review of Ecology Evolution and Systematics 36: 147168.
  • DeSalle, R. & Amato, G. 2004. The expansion of conservation genetics. Nature Reviews Genetics 5: 702712.
  • Dieterman, D., Thorn, W. & Anderson, C. 2004. Application of a bioenergetics model for brown trout to evaluate growth in Southeast Minnesota streams. Tech. Rep. 513, St. Paul, MN: Minnesota Department of Natural Resources.
  • Dillane, E., McGinnity, P., Coughlan, J., Cross, M., de Eyto, E., Kenchington, E., Prodohl, P. & Cross, T. 2008. Demographics and landscape features determine intrariver population structure in Atlantic salmon (Salmo salar L.): the case of the River Moy in Ireland. Molecular Ecology 17: 47864800.
  • Dineen, G., Harrison, S.S.C. & Giller, P.S. 2007. Growth, production and bioenergetics of brown trout in upland streams with contrasting riparian vegetation. Freshwater Biology 52: 771783.
  • Dionne, M., Caron, F., Dodson, J. & Bernatchez, L. 2008. Landscape genetics and hierarchical genetic structure in Atlantic salmon: the interaction of gene flow and local adaptation. Molecular Ecology 17: 23822396.
  • Dolinsek, I., Biron, P. & Grant, J. 2007. Assessing the effect of visual isolation on the population density of Atlantic salmon (Salmo salar) using GIS. River Research and Applications 23: 763774.
  • Duchesne, P., Godbout, M.H. & Bernatchez, L. 2002. PAPA (package for the analysis of parental allocation): a computer program for simulated and real parental allocation. Molecular Ecology Notes 2: 191193.
  • Duchesne, P., Meldgaard, T. & Berrebi, P. 2008. Parentage analysis with few contributing breeders: validation and improvement. Journal of Heredity 99: 323334.
  • Dudgeon, D., Arthington, A., Gessner, M., Kawabata, Z., Knowler, D., Leveque, C., Naiman, R., Prieur-Richard, A., Soto, D., Stiassny, M. & Sullivan, C. 2006. Freshwater biodiversity: importance, threats, status and conservation challenges. Biological Reviews of the Cambridge Philosophical Society 81: 163182.
  • Dunlop, E.S., Heino, M. & Dieckmann, U. 2009. Eco-genetic modeling of contemporary life-history evolution. Ecological Applications 19: 18151834.
  • Easterling, M.R., Ellner, S.P. & Dixon, P.M. 2000. Size-specific sensitivity: applying a new structured population model. Ecology 81: 694708.
  • Einum, S., Nislow, K., Reynolds, J. & Sutherland, W. 2008. Predicting population responses to restoration of breeding habitat in Atlantic salmon. Journal of Applied Ecology 45: 930938.
  • Eklov, A.G., Greenberg, L.A., Bronmark, C., Larsson, P. & Berglund, O. 1999. Influence of water quality, habitat and species richness on brown trout populations. Journal of Fish Biology 54: 3343.
  • Elliott, J. 1994. Quantitative ecology and the brown trout. Oxford: Oxford University Press. 304 pp.
  • Elliott, J. & Hurley, M. 1999. A new energetics model for brown trout, Salmo trutta. Freshwater Biology 42: 235246.
  • Elliott, J. & Hurley, M. 2000. Daily energy intake and growth of piscivorous brown trout, Salmo trutta. Freshwater Biology 44: 237245.
  • Ellner, S. & Guckenheimer, J. 2006. Dynamic models in biology. Princeton, NJ: Princeton University Press, chap. What are dynamic models? 352 pp.
  • Ellner, S. & Rees, M. 2006. Integral projection models for species with complex demography. American Naturalist 167: 410428.
  • Enders, E., Clarke, K., Pennell, C., Ollerhead, L. & Scruton, D. 2007. Comparison between PIT and radio telemetry to evaluate winter habitat use and activity patterns of juvenile Atlantic salmon and brown trout. Hydrobiologia 582: 231242.
  • Epperson, B.K., McRae, B.H., Scribner, K., Cushman, S.A., Rosenberg, M.S., Fortin, M.J., James, P.M.A., Murphy, M., Manel, S., Legendre, P. & Dale, M.R.T. 2010. Utility of computer simulations in landscape genetics. Molecular Ecology 19: 35493564.
  • Estoup, A., Rousset, F., Michalakis, Y., Cornuet, J., Adriamanga, M. & Guyomard, R. 1998. Comparative analysis of microsatellite and allozyme markers: a case study investigating microgeographic differentiation in brown trout (Salmo trutta). Molecular Ecology 7: 339353.
  • Excoffier, L. & Heckel, G. 2006. Computer programs for population genetics data analysis: a survival guide. Nature Reviews Genetics 7: 745758.
  • Excoffier, L., Novembre, J. & Schneider, S. 2000. SIMCOAL: a general coalescent program for the simulation of molecular data in interconnected populations with arbitrary demography. Journal of Heredity 91: 506509.
  • Excoffier, L., Laval, G. & Schneider, S. 2005. Arlequin 3.0: an integrated software package for population genetics data analysis. Evolutionary Bioinformatics 1: 4750.
  • Excoffier, L. & Lischer, H. 2010. Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Molecular Ecology Resources 10: 564567.
  • Falconer, D. & Mackay, T. 1996. Introduction to quantitative genetics, 4th edn. Harlow: Prentice Hall. 480 pp.
  • Fausch, K.D. 1984. Profitable stream positions for salmonids – Relating specific growth rate to net energy gain. Canadian Journal of Zoology 62: 441451.
  • Fausch, K.D. & White, R.J. 1981. Competition between brook trout (Salvelinus fontinalis) and brown trout (Salmo trutta) for positions in a Michigan stream. Canadian Journal of Fisheries and Aquatic Sciences 38: 12201227.
  • Ferguson, A. 1989. Genetic differences among brown trout, Salmo trutta L., stocks and their importance for the conservation and management of the species. Freshwater Biology 21: 3546.
  • Ferguson, A. 2004. The importance of identifying conservation units: brown trout and pollan biodiversity in Ireland. Biology and Environment: Proceedings of the Royal Irish Academy 104B: 3341.
  • Ferguson, A. 2006. Genetic impacts of stocking on indigenous brown trout populations. Tech. Rep. SCO40071/SR, Bristol: Environment Agency.
  • Filipe, A., Marques, T., Seabra, S., Tiago, P., Ribeiro, F., Da Costa, L., Cowx, I. & Collares-Pereira, M. 2004. Selection of priority areas for fish conservation in Guadiana River basin, Iberian Peninsula. Conservation Biology 18: 189200.
  • Fisher, R. 1930. The genetical theory of natural selection. Oxford: Oxford University Press, 308 pp.
  • Franco, E. & Budy, P. 2005. Effects of biotic and abiotic factors on the distribution of trout and salmon along a longitudinal stream gradient. Environmental Biology of Fishes 72: 379391.
  • François, O., Ancelet, S. & Guillot, G. 2006. Bayesian clustering using hidden Markov random fields in spatial population genetics. Genetics 174: 805816.
  • Fraser, D., Hansen, M., Ostergaard, S., Tessier, N., Legault, M. & Bernatchez, L. 2007. Comparative estimation of effective population sizes and temporal gene flow in two contrasting population systems. Molecular Ecology 16: 38663889.
  • Fukuwaka, M.A. & Morita, K. 2008. Increase in maturation size after the closure of a high seas gillnet fishery on hatchery-reared chum salmon Oncorhynchus keta. Evolutionary Applications 1: 376387.
  • Galindo, H.M., Pfeiffer-Herbert, A.S., McManus, M.A., Chao, Y., Chai, F. & Palumbi, S.R. 2010. Seascape genetics along a steep cline: using genetic patterns to test predictions of marine larval dispersal. Molecular Ecology 19: 36923707.
  • Garant, D., Dodson, J.J. & Bernatchez, L. 2003. Differential reproductive success and heritability of alternative reproductive tactics in wild Atlantic salmon (Salmo salar L.). Evolution 57: 11331141.
  • Gevrey, M., Dimopoulos, L. & Lek, S. 2003. Review and comparison of methods to study the contribution of variables in artificial neural network models. Ecological Modelling 160: 249264.
  • Gibbins, C.N. & Acornley, R.M. 2000. Salmonid habitat modelling studies and their contribution to the development of an ecologically acceptable release policy for Kielder Reservoir, North-East England. Regulated Rivers: Research & Management 16: 203224.
  • Ginot, V. 1995. EVHA, a Windows software for fish habitat assessment in streams. Bulletin Français de la Pêche et de la Pisciculture 337: 303308.
  • Gomez-Uchida, D., Dunphy, K.P., O’Connell, M.F. & Ruzzante, D.E. 2008. Genetic divergence between sympatric Arctic charr Salvelinus alpinus morphs in Gander Lake, Newfoundland: roles of migration, mutation and unequal effective population sizes. Journal of Fish Biology 73: 20402057.
  • Goslee, S.C. & Urban, D.L. 2007. The ECODIST package for dissimilarity-based analysis of ecological data. Journal of Statistical Software 22: 119.
  • Goudet, J. 1995. FSTAT (version 1.2): a computer program to calculate F-statistics. Journal of Heredity 86: 485486.
  • Goudet, J. 1999. PCA-GEN (version 1.2.1): a computer program to perform principal component analysis on gene frequency data. Lausanne, Switzerland: Lausanne University. Available at: http://www2.unil.ch/popgen/softwares/pcagen.htm.
  • Gouraud, V., Baglinière, J.L., Baran, P., Sabaton, C., Lim, P. & Ombredane, D. 2001. Factors regulating brown trout populations in two French rivers: application of a dynamic population model. Regulated Rivers: Research & Management 17: 557569.
  • Gouraud, V., Capra, H., Sabaton, C., Tissot, L., Lim, P., Vandewalle, F., Fahrner, G. & Souchon, Y. 2008. Long-term simulations of the dynamics of trout populations on river reaches bypassed by hydroelectric installations – Analysis of the impact of different hydrological scenarios. River Research and Applications 24: 11851205.
  • Gregersen, F., Haugen, T. & Larsen, O. 2006. Egg size differentiation among sympatric demes of brown trout: possible effects of density-dependent interactions among fry. Ecology of Freshwater Fish 15: 237246.
  • Grimm, V. 1999. Ten years of individual-based modelling in ecology: what have we learned and what could we learn in the future? Ecological Modelling 115: 129148.
  • Grimm, V. & Railsback, S. 2005. Individual-based modeling and ecology. Princeton, NJ: Princeton University Press. 480 pp.
  • Groeneveld, E. 1994. A reparameterization to improve numerical optimization in multivariate reml (co)variance component estimation. Genetics Selection Evolution 26: 537545.
  • Guay, J., Boisclair, D., Rioux, D., Leclerc, M., Lapointe, M. & Legendre, P. 2000. Development and validation of numerical habitat models for juveniles of Atlantic salmon (Salmo salar). Canadian Journal of Fisheries and Aquatic Sciences 57: 20652075.
  • Guensch, G., Hardy, T. & Addley, R. 2001. Examining feeding strategies and position choice of drift-feeding salmonids using an individual-based, mechanistic foraging model. Canadian Journal of Fisheries and Aquatic Sciences 58: 446457.
  • Guillaume, F. & Rougemont, J. 2006. NEMO: an evolutionary and population genetics programming framework. Bioinformatics 22: 25562557.
  • Guillot, G., Mortier, F. & Estoup, A. 2005. GENELAND: a computer package for landscape genetics. Molecular Ecology Notes 5: 712715.
  • Guillot, G., Leblois, R., Coulon, A. & Frantz, A.C. 2009. Statistical methods in spatial genetics. Molecular Ecology 18: 47344756.
  • Guisan, A. & Zimmermann, N. 2000. Predictive habitat distribution models in ecology. Ecological Modelling 135: 147186.
  • Hadfield, J.D. 2010. MCMC methods for multi-response generalized linear mixed models: the MCMCglmm R package. Journal of Statistical Software 33: 122.
  • Halleraker, J.H., Saltveit, S.J., Harby, A., Arnekleiv, J.V., Fjeldstad, H.P. & Kohler, B. 2003. Factors influencing stranding of wild juvenile brown trout (Salmo trutta) during rapid and frequent flow decreases in an artificial stream. River Research and Applications 19: 589603.
  • Hansen, M., Nielsen, E., Bekkevold, D. & Mensberg, K. 2001. Admixture analysis and stocking impact assessment in brown trout (Salmo trutta), estimated with incomplete baseline data. Canadian Journal of Fisheries and Aquatic Sciences 58: 18531860.
  • Hansen, M., Ruzzante, D., Nielsen, E., Bekkevold, D. & Mensberg, K. 2002. Long-term effective population sizes, temporal stability of genetic composition and potential for local adaptation in anadromous brown trout (Salmo trutta) populations. Molecular Ecology 11: 25232535.
  • Hansen, M., Bekkevold, D., Jensen, L., Mensberg, K. & Nielsen, E. 2006. Genetic restoration of a stocked brown trout Salmo trutta population using microsatellite DNA analysis of historical and contemporary samples. Journal of Applied Ecology 43: 669679.
  • Hansen, M., Skaala, O., Jensen, L., Bekkevold, D. & Mensberg, K. 2007. Gene flow, effective population size and selection at major histocompatibility complex genes: brown trout in the Hardanger Fjord, Norway. Molecular Ecology 16: 14131425.
  • Hanson, P., Johnson, T., Kitchell, J. & Schindler, D. 1997. Fish bioenergetics 3.0. Tech. Rep. WISCU-T-97-001. Madison: Sea Grant Institute, University of Wisconsin.
  • Harby, A., Baptist, M., Dunbar, M. & Schmutz, S. 2004. State-of-the-art in data sampling, modelling analysis and applications of river habitat modelling. Tech. Rep. COST Action 626. France: European Aquatic Modelling Network.
  • Hard, J.J., Winans, G.A. & Richardson, J.C. 1999. Phenotypic and genetic architecture of juvenile morphometry in Chinook salmon. Journal of Heredity 90: 597606.
  • Hardy, O.J. & Vekemans, X. 2002. SPAGeDi: a versatile computer program to analyse spatial genetic structure at the individual or population levels. Molecular Ecology Notes 2: 618620.
  • Harris, D. & Hubert, W. 1992. Habitat use by young-of-year brown trout and effects on weighted usable area. Rivers 3: 99105.
  • Hartl, D. & Clark, A. 1989. Principles of population genetics, 2nd edn. Sunderland, MA: Sinauer Associates. 682 pp.
  • Hauer, C., Unfer, G., Schmutz, S. & Habersack, H. 2007. The importance of morphodynamic processes at riffles used as spawning grounds during the incubation time of nase (Chondrostoma nasus). Hydrobiologia 579: 1527.
  • Haugen, T., Aass, P., Stenseth, N. & Vollestad, L. 2008. Changes in selection and evolutionary responses in migratory brown trout following the construction of a fish ladder. Evolutionary Applications 1: 319335.
  • Hauser, L., Seamons, T.R., Dauer, M., Naish, K.A. & Quinn, T.P. 2006. An empirical verification of population assignment methods by marking and parentage data: hatchery and wild steelhead (Oncorhynchus mykiss) in Forks Creek, Washington, USA. Molecular Ecology 15: 31573173.
  • Hayes, J., Stark, J. & Shearer, K. 2000. Development and test of a whole-lifetime foraging and bioenergetics growth model for drift-feeding brown trout. Transactions of the American Fisheries Society 129: 315332.
  • Hayes, J., Hughes, N. & Kelly, L. 2007. Process-based modelling of invertebrate drift transport, net energy intake and reach carrying capacity for drift-feeding salmonids. Ecological Modelling 207: 171188.
  • Heggenes, J. 1996. Habitat selection by brown trout (Salmo trutta) and young Atlantic salmon (S. salar) in streams: static and dynamic hydraulic modelling. Regulated Rivers: Research & Management 12: 155169.
  • Heggenes, J. & Roed, K. 2006. Do dams increase genetic diversity in brown trout (Salmo trutta)? Microgeographic differentiation in a fragmented river. Ecology of Freshwater Fish 15: 366375.
  • Heggenes, J., Roed, K., Hoyheim, B. & Rosef, L. 2002. Microsatellite diversity assessment of brown trout (Salmo trutta) population structure indicate limited genetic impact of stocking in a Norwegian alpine lake. Ecology of Freshwater Fish 11: 93100.
  • Heggenes, J., Roed, K., Jorde, P. & Brabrand, A. 2009. Dynamic micro-geographic and temporal genetic diversity in vertebrates: the case of lake-spawning populations of brown trout (Salmo trutta). Molecular Ecology 18: 11001111.
  • Hernandez, R. 2008. A flexible forward simulator for populations subject to selection and demography. Bioinformatics 24: 27862787.
  • Hey, J. 2004. FPG: a computer program for forward population genetic simulation. Piscataway, NJ: Rutgers University. Available at: http://genfaculty.rutgers.edu/hey/software.
  • Hey, J. & Nielsen, R. 2004. Multilocus methods for estimating population sizes, migration rates and divergence time, with applications to the divergence of Drosophila pseudoobscura and D. persimilis. Genetics 167: 747760.
  • Hey, J. & Nielsen, R. 2007. Integration within the Felsenstein equation for improved Markov chain Monte Carlo methods in population genetics. Proceedings of the National Academy of Sciences of the United States of America 104: 27852790.
  • Hickey, J.T. & Diaz, G.E. 1999. From flow to fish to dollars: an integrated approach to water allocation. Journal of the American Water Resources Association 35: 10531067.
  • Hitt, N. & Angermeier, P. 2008. Evidence for fish dispersal from spatial analysis of stream network topology. Journal of the North American Benthological Society 27: 304320.
  • Holderegger, R., Kamm, U. & Gugerli, F. 2006. Adaptive vs. neutral genetic diversity: implications for landscape genetics. Landscape Ecology 21: 797807.
  • Hudson, R.R. 1990. Gene genealogies and the coalescent process. Oxford Surveys in Evolutionary Biology 7: 144.
  • Hudson, R.R. 2002. Generating samples under a Wright-Fisher neutral model of genetic variation. Bioinformatics 18: 337338.
  • Hudy, M., Coombs, J., Nislow, K. & Letcher, B. 2010. Dispersal and within-stream spatial population structure of brook trout revealed by pedigree reconstruction analysis. Transactions of the American Fisheries Society 139: 12761287.
  • Hughes, N.F. 1992. Selection of positions by drift-feeding salmonids in dominance hierarchies – Model and test for Arctic grayling (Thymallus-arcticus) in sub-arctic mountain streams, interior Alaska. Canadian Journal of Fisheries and Aquatic Sciences 49: 19992008.
  • Hughes, N.F. 1998. A model of habitat selection by drift-feeding stream salmonids at different scales. Ecology 79: 281294.
  • Hughes, N.F. & Dill, L.M. 1990. Position choice by drift-feeding salmonids – Model and test for Arctic grayling (Thymallus-arcticus) in sub-arctic mountain streams, interior Alaska. Canadian Journal of Fisheries and Aquatic Sciences 47: 20392048.
  • Hughes, N.F., Hayes, J.W., Shearer, K.A. & Young, R.G. 2003. Testing a model of drift-feeding using three-dimensional videography of wild brown trout, Salmo trutta, in a New Zealand river. Canadian Journal of Fisheries and Aquatic Sciences 60: 14621476.
  • Imre, I. & Boisclair, D. 2005. Moon phase and nocturnal density of Atlantic salmon parr in the Sainte-Marguerite River, Quebec. Journal of Fish Biology 66: 198207.
  • Jager, H.I., King, A.W., Schumaker, N.H., Ashwood, T.L. & Jackson, B.L. 2005. Spatial uncertainty analysis of population models. Ecological Modelling 185: 1327.
  • Jenkins, T., Diehl, S., Kratz, K. & Cooper, S. 1999. Effects of population density on individual growth of brown trout in streams. Ecology 80: 941956.
  • Jensen, A. & Johnsen, B. 1999. The functional relationship between peak spring floods and survival and growth of juvenile Atlantic salmon (Salmo salar) and brown trout (Salmo trutta). Functional Ecology 13: 778785.
  • Jensen, L., Hansen, M., Carlsson, J., Loeschcke, V. & Mensberg, K. 2005a. Spatial and temporal genetic differentiation and effective population size of brown trout (Salmo trutta, L.) in small Danish rivers. Conservation Genetics 6: 615621.
  • Jensen, J.L., Bohonak, A.J. & Kelley, S.T. 2005b. Isolation by distance, web service. BMC Genetics 6: 13.
  • Jensen, H., Amundsen, P.A., Elliott, J.M., Bohn, T. & Aspholm, P.E. 2006. Prey consumption rates and growth of piscivorous brown trout in a subarctic watercourse. Journal of Fish Biology 68: 838848.
  • Jessup, B. 1998. A strategy for simulating brown trout population dynamics and habitat quality in an urbanizing watershed. Ecological Modelling 112: 151167.
  • Johansen, M., Elliott, J. & Klemetsen, A. 2005. Relationships between juvenile salmon, Salmo salar L., and invertebrate densities in the River Tana, Norway. Ecology of Freshwater Fish 14: 331343.
  • Johnson, L. & Gage, S. 1997. Landscape approaches to the analysis of aquatic ecosystems. Freshwater Biology 37: 113132.
  • Johnson, R.L., Blumenshine, S.C. & Coghlan, S.M. 2006. A bioenergetic analysis of factors limiting brown trout growth in an ozark tailwater river. Environmental Biology of Fishes 77: 121132.
  • Jones, N. & Tonn, W. 2004. Resource selection functions for age-0 Arctic grayling (Thymallus arcticus) and their application to stream habitat compensation. Canadian Journal of Fisheries and Aquatic Sciences 61: 17361746.
  • Jones, O.R. & Wang, J. 2010a. Molecular marker-based pedigrees for animal conservation biologists. Animal Conservation 13: 2634.
  • Jones, O.R. & Wang, J.L. 2010b. COLONY: a program for parentage and sibship inference from multilocus genotype data. Molecular Ecology Resources 10: 551555.
  • Jones, K.L., Poole, G.C., Meyer, J.L., Bumback, W. & Kramer, E.A. 2006. Quantifying expected ecological response to natural resource legislation: a case study of riparian buffers, aquatic habitat, and trout populations. Ecology and Society 11: 15.
  • Jones, A.G., Small, C.M., Paczolt, K.A. & Ratterman, N.L. 2010. A practical guide to methods of parentage analysis. Molecular Ecology Resources 10: 630.
  • Jongejans, E., Skarpaas, O. & Shea, K. 2008. Dispersal, demography and spatial population models for conservation and control management. Perspectives in Plant Ecology, Evolution and Systematics 9: 153170.
  • Jorde, P.E. & Ryman, N. 2007. Unbiased estimator for genetic drift and effective population size. Genetics 177: 927935.
  • Jorde, K., Schneider, M. & Zöllner, F. 2000. Analysis of instream habitat quality – preference functions and fuzzy models. In: Wang, Z. & Hu, S., eds. Stochastic Hydraulics 2000. Rotterdam: Balkema, pp. 671680.
  • Jorde, K., Schneider, M., Peter, A. & Zollner, F. 2001. Fuzzy based models for the evaluation of fish habitat quality and instream flow assessment. In: Boyer, D. & Rankin, R., eds. Proceedings of the 3rd International Symposium on Environmental Hydraulics, 5–8 December, Tempe, Arizona. CD-ROM.
  • Jorgensen, S. 2008. Overview of the model types available for development of ecological models. Ecological Modelling 215: 39.
  • Jowett, I. 1995. Spatial and temporal variability of brown trout abundance: a test of regression models. Rivers 5: 112.
  • Jowett, I. 2002. RHYHABSIM: river HYdraulic and HABitat SIMulation. Hamilton, New Zealand: National institute of Water & Atmospheric Research.
  • Jowett, I. & Davey, A. 2007. A comparison of composite habitat suitability indices and generalized additive models of invertebrate abundance and fish presence-habitat availability. Transactions of the American Fisheries Society 136: 428444.
  • Joy, M. & Death, R. 2004. Predictive modelling and spatial mapping of freshwater fish and decapod assemblages using GIS and neural networks. Freshwater Biology 49: 10361052.
  • Kalinowski, S., Meeuwig, M., Narum, S. & Taper, M. 2008. Stream trees: a statistical method for mapping genetic differences between populations of freshwater organisms to the sections of streams that connect them. Canadian Journal of Fisheries and Aquatic Sciences 65: 27522760.
  • Kimmerer, W., Mitchell, B. & Hamilton, A. 2001. Building models and gathering data: can we do this better? In: Brown, R., ed. Contributions to the biology of Central Valley salmonids. Sacramento, California: California Department of Fish and Game, vol. 2 of Fish Bulletin 179, pp. 305317.
  • Kimura, M. & Crow, J. 1964. Number of alleles that can be maintained in finite population. Genetics 49: 725.
  • Kimura, M. & Weiss, G. 1964. The stepping stone model of population structure and the decrease of genetic correlation with distance. Genetics 49: 561576.
  • Kingman, J. 1982. The coalescent. Stochastic Processes and their Applications 13: 235248.
  • Klemetsen, A., Amundsen, P., Dempson, J., Jonsson, B., Jonsson, N., O’Connell, M. & Mortensen, E. 2003. Atlantic salmon Salmo salar L., brown trout Salmo trutta L. and Arctic charr Salvelinus alpinus (L.): a review of aspects of their life histories. Ecology of Freshwater Fish 12: 159.
  • Koizumi, I. & Maekawa, K. 2004. Metapopulation structure of stream-dwelling Dolly Varden charr inferred from patterns of occurrence in the Sorachi River basin, Hokkaido, Japan. Freshwater Biology 49: 973981.
  • Kool, J.T. 2009. An object-oriented, individual-based approach for simulating the dynamics of genes in subdivided populations. Ecological Informatics 4: 136146.
  • Krieg, F. & Guyomard, R. 1983. Electrophoretic evidence for a large differentiation between brown trout populations of Corsica. Comptes Rendus de l’Académie des Sciences 296: 10891093.
  • Kristensen, E. & Closs, G. 2008. Variation in growth and aggression of juvenile brown trout (Salmo trutta) from upstream and downstream reaches of the same river. Ecology of Freshwater Fish 17: 130135.
  • Kruuk, L.E.B. 2004. Estimating genetic parameters in natural populations using the ‘animal model’. Philosophical Transactions of the Royal Society of London Series B-Biological Sciences 359: 873890.
  • Kuhner, M.K. 2006. LAMARC 2.0: maximum likelihood and bayesian estimation of population parameters. Bioinformatics 22: 768770.
  • Kuhner, M.K. 2009. Coalescent genealogy samplers: windows into population history. Trends in Ecology & Evolution 24: 8693.
  • Labonne, J., Ravigne, V., Parisi, B. & Gaucherel, C. 2008. Linking dendritic network structures to population demogenetics: the downside of connectivity. Oikos 117: 14791490.
  • Lacy, R. 2000. Structure of the VORTEX simulation model for population viability analysis. Ecological Bulletin 48: 191203.
  • Lacy, R., Borbat, M. & Pollak, J. 2005. VORTEX: a stochastic simulation of the extinction process. Version 9.50. Brookfield, IL: Chicago Zoological Society. Available at: http://www.vortex9.org/vortex.html.
  • Laikre, L. 1999. Conservation genetic management of brown trout (Salmo trutta) in Europe. Tech. Rep. EU FAIR CT97-3882, TroutConcert: Concerted action on identification, management and exploitation of genetic resources in the brown trout.
  • Lamouroux, N. & Capra, H. 2002. Simple predictions of instream habitat model outputs for target fish populations. Freshwater Biology 47: 15431556.
  • Lamouroux, N. & Jowett, I.G. 2005. Generalized instream habitat models. Canadian Journal of Fisheries and Aquatic Sciences 62: 714.
  • Lamouroux, N., Capra, H., Pouilly, M. & Souchon, Y. 1999. Fish habitat preferences in large streams of southern France. Freshwater Biology 42: 673685.
  • Lancaster, J. & Downes, B.J. 2010. Linking the hydraulic world of individual organisms to ecological processes: putting ecology into ecohydraulics. River Research and Applications 26: 385403.
  • Landguth, E. & Cushman, S. 2010. CDPOP: a spatially explicit cost distance population genetics program. Molecular Ecology Resources 10: 156161.
  • Larkin, P. 1978. Fisheries management–an essay for ecologists. Annual Review of Ecology and Systematics 9: 5773.
  • Latch, E.K., Dharmarajan, G., Glaubitz, J.C. & Rhodes, O.E. 2006. Relative performance of bayesian clustering software for inferring population substructure and individual assignment at low levels of population differentiation. Conservation Genetics 7: 295302.
  • Laval, G. & Excoffier, L. 2004. SIMCOAL 2.0: a program to simulate genomic diversity over large recombining regions in a subdivided population with a complex history. Bioinformatics 20: 24852487.
  • Le Pichon, C., Gorges, G., Boet, P., Baudry, J., Goreaud, F. & Faure, T. 2006. A spatially explicit resource-based approach for managing stream fishes in riverscapes. Environmental Management 37: 322335.
  • Leberg, P. 2005. Genetic approaches for estimating the effective size of populations. The Journal of Wildlife Management 69: 13851399.
  • Lebreton, J. 2006. Dynamical and statistical models of vertebrate population dynamics. Comptes Rendus Biologies 329: 804812.
  • Lee, D. & Rieman, B. 1997. Population viability assessment of salmonids by using probabilistic networks. North American Journal of Fisheries Management 17: 11441157.
  • Lefkovitch, L.P. 1965. The study of population growth in organisms grouped by stages. Biometrics 21: 118.
  • Lehane, B.M., Giller, P.S., O’Halloran, J. & Walsh, P.M. 2004. Relative influences of catchment geology, land use and in-stream habitat on brown trout populations in South-Western Ireland. Biology and Environment: Proceedings of the Royal Irish Academy, Section B 1043B: 4354.
  • Lehtonen, P.K., Tonteri, A., Sendek, D., Titov, S. & Primmer, C.R. 2009. Spatio-temporal genetic structuring of brown trout (Salmo trutta L.) populations within the River Luga, northwest Russia. Conservation Genetics 10: 281289.
  • Lek, S. & Baran, P. 1997. Estimations of trout density and biomass: a neural networks approach. Nonlinear Analysis, Theory Methods & Applications 30: 49854990.
  • Lek, S., Belaud, A., Baran, P., Dimopoulos, L. & Delacoste, M. 1996. Role of some environmental variables in trout abundance models using neural networks. Aquatic Living Resources 9: 2329.
  • Leprieur, F., Hickey, M.A., Arbuckle, C.J., Closs, G.P., Brosse, S. & Townsend, C.R. 2006. Hydrological disturbance benefits a native fish at the expense of an exotic fish. Journal of Applied Ecology 43: 930939.
  • Leslie, P. 1945. On the use of matrices in certain population mathematics. Biometrika 33: 183212.
  • Letcher, B.H., Nislow, K.H., Coombs, J.A., O’Donnell, M.J. & Dubreuil, T.L. 2007. Population response to habitat fragmentation in a stream-dwelling brook trout population. PLoS ONE 2: 111.
  • Lischke, H., Loffler, T., Thornton, P. & Zimmermann, N. 2007. A changing world. Challenges for landscape research. Springer, chap. Model up-scaling in landscape research. pp. 249272.
  • Lobon-Cervia, J. 2005. The importance of recruitment for the production dynamics of stream-dwelling brown trout (Salmo trutta). Canadian Journal of Fisheries and Aquatic Sciences 62: 24842493.
  • Lobon-Cervia, J. 2006. Instability of stream salmonid population dynamics under strong environmental limitations-a reply. Oikos 114: 376380.
  • Lobon-Cervia, J. 2007. Density-dependent growth in stream-living brown trout Salmo trutta. Functional Ecology 21: 117124.
  • Lobon-Cervia, J. & Rincon, P. 2004. Environmental determinants of recruitment and their influence on the population dynamics of stream-living brown trout Salmo trutta. Oikos 105: 641646.
  • Lopes, L., Do Carmo, J., Cortes, R. & Oliveira, D. 2004. Hydrodynamics and water quality modelling in a regulated river segment: application on the instream flow definition. Ecological Modelling 173: 197218.
  • Louhi, P., Maki-Petays, A. & Erkinaro, J. 2008. Spawning habitat of Atlantic salmon and brown trout: general criteria and intragravel factors. River Research and Applications 24: 330339.
  • Luikart, G. & England, P. 1999. Statistical analysis of microsatellite DNA data. Trends in Ecology & Evolution 14: 253256.
  • Luikart, G., Ryman, N., Tallmon, D.A., Schwartz, M.K. & Allendorf, F.W. 2010. Estimation of census and effective population sizes: the increasing usefulness of DNA-based approaches. Conservation Genetics 11: 355373.
  • Lunn, D., Thomas, A., Best, N. & Spiegelhalter, D. 2000. WinBUGS, a Bayesian modelling framework: concepts, structure and extensibility. Statistics and Computing 10: 325337.
  • Lynch, M. & Walsh, B. 1998. Genetics and analysis of quantitative traits, 1st edn. Sunderland: Sinauer Associates. 980 pp.
  • Malthus, T. 1798. An essay on the principle of population. London: J. Johnson Edition.
  • Manel, S., Dias, J. & Ormerod, S. 1999. Comparing discriminant analysis, neural networks and logistic regression for predicting species distributions: a case study with a Himalayan river bird. Ecological Modelling 120: 337347.
  • Manel, S., Schwartz, M., Luikart, G. & Taberlet, P. 2003. Landscape genetics: combining landscape ecology and population genetics. Trends in Ecology & Evolution 18: 189197.
  • Manel, S., Gaggiotti, O. & Waples, R. 2005. Assignment methods: matching biological questions with appropriate techniques. Trends in Ecology & Evolution 20: 136142.
  • Manni, F., Guerard, E. & Heyer, E. 2004. Geographic patterns of (genetic, morphologic, linguistic) variation: how barriers can be detected by using Monmonier’s algorithm. Human Biology 76: 173190.
  • Maridet, L. & Souchon, Y. 1995. Potential brown trout habitat (Salmo trutta fario L. 1758) in three Massif-Central streams – Methodological approach and first results on influence of riparian corridors. Bulletin Français de la Pêche et de la Pisciculture 336: 118.
  • Marjoram, P. & Tavaré, S. 2006. Modern computational approaches for analysing molecular genetic variation data. Nature Reviews Genetics 7: 759770.
  • Martyniuk, C.J., Perry, G.M.L., Mogahadam, H.K., Ferguson, M.M. & Danzmann, R.G. 2003. The genetic architecture of correlations among growth-related traits and male age at maturation in rainbow trout. Journal of Fish Biology 63: 746764.
  • Massa-Gallucci, A., Coscia, I., O’Grady, M., Kelly-Quinn, M. & Mariani, S. 2010. Patterns of genetic structuring in a brown trout (Salmo trutta L.) metapopulation. Conservation Genetics 11: 16891699.
  • Matulla, C., Schmutz, S., Melcher, A., Gerersdorfer, T. & Haas, P. 2007. Assessing the impact of a downscaled climate change simulation on the fish fauna in an Inner-Alpine river. International Journal of Biometeorology 52: 127137.
  • McGarigal, K., Cushman, S., Neel, M. & Ene, E. 2002. FRAGSTATS: spatial pattern analysis program for categorical maps. Amherst, MA: University of Massachusetts. Available at: http://www.umass.edu/landeco/research/fragstats/fragstats.html.
  • McKeown, N.J., Hynes, R.A., Duguid, R.A., Ferguson, A. & Prodohl, P.A. 2010. Phylogeographic structure of brown trout Salmo trutta in Britain and Ireland: glacial refugia, postglacial colonization and origins of sympatric populations. Journal of Fish Biology 76: 319347.
  • McRae, B. & Diana, J. 2005. Factors influencing density of age-0 brown trout and brook trout in the Au Sable River, Michigan. Transactions of the American Fisheries Society 134: 132140.
  • Meeuwig, M.H., Guy, C.S., Kalinowski, S.T. & Fredenberg, W.A. 2010. Landscape influences on genetic differentiation among bull trout populations in a stream-lake network. Molecular Ecology 19: 36203633.
  • Mengin, N., Thorel, A., Liebig, H. & Segura, G. 2002. ProCURVE: software to calculate habitat preferences of aquatic organisms. Annales de Limnologie - International Journal of Limnology 38: 329338.
  • Meyer, K. 1988. DFREML – A set of programs to estimate variance components under an individual animal model. Journal of Dairy Science 71: 3334.
  • Meyer, K. 2007. WOMBAT – A tool for mixed model analyses in quantitative genetics by restricted maximum likelihood (REML). Journal of Zhejiang University Science B 8: 815821.
  • Milner, N., Wyatt, R. & Scott, M. 1993. Variability in the distribution and abundance of stream salmonids, and the associated use of habitat models. Journal of Fish Biology 43: 103119.
  • Milner, N., Elliott, J., Armstrong, J., Gardiner, R., Welton, J. & Ladle, M. 2003. The natural control of salmon and trout populations in streams. Fisheries Research 62: 111125.
  • Morrissey, M.B. & de Kerckhove, D.T. 2009. The maintenance of genetic variation due to asymmetric gene flow in dendritic metapopulations. American Naturalist 174: 875889.
  • Mouton, A., Meixner, H., Goethals, P., De Pauw, N. & Mader, H. 2007a. Concept and application of the usable volume for modelling the physical habitat of riverine organisms. River Research and Applications 23: 545558.
  • Mouton, A., Schneider, M., Depestele, J., Goethals, P. & De Pauw, N. 2007b. Fish habitat modelling as a tool for river management. Ecological Engineering 29: 305315.
  • Mouton, A., Schneider, M., Peter, A., Holzer, G., Muller, R., Goethals, P. & De Pauw, N. 2008. Optimisation of a fuzzy physical habitat model for spawning European grayling (Thymallus thymallus L.) in the Aare river (Thun, Switzerland). Ecological Modelling 215: 122132.
  • Naish, K.A. & Hard, J.J. 2008. Bridging the gap between the genotype and the phenotype: linking genetic variation, selection and adaptation in fishes. Fish and Fisheries 9: 396422.
  • Narum, S.R., Zendt, J.S., Graves, D. & Sharp, W.R. 2008. Influence of landscape on resident and anadromous life history types of Oncorhynchus mykiss. Canadian Journal of Fisheries and Aquatic Sciences 65: 10131023.
  • Nehring, R. & Anderson, R. 1993. Determination of population-limiting critical salmonid habitats in Colorado streams using the physical habitat simulation system. Rivers 4: 119.
  • Neuenschwander, S. 2006. AQUASPLATCHE: a program to simulate genetic diversity in populations living in linear habitats. Molecular Ecology Notes 6: 583585.
  • Neuenschwander, S., Hospital, F., Guillaume, F. & Goudet, J. 2008a. quantiNemo: an individual-based program to simulate quantitative traits with explicit genetic architecture in a dynamic metapopulation. Bioinformatics 24: 15521553.
  • Neuenschwander, S., Largiader, C., Ray, N., Currat, M., Vonlanthen, P. & Excoffier, L. 2008b. Colonization history of the Swiss Rhine basin by the bullhead (Cottus gobio): inference under a Bayesian spatially explicit framework. Molecular Ecology 17: 757772.
  • Nikolic, N., Butler, J.R.A., Bagliniere, J.L., Laughton, R., Mcmyn, I.A.G. & Chevalet, C. 2009. An examination of genetic diversity and effective population size in Atlantic salmon populations. Genetics Research 91: 395412.
  • Nislow, K., Einum, S. & Folt, C. 2004. Testing predictions of the critical period for survival concept using experiments with stocked Atlantic salmon. Journal of Fish Biology 65: 188200.
  • Nordborg, M. 2001. Handbook of statistical genetics. Chichester: Wiley, chap. Coalescent theory, pp. 179212.
  • Norris, K. 2004. Managing threatened species: the ecological toolbox, evolutionary theory and declining-population paradigm. Journal of Applied Ecology 41: 413426.
  • Northcote, T. & Lobon-Cervia, J. 2008. Increasing experimental approaches in stream trout research – 1987–2006. Ecology of Freshwater Fish 17: 349361.
  • Nykanen, M. & Huusko, A. 2004. Transferability of habitat preference criteria for larval European grayling (Thymallus thymallus). Canadian Journal of Fisheries and Aquatic Sciences 61: 185192.
  • Ohlund, G., Nordwall, F., Degerman, E. & Eriksson, T. 2008. Life history and large-scale habitat use of brown trout (Salmo trutta) and brook trout (Salvelinus fontinalis) – Implications for species replacement patterns. Canadian Journal of Fisheries and Aquatic Sciences 65: 633644.
  • Ohta, T. & Kimura, M. 1973. Model of mutation appropriate to estimate number of electrophoretically detectable alleles in a finite population. Genetical Research 22: 201204.
  • Olden, J. & Jackson, D. 2002. Illuminating the ‘black box’: a randomization approach for understanding variable contributions in artificial neural networks. Ecological Modelling 154: 135150.
  • Olsen, N. 2010. SSIIM: a three-dimensional numerical model for Simulation of Sediment movements In water Intakes with Multiblock option. Trondheim, Norway: University of Science and Technology. Available at: http://folk.ntnu.no/nilsol/ssiim.
  • Ortigosa, G.R., De Leo, G.A. & Gatto, M. 2000. VVF: integrating modelling and GIS in a software tool for habitat suitability assessment. Environmental Modelling & Software 15: 112.
  • Ostergaard, S., Hansen, M., Loeschcke, V. & Nielsen, E. 2003. Long-term temporal changes of genetic composition in brown trout (Salmo trutta L.) populations inhabiting an unstable environment. Molecular Ecology 12: 31233135.
  • Otto, S. & Day, T. 2007. A biologist’s guide to mathematical modeling in ecology and evolution. Princeton, NJ: Princeton University Press. 752 pp.
  • Ovidio, M., Capra, H. & Philippart, J. 2008. Regulated discharge produces substantial demographic changes on four typical fish species of a small salmonid stream. Hydrobiologia 609: 5970.
  • Ozgul, A., Childs, D.Z., Oli, M.K., Armitage, K.B., Blumstein, D.T., Olson, L.E., Tuljapurkar, S. & Coulson, T. 2010. Coupled dynamics of body mass and population growth in response to environmental change. Nature 466: 482485.
  • Paez, D.J., Morrissey, M., Bernatchez, L. & Dodson, J.J. 2010. The genetic basis of early-life morphological traits and their relation to alternative male reproductive tactics in Atlantic salmon. Journal of Evolutionary Biology 23: 757768.
  • Palsboll, P.J., Berube, M. & Allendorf, F.W. 2007. Identification of management units using population genetic data. Trends in Ecology & Evolution 22: 1116.
  • Parasiewicz, P. 2001. MesoHABSIM: a concept for application of instream flow models in river restoration planning. Fisheries 26: 613.
  • Parasiewicz, P. 2007. The MesoHABSIM model revisited. River Research and Applications 23: 893903.
  • Patterson, T., Thomas, L., Wilcox, C., Ovaskainen, O. & Matthiopoulos, J. 2008. State-space models of individual animal movement. Trends in Ecology & Evolution 23: 8794.
  • Pavey, S.A., Nielsen, J.L. & Hamon, T.R. 2010. Recent ecological divergence despite migration in sockeye salmon (Oncorhynchus nerka). Evolution 64: 17731783.
  • Payne, T. 2005. RHABSIM: Riverine HABitat SIMuation. Arcata, CA: Thomas R. Payne & Associates, Fisheries biology, consulting and software publishing. Available at: http://trpafishbiologists.com.
  • Peakall, R. & Smouse, P.E. 2006. GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes 6: 288295.
  • Pearse, D. & Crandall, K. 2004. Beyond F-ST: analysis of population genetic data for conservation. Conservation Genetics 5: 585602.
  • Peck, S. 2004. Simulation as experiment: a philosophical reassessment for biological modeling. Trends in Ecology & Evolution 19: 530534.
  • Peng, B. & Amos, C.I. 2008. Forward-time simulations of non-random mating populations using simuPOP. Bioinformatics 24: 14081409.
  • Peng, B. & Kimmel, M. 2005. simuPOP: a forward-time population genetics simulation environment. Bioinformatics 21: 36863687.
  • Perry, G.M.L., Audet, C., Laplatte, B. & Bernatchez, L. 2004. Shifting patterns in genetic control at the embryo-alevin boundary in brook charr. Evolution 58: 20022012.
  • Perry, G.M.L., Martyniuk, C.M., Ferguson, M.M. & Danzmann, R.G. 2005. Genetic parameters for upper thermal tolerance and growth-related traits in rainbow trout (Oncorhynchus mykiss). Aquaculture 250: 120128.
  • Pertoldi, C. & Topping, C. 2004. The use of agent-based modelling of genetics in conservation genetics studies. Journal for Nature Conservation 12: 111120.
  • Peterson, D. & Parker, V. 1998. Ecological scale: theory and applications. New York: Columbia University Press. 615 pp.
  • Petts, G. & Kennedy, R. 2005. Water quality technical support program: emerging concepts for integrating human and environmental water needs in river basin management. Tech. Rep. ERDC/EL TR-05-13, U.S. Washington: Army Corps of Engineers, Engineer Research and Development Center.
  • Piry, S., Alapetite, A., Cornuet, J.M., Paetkau, D., Baudouin, L. & Estoup, A. 2004. GENECLASS2: a software for genetic assignment and first-generation migrant detection. Journal of Heredity 95: 536539.
  • Poff, N., Allan, J., Bain, M., Karr, J., Prestegaard, K., Richter, B., Sparks, R. & Stromberg, J. 1997. The natural flow regime: a paradigm for river conservation and restoration. BioScience 47: 769784.
  • Poissant, J., Knight, T. & Ferguson, M. 2005. Nonequilibrium conditions following landscape rearrangement: the relative contribution of past and current hydrological landscapes on the genetic structure of a stream-dwelling fish. Molecular Ecology 14: 13211331.
  • Pont, D., Hugueny, B. & Oberdorff, T. 2005. Modelling habitat requirement of European fishes: do species have similar responses to local and regional environmental constraints? Canadian Journal of Fisheries and Aquatic Sciences 62: 163173.
  • Pouilly, M., Valentin, S., Capra, H., Ginot, V. & Souchon, Y. 1995. Microhabitat methodology: principles and procedures. Bulletin Français de la Pêche et de la Pisciculture 336: 4154.
  • Pritchard, J., Stephens, M. & Donnelly, P. 2000. Inference of population structure using multilocus genotype data. Genetics 155: 945959.
  • Pudovkin, A., Zaykin, D. & Hedgecock, D. 1996. On the potential for estimating the effective number of breeders from heterozygote excess in progeny. Genetics 144: 383387.
  • R Development Core Team. 2010. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.
  • Railsback, S. & Rose, K.A. 1999. Bioenergetics modeling of stream trout growth: temperature and food consumption effects. Transactions of the American Fisheries Society 128: 241256.
  • Railsback, S. & Harvey, B. 2002. Analysis of habitat-selection rules using an individual-based model. Ecology 83: 18171830.
  • Railsback, S., Stauffer, H. & Harvey, B. 2003. What can habitat preference models tell us? Tests using a virtual trout population. Ecological Applications 13: 15801594.
  • Railsback, S., Harvey, B., Jackson, S. & Lamberson, R. 2009. InSTREAM: the individual-based stream trout research and environmental assessment model. Gen. Tech. Rep. PSW-GTR-218. Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station. 254 pp.
  • Raleigh, R., Zuckerman, L. & Nelson, P. 1986. Habitat suitability index models and instream flow suitability curves: brown trout. U.S. Fish and Wildlife Service, Biological Report 82-10.124. 65 pp.
  • Rambaut, A. & Grassly, N.C. 1997. SEQ-GEN: an application for the Monte Carlo simulation of DNA sequence evolution along phylogenetic frees. Computer Applications in the Biosciences 13: 235238.
  • Ramula, S., Rees, M. & Buckley, Y.M. 2009. Integral projection models perform better for small demographic data sets than matrix population models: a case study of two perennial herbs. Journal of Applied Ecology 46: 10481053.
  • Ray, N., Currat, M., Foll, M. & Excoffier, L. 2010. SPLATCHE2: a spatially-explicit simulation framework for complex demography, genetic admixture and recombination. Bioinformatics 26: 29932994.
  • Raymond, M. & Rousset, F. 1995. GENEPOP (version 1.2): population-genetics software for exact tests and ecumenicism. Journal of Heredity 86: 248249.
  • Rees, M. & Ellner, S.P. 2009. Integral projection models for populations in temporally varying environments. Ecological Monographs 79: 575594.
  • Reyjol, Y., Lim, P., Belaud, A. & Lek, S. 2001. Modelling of microhabitat used by fish in natural and regulated flows in the river Garonne (France). Ecological Modelling 146: 131142.
  • Ricker, W. 1954. Stock and recruitment. Journal of the Fisheries Research Board 11: 559623.
  • Ricker, W. 1972. Hereditary and environmental factors affecting certain salmonid populations. In: Simon, R. & Larkin, P., eds. The stock concept in Pacific salmon. Vancouver: University of British Columbia, pp. 19160.
  • Rieman, B., Peterson, J., Clayton, J., Howell, P., Thurow, R., Thompson, W. & Lee, D. 2001. Evaluation of potential effects of federal land management alternatives on trends of salmonids and their habitats in the interior Columbia River basin. Forest Ecology and Management 153: 4362.
  • Rivot, E., Prévost, E., Parent, E. & Baglinière, J.L. 2004. A Bayesian state-space modelling framework for fitting a salmon stage-structured population dynamic model to multiple time series of field data. Ecological Modelling 179: 463485.
  • Rogers, S.M., Gagnon, V. & Bernatchez, L. 2002. Genetically based phenotype-environment association for swimming behavior in lake whitefish ecotypes (Coregonus clupeaformis Mitchill). Evolution 56: 23222329.
  • Rosenberg, N.A. & Nordborg, M. 2002. Genealogical trees, coalescent theory and the analysis of genetic polymorphisms. Nature Reviews Genetics 3: 380390.
  • Rosenfeld, J. 2003. Assessing the habitat requirements of stream fishes: an overview and evaluation of different approaches. Transactions of the American Fisheries Society 132: 953968.
  • Roussel, J.M. & Bardonnet, A. 2002. The habitat of juvenile brown trout (Salmo trutta L.) in small streams: preferences, movements, diel and seasonal variations. Bulletin Français de la Pêche et de la Pisciculture 365/366: 435454.
  • Rousset, F. 2008. GENEPOP ‘007: a complete re-implementation of the GENEPOP software for Windows and Linux. Molecular Ecology Resources 8: 103106.
  • Sabaton, C., Siegler, L., Gouraud, V., Baglinière, J.L. & Mann, S. 1997. Presentation and first applications of a dynamic population model for brown trout, Salmo trutta L.: aid to river management. Fisheries Management and Ecology 4: 425438.
  • Sanz, L. & Bravo de la Parra, R. 2007. Approximate reduction of multiregional models with environmental stochasticity. Mathematical Biosciences 206: 134154.
  • Sanz, N., Garcia-Marin, J.L. & Pla, C. 2002. Managing fish populations under mosaic relationships – The case of brown trout (Salmo trutta) in peripheral Mediterranean populations. Conservation Genetics 3: 385400.
  • Sanz, L., Blasco, A. & Bravo de la Parra, R. 2003. Approximate reduction of multi-type Galton-Watson processes with two time scales. Mathematical Models & Methods in Applied Sciences 13: 491525.
  • Sato, T. & Harada, Y. 2008. Loss of genetic variation and effective population size of Kirikuchi charr: implications for the management of small, isolated salmonid populations. Animal Conservation 11: 153159.
  • Schager, E., Peter, A. & Burkhardt-Holm, P. 2007. Status of young-of-the-year brown trout (Salmo trutta fario) in Swiss streams: factors influencing YOY trout recruitment. Aquatic Sciences 69: 4150.
  • Schindler, D., Hilborn, R., Chasco, B., Boatright, C., Quinn, T., Rogers, L. & Webster, M. 2010. Population diversity and the portfolio effect in an exploited species. Nature 465: 609612.
  • Schneider, D.C. 2001. The rise of the concept of scale in ecology. BioScience 51: 545553.
  • Schneider, M. & Jorde, K. 2003. Fuzzy-rule based models for the evaluation of fish habitat quality and instream flow assessment. In: Proceedings of the Eighth International IFIM Users’ Workshop, 1–5 June, Fort Collins, Colorado. CD-ROM.
  • Schneider, M., Jorde, K., Zollner, F., Kerle, F. & Eisner, A. 2002. Use of habitat models for decision support in water resources management. In: Schmitz, G.H., ed. Proceedings of the 3rd International Conference on Water Resources and Environment Research, 22–26 July, Dresden, Germany. Dresden: Eigenverlag, vol. II, pp. 300–304.
  • Schumaker, N. 2011. HexSim (version 2.1). Corvallis, OR: U.S. Environmental Protection Agency. Available at: http://www.epa.gov/hexsim.
  • Schwartz, M., Luikart, G. & Waples, R. 2007. Genetic monitoring as a promising tool for conservation and management. Trends in Ecology & Evolution 22: 2533.
  • Segelbacher, G., Cushman, S.A., Epperson, B.K., Fortin, M.J., François, O., Hardy, O.J., Holderegger, R., Taberlet, P., Waits, L.P. & Manel, S. 2010. Applications of landscape genetics in conservation biology: concepts and challenges. Conservation Genetics 11: 375385.
  • Serbezov, D., Bernatchez, L., Olsen, E.M. & Vollestad, L.A. 2010a. Mating patterns and determinants of individual reproductive success in brown trout (Salmo trutta) revealed by parentage analysis of an entire stream living population. Molecular Ecology 19: 31933205.
  • Serbezov, D., Bernatchez, L., Olsen, E.M. & Vollestad, L.A. 2010b. Quantitative genetic parameters for wild stream-living brown trout: heritability and parental effects. Journal of Evolutionary Biology 23: 16311641.
  • Shannon, P., Markiel, A., Ozier, O., Baliga, N., Wang, J., Ramage, D., Amin, N., Schwikowski, B. & Ideker, T. 2003. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Research 13: 24982504.
  • Shieh, C.L., Guh, Y.R. & Wang, S.Q. 2007. The application of range of variability approach to the assessment of a check dam on riverine habitat alteration. Environmental Geology 52: 427435.
  • Skalski, G.T. 2007. Joint estimation of migration rate and effective population size using the island model. Genetics 177: 10431057.
  • Sonstebo, J., Borgstrom, R. & Heun, M. 2007a. A comparison of AFLPs and microsatellites to identify the population structure of brown trout (Salmo trutta L.) populations from Hardangervidda, Norway. Molecular Ecology 16: 14271438.
  • Sonstebo, J., Borgstrom, R. & Heun, M. 2007b. Genetic structure of brown trout (Salmo trutta L.) from the Hardangervidda mountain plateau (Norway) analyzed by microsatellite DNA: a basis for conservation guidelines. Conservation Genetics 8: 3344.
  • Sork, V.L. & Waits, L. 2010. Contributions of landscape genetics – Approaches, insights, and future potential. Molecular Ecology 19: 34893495.
  • Souchon, Y., Trocherie, F., Fragnoud, E. & Lacombe, C. 1989. Les modèles numériques des microhabitats des poissons : application et nouveaux développements. Revue des Sciences de l’Eau 2: 807830.
  • Spangler, G., Berst, A. & Koonce, J. 1981. Perspectives and policy recommendations on the relevance of the stock concept of fishery management. Canadian Journal of Fisheries and Aquatic Sciences 38: 19081914.
  • Spence, R. & Hickley, P. 2000. The use of PHABSIM in the management of water resources and fisheries in England and Wales. Ecological Engineering 16: 153158.
  • Stanfield, L. & Gibson, S. 2006. Using a landscape approach to identify the distribution and density patterns of salmonids in Lake Ontario tributaries. American Fisheries Society Symposium 48: 601621.
  • Statzner, B., Sagnes, P., Champagne, J. & Viboud, S. 2003. Contribution of benthic fish to the patch dynamics of gravel and sand transport in streams. Water Resources Research 39: 1309.
  • Steen, P. 2008. Michigan stream fish: distribution models, future predictions, and urban impacts. Ph.D. thesis. Ann Arbor, MI: University of Michigan, 243 pp.
  • Steffler, P., Ghanem, A. & Blackburn, J. 2006. River2D computer program. Calgary, Canada: University of Alberta. Available at: http://www.river2d.ualberta.ca.
  • Stoneman, C.L. & Jones, M.L. 2000. The influence of habitat features on the biomass and distribution of three species of southern Ontario stream salmonines. Transactions of the American Fisheries Society 129: 639657.
  • Storfer, A., Murphy, M., Evans, J., Goldberg, C., Robinson, S., Spear, S., Dezzani, R., Delmelle, E., Vierling, L. & Waits, L. 2007. Putting the ‘landscape’ in landscape genetics. Heredity 98: 128142.
  • Storfer, A., Murphy, M., Spear, S.F., Holderegger, R. & Waits, L.P. 2010. Landscape genetics: where are we now? Molecular Ecology 19: 34963514.
  • Strand, A.E. 2002. METASIM 1.0: an individual-based environment for simulating population genetics of complex population dynamics. Molecular Ecology Notes 2: 373376.
  • Strand, A.E. & Niehaus, J.M. 2007. KERNELPOP, a spatially explicit population genetic simulation engine. Molecular Ecology Notes 7: 969973.
  • Susnik, S., Snoj, A., Wilson, I.F., Mrdak, D. & Weiss, S. 2007. Historical demography of brown trout (Salmo trutta) in the Adriatic drainage including the putative S. Letnica endemic to Lake Ohrid. Molecular Phylogenetics And Evolution 44: 6376.
  • Tallmon, D.A., Koyuk, A., Luikart, G. & Beaumont, M.A. 2008. ONeSAMP: a program to estimate effective population size using approximate Bayesian computation. Molecular Ecology Resources 8: 299301.
  • Taylor, E. 1991. A review of local adaptation in Salmonidae with particular reference to Pacific and Atlantic salmon. Aquaculture 98: 185207.
  • Teixeira, A. & Cortes, R. 2007. PIT telemetry as a method to study the habitat requirements of fish populations: application to native and stocked trout movements. Hydrobiologia 582: 171185.
  • Teixeira, A., Cortes, R. & Oliveira, D. 2006. Habitat use by native and stocked trout (Salmo trutta L.) in two Northeast streams, Portugal. Bulletin Français de la Pêche et de la Pisciculture 382: 118.
  • ter Braak, C. & Smilauer, P. 2002. CANOCO: software for canonical community ordination (version 4.5). Ithaca, NY: Microcomputer Power. Available at: http://www.canoco.com.
  • Tharme, R.E. 2003. A global perspective on environmental flow assessment: emerging trends in the development and application of environmental flow methodologies for rivers. River Research and Applications 19: 397441.
  • Thériault, V., Dunlop, E.S., Dieckmann, U., Bernatchez, L. & Dodson, J.J. 2008. The impact of fishing-induced mortality on the evolution of alternative life-history tactics in brook charr. Evolutionary Applications 1: 409423.
  • Thiele, J.C. & Grimm, V. 2010. NetLogo meets R: linking agent-based models with a toolbox for their analysis. Environmental Modelling & Software 25: 972974.
  • Thomas, L., Buckland, S., Newman, K. & Harwood, J. 2005. A unified framework for modelling wildlife population dynamics. Australian & New Zealand Journal of Statistics 47: 1934.
  • Thorn, P. & Conallin, J. 2006. RHYHABSIM as a stream management tool: case study in the River Kornerup catchment, Denmark. Journal of Transdisciplinary Environmental Studies 5: 118.
  • Thurow, R., Peterson, J. & Guzevich, J. 2006. Utility and validation of day and night snorkel counts for estimating bull trout abundance in first- to third-order streams. North American Journal of Fisheries Management 26: 217232.
  • Tuljapurkar, S. 1990. Population dynamics in variable environments. New York: Springer. 154 pp.
  • Turner, T.F. & Trexler, J.C. 1998. Ecological and historical associations of gene flow in darters (Teleostei: Percidae). Evolution 52: 17811801.
  • Usher, M. 1966. A matrix approach to the management of renewable resources, with special reference to selection forest. Journal of Applied Ecology 3: 355367.
  • Van Winkle, W., Jager, H., Railsback, S., Holcomb, B., Studley, T. & Baldrige, J. 1998. Individual-based model of sympatric populations of brown and rainbow trout for instream flow assessment: model description and calibration. Ecological Modelling 110: 175207.
  • Vandeputte, M., Mauger, S. & Dupont-Nivet, M. 2006. An evaluation of allowing for mismatches as a way to manage genotyping errors in parentage assignment by exclusion. Molecular Ecology Notes 6: 265267.
  • Verhulst, P.F. 1838. Notice sur la loi que la population suit dans son accroissement. Correspondance Mathématique et Physique 10: 113121.
  • Vik, J., Borgstrom, R. & Skaala, O. 2001. Cannibalism governing mortality of juvenile brown trout, Salmo trutta, in a regulated stream. Regulated Rivers: Research & Management 17: 583594.
  • Vilas, R., Bouza, C., Castro, J., Lopez, A. & Martinez, P. 2010. Management units of brown trout from Galicia (NW: Spain) based on spatial genetic structure analysis. Conservation Genetics 11: 897906.
  • Vilizzi, L., Copp, G. & Roussel, J. 2004. Assessing variation in suitability curves and electivity profiles in temporal studies of fish habitat use. River Research and Applications 20: 605618.
  • Vincenzi, S., Crivelli, A., Jesensek, D., Rubin, J. & De Leo, G. 2007. Density-dependent individual growth of marble trout (Salmo marmoratus) in the Soca and Idrijca river basins, Slovenia. Hydrobiologia 583: 5768.
  • Vincenzi, S., Crivelli, A., Jesensek, D. & De Leo, G. 2008a. The role of density-dependent individual growth in the persistence of freshwater salmonid populations. Oecologia 156: 523534.
  • Vincenzi, S., Crivelli, A., Jesensek, D., Rubin, J., Poizat, G. & De Leo, G. 2008b. Potential factors controlling the population viability of newly introduced endangered marble trout populations. Biological Conservation 141: 198210.
  • Vitalis, R. & Couvet, D. 2001. Estimation of effective population size and migration rate from one- and two-locus identity measures. Genetics 157: 911925.
  • Waddle, T. 2001. PHABSIM for Windows (version 1.20). Fort Collins, CO: U.S. Geological Survey. Available at: http://www.fort.usgs.gov/products/software/phabsim.
  • Wang, J. 2001. A pseudo-likelihood method for estimating effective population size from temporally spaced samples. Genetical Research 78: 243257.
  • Wang, J. 2004. Sibship reconstruction from genetic data with typing errors. Genetics 166: 19631979.
  • Wang, H.Y. & Hook, T.O. 2009. Eco-genetic model to explore fishing-induced ecological and evolutionary effects on growth and maturation schedules. Evolutionary Applications 2: 438455.
  • Wang, J. & Whitlock, M. 2003. Estimating effective population size and migration rates from genetic samples over space and time. Genetics 163: 429446.
  • Waples, R. & Do, C. 2008. LDNE: a program for estimating effective population size from data on linkage disequilibrium. Molecular Ecology Resources 8: 753756.
  • Waples, R. & Gaggiotti, O. 2006. What is a population? An empirical evaluation of some genetic methods for identifying the number of gene pools and their degree of connectivity. Molecular Ecology 15: 14191439.
  • Weber, C., Peter, A. & Zanini, F. 2007. Spatio-temporal analysis of fish and their habitat: a case study on a highly degraded Swiss river system prior to extensive rehabilitation. Aquatic Sciences 69: 162172.
  • Wegmann, D., Leuenberger, C., Neuenschwander, S. & Excoffier, L. 2010. ABCtoolbox: a versatile toolkit for approximate Bayesian computations. BMC Bioinformatics 11: 116.
  • Weigel, D.E. & Sorensen, P.W. 2001. The influence of habitat characteristics on the longitudinal distribution of brook, brown, and rainbow trout in a small midwestern stream. Journal of Freshwater Ecology 16: 599613.
  • Wesche, T., Goertler, C. & Hubert, W. 1987. Modified habitat suitability index model for brown trout in Southeastern Wyoming. North American Journal of Fisheries Management 7: 232237.
  • Whipple, S., Link, J., Garrison, L. & Fogarty, M. 2000. Models of predation and fishing mortality in aquatic ecosystems. Fish and Fisheries 1: 2240.
  • Whiteley, A., Spruell, P. & Allendorf, F. 2004. Ecological and life history characteristics predict population genetic divergence of two salmonids in the same landscape. Molecular Ecology 13: 36753688.
  • Whiteley, A., Hastings, K., Wenburg, J., Frissell, C., Martin, J. & Allendorf, F. 2010. Genetic variation and effective population size in isolated populations of coastal cutthroat trout. Conservation Genetics 11: 19291943.
  • Wiens, J. 1989. Spatial scaling in ecology. Functional Ecology 3: 385397.
  • Wiens, J. 2002. Riverine landscapes: taking landscape ecology into the water. Freshwater Biology 47: 501515.
  • Wilenski, U. 1999. NetLogo. Evanston, IL: Northwestern University, Center for Connected Learning and Computer-Based Modeling. Available at: http://ccl.northwestern.edu/netlogo.
  • Williamson, S., Bartholow, J. & Stalnaker, C. 1993. Conceptual-model for quantifying pre-smolt production from flow-dependent physical habitat and water temperature. Regulated Rivers: Research & Management 8: 1528.
  • Wilson, A.J. & Ferguson, M.M. 2002. Molecular pedigree analysis in natural populations of fishes: approaches, applications, and practical considerations. Canadian Journal of Fisheries and Aquatic Sciences 59: 16961707.
  • Wilson, G. & Rannala, B. 2003. Bayesian inference of recent migration rates using multilocus genotypes. Genetics 163: 11771191.
  • Wilson, A.J., Reale, D., Clements, M.N., Morrissey, M.M., Postma, E., Walling, C.A., Kruuk, L.E.B. & Nussey, D.H. 2010. An ecologist’s guide to the animal model. Journal of Animal Ecology 79: 1326.
  • Wollebaek, J., Heggenes, J. & Roed, K. 2010. Disentangling stocking introgression and natural migration in brown trout: survival success and recruitment failure in populations with semi-supportive breeding. Freshwater Biology 55: 26262638.
  • Wright, S. 1931. Evolution in mendelian populations. Genetics 16: 97159.
  • Wright, S. 1943. Isolation by distance. Genetics 28: 114138.
  • Wright, S. 1969. Evolution and the genetics of populations, volume 2: theory of gene frequencies. Chicago, IL: University of Chicago Press. 520 pp.
  • Yamamoto, S., Morita, K., Koizumi, I. & Maekawa, K. 2004. Genetic differentiation of white-spotted charr (Salvelinus leucomaenis) populations after habitat fragmentation: spatial-temporal changes in gene frequencies. Conservation Genetics 5: 529538.
  • Young, F., Valero-Mora, P. & Friendly, M. 2006. Visual statistics: seeing data with dynamic interactive graphics. Hoboken, NJ: Wiley Series in Probability and Statistics, 363 pp.
  • Zorn, T. & Nuhfer, A. 2007. Influences on brown trout and brook trout population dynamics in a Michigan river. Transactions of the American Fisheries Society 136: 691705.