Contents of volume 191

VOL. 191 ISSUE 1 27 JANUARY 2006

Selected Papers from the Fourth International Workshop on Environmental Applications of Machine Learning

EditorialThe Fourth International Workshop on Environmental Applications of Machine Learning, 27 September–1 October 2004, Bled, Slovenia

S. Dzeroski, B. Zenko and M. Debeljak (Ljubljana, Slovenia) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

A new synergetic paradigm in environmental numerical modeling: Hybrid models combining deterministic and machine learningcomponentsV.M. Krasnopolsky (College Park, MD, USA and Camp Springs, MD, USA) and M.S. Fox-Rabinovitz (College Park, MD, USA) . . . 5

The application of artificial neural networks to flow and phosphorus dynamics in small streams on the Boreal Plain, with emphasison the role of wetlandsM.H. Nour, D.W. Smith, M.G. El-Din (Ednonton, Canada) and E.E. Prepas (Thunder Bay, Canada and Ednonton, Canada) . . . . 19

Modelling Lake Glumsø with Q2 learningD. Vladusic, B. Kompare and I. Bratko (Ljubljana, Slovenia) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

Learning to predict channel stability using biogeomorphic featuresS.L. Moret (Baton Rouge, LA, USA), W.T. Langford (Santa Barbara, CA, USA) and D.D. Margineantu (Seattle, WA, USA) . . . 47

Neural network modelling for the analysis of forcings/temperatures relationships at different scales in the climate systemA. Pasini, M. Lorè and F. Ameli (Rome, Italy) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

Q2 Prediction of ozone concentrationsJ. Zabkar, R. Zabkar, D. Vladusic, D. Cemas, D. Suc and I. Bratko (Ljubljana, Slovenia) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

Habitat mapping using machine learning-extended kernel-based reclassification of an Ikonos satellite imageA. Kobler, S. Dzeroski (Ljubljana, Slovenia) and I. Keramitsoglou (Athens, Greece) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

Modelling spatial distribution of the Croatian marine benthic habitatsT. Bakran-Petricioli, O. Antonic, D. Bukovec, D. Petricioli, I. Janekovic, J. Krizan, V. Kusan and S. Dujmovic (Zagreb, Croatia) . . . 96

Using the expert model PERPEST to translate measured and predicted pesticide exposure data into ecological risksP.J. Van den Brink (Wageningen, The Netherlands), C.D. Brown and I.G. Dubus (Bedford, UK) . . . . . . . . . . . . . . . . . . . . . . . . . 106

Sparse regression for analyzing the development of foliar nutrient concentrations in coniferous treesM. Sulkava, J. Tikka and J. Hollmén (HUT, Finland) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118

Using multi-objective classification to model communities of soil microarthropodsD. Demsar, S. Dzeroski (Ljubljana, Slovenia), T. Larsen (Roskilde, Denmark), J. Struyf (Leuven, Belgium), J. Axelsen, M.B. Pedersen and P.H. Krogh (Roskilde, Denmark) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131

Automatic construction of concept hierarchies: The case of foliage-dwelling spidersM. Znidarsic, A. Jakulin, S. Dzeroski (Ljubljana, Slovenia) and C. Kampichler (Villahermosa, Mexico) . . . . . . . . . . . . . . . . . . . 144

Application of machine learning methods to palaeoecological dataM. Jeraj (Madison, WI, USA), S. Dzeroski, L. Todorovski and M. Debeljak (Ljubljana, Slovenia) . . . . . . . . . . . . . . . . . . . . . . . 159

Studying crop sequences with CARROTAGE, a HMM-based data mining softwareF. Le Ber (Strasbourg, France and Vandœuvre-lès-Nancy, France), M. Benoît, C. Schott (Mirecourt, France), J.-F. Mari(Vandœuvre-lès-Nancy, France) and C. Mignolet (Mirecourt, France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170

Model selection in demographic time series using VC-boundsG. Corani and M. Gatto (Milano, Italy) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186

Ecological Modelling 191 (2006) 562–564

doi:10.1016/S0304-3800(05)00637-X

VOL. 191 ISSUE 2 31 JANUARY 2006

The importance of spatial autocorrelation, extent and resolution in predicting forest bird occurrenceM.G. Betts (Fredericton, Canada and New Brunswick, Canada), A.W. Diamond, G.J. Forbes (Burnswick, Canada), M.-A. Villard(Moncton, Canada) and J.S. Gunn (Canada) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197

Dynamic growth model for Scots pine (Pinus sylvestris L.) plantations in Galicia (north-western Spain)U. Diéguez-Aranda (Lugo, Spain), F. Castedo Dorado (Ponferrada (León), Spain), J.G. Álvarez González and A.R. Alboreca(Lugo, Spain) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225

Trophic relationships in the recently impounded Bagré reservoir in Burkina FasoM.C. Villanueva (Castanet Tolosan, France), M. Ouedraogo (Ouagadongou, Burkina Faso) and J. Moreau (Castanet Tolosan,France and Ouagadongou, Burkina Faso) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243

The residence time of river water in reservoirsF. Rueda, E. Moreno-Ostos (Granada, Spain) and J. Armengol (Barcelona, Spain) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 260

Analysis of the eastern Pacific yellowfin tuna fishery based on multiple management objectivesJ.G. Vaca-Rodríguez and R.R. Enríquez-Andrade (California, Mexico) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275

Chaos and pattern formation in a spatial tritrophic food chainD.O. Maionchi (São Paulo, Brazil), S.F. dos Reis (Campinas, Brazil) and M.A.M. de Aguiar (São Paulo, Brazil and Massachusetts,USA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 291

Causasilty among wildfire, ENSO, timber harvest, and urban sprawl: The vector autoregression approachJ. Gan (College Station, TX, USA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 304

VOL. 191 ISSUES 3–4 5 FEBRUARY 2006

System-analytical modelling—Part I. General principles and theoretically best accuracies of ecological models. Soil-moistureexchange in agroecosystemsY.B. Kirsta (Barnaul, Russia) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315

System-analytical modelling—Part II. Wheat biotime run and yield formation. Agroclimatic potential, the Le Chatelier principle, andchanges in agroclimatic potential and climate in Russia and the U.S.Y.B. Kirsta (Barnaul, Russia) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 331

Physiologically based demographics of Bt cotton–pest interactions. I. Pink bollworm resistance, refuge and riskA.P. Gutierrez (Berkeley, CA, USA) and S. Ponsard (Berkeley, CA, USA and Toulouse, France) . . . . . . . . . . . . . . . . . . . . . . . . 346

Physiologically based demographics of Bt cotton–pest interactions. II. Temporal refuges, natural enemy interactionsA.P. Gutierrez (Berkeley, CA, USA), J.J. Adamczyk, Jr. (Stoneville, MS, USA), S. Ponsard (Berkeley, CA, USA and Toulouse,France) and C.K. Ellis (Berkeley, CA, USA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 360

Effects of population size/age structure, condition and temporal dynamics of spawning on reproductive output in Atlantic cod (Gadus morhua)B.E. Scott (Aberdeen, UK), G. Marteinsdottir (Reykjavik, Iceland), G.A. Begg (Townsville, Australia), P.J. Wright (Aberdeen, UK)and O.S. Kjesbu (Bergen, Norway) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383

Simulated effects of habitat loss and fragmentation on a solitary mustelid predatorH.I. Jager, E.A. Carr and R.A. Efroymson (Oak Ridge, TN, USA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 416

Knowledge discovery from models of soil properties developed through data miningE.N. Bui, B.L. Henderson (Canberra, Australia) and K. Viergever (Wageningen, The Netherlands) . . . . . . . . . . . . . . . . . . . . . . . 431

The porous media model for the hydraulic system of a conifer tree: Linking sap flux data to transpiration rateY.-L. Chuang (Durham, NC, USA and Los Angeles, CA, USA), R. Oren (Durham, NC, USA), A.L. Bertozzi (Durham, NC, USAand Los Angeles, CA, USA), N. Phillips (Boston, MA, USA) and G.G. Katul (Durham, NC, USA) . . . . . . . . . . . . . . . . . . . . . . 447

Impact of climate variability on present and Holocene vegetation: A model-based studyJ. Ni (Jena, Germany and Beijing, China), S.P. Harrison, I.C. Prentice (Jena, Germany), J.E. Kutzbach (Madison, WI, USA) and S.Sitch (Potsdam, Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 469

GIS-assisted modelling of the spatial distribution of Qinghai spruce (Picea crassifolia) in the Qilian Mountains, northwestern Chinabased on biophysical parametersC. Zhao, Z. Nan, G. Cheng, J. Zhang and Z. Feng (Lanzhou, China) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 487

Inference for the Richards growth model using Box and Cox transformation and bootstrap techniquesS. Loibel, J.B.R. do Val (Campinas, Brazil) and M.G. Andrade (São Carlos, Brazil) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 501

One large, several medium, or many small?S.-R. Zhou (Beijing, PR China and Gansu, PR China) and G. Wang (Gansu, PR China) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 513

Optimal estimation of parameters for a estuarine eutrophication modelJ. Shen (Gloucester Point, VA, USA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 521

Contents of volume 191 563

Short communicationsCatch crops affect nitrogen dynamics in organic farming systems without livestock husbandry—Simulations with the DAISY model

T. Müller (Stuttgart, Germany), K. Thorup-Kristensen (Denmark), J. Magid, L.S. Jensen and S. Hansen (Frederiksberg,Denmark) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 538

How to detect and visualize extinction thresholds for structured PVA modelsH. Hildenbrandt (Bremen, Germany), M.S. Müller and V. Grimm (Leipzig, Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 545

Emergence of ratio-dependent and predator-dependent functional responses for pollination mutualism and seed parasitismD.L. DeAngelis (Coral Gables, FL, USA) and J.N. Holland (Houston, TX, USA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 551

Author index of volume 191 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 557Subject index of volume 191 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 559Contents of volume 191 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 562

564 Contents of volume 191