LEADER 02416nam 2200565 450 001 9910786564203321 005 20230811221758.0 010 $a1-78023-215-2 035 $a(CKB)3710000000114340 035 $a(EBL)1693149 035 $a(SSID)ssj0001255508 035 $a(PQKBManifestationID)12541129 035 $a(PQKBTitleCode)TC0001255508 035 $a(PQKBWorkID)11244305 035 $a(PQKB)11486960 035 $a(MiAaPQ)EBC1693149 035 $a(Au-PeEL)EBL1693149 035 $a(CaPaEBR)ebr10882431 035 $a(CaONFJC)MIL617066 035 $a(OCoLC)880531337 035 $a(EXLCZ)993710000000114340 100 $a20140701d2013 uy| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aOctopus /$fRichard Schweid 210 1$aLondon :$cReaktion Books,$d2013. 215 $a1 online resource (200 p.) 225 1 $aAnimal 300 $aDescription based upon print version of record. 311 $a1-78023-177-6 320 $aIncludes bibliographical references and index. 327 $aOctopus; Imprint Page; Contents; 1. Octopus Body; 2. Octopus Brain; 3. Octopus Mind; 4. Octopus Fishing, Farming and Marketing; 5. Octopus Cuisine; 6. Octopus Iconography; 7. Octopus Keeping; Timeline; References; Select Bibliography; Associations and Websites; Acknowledgements; Photo Acknowledgements; Index 330 $aOur relationship to the octopus dates back to prehistory, when the eight-armed animal was depicted on vases and found in stone carvings from ancient Greece. Now we appreciate them for their abilities as escape artists, with sophisticated camouflage systems and ink jets-as well as their roles in tasty dishes from many cuisines. Octopuses are also among the most intelligent invertebrates in the world, with mental capacity comparable to that of a dog. In this heavily illustrated book, Richard Schweid details this animal's remarkable natural history and its multifaceted relationship with humans.< 410 0$aAnimal (Reaktion Books) 606 $aOctopuses 606 $aOctopus fisheries 615 0$aOctopuses. 615 0$aOctopus fisheries. 676 $a594.56 700 $aSchweid$b Richard$01136498 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910786564203321 996 $aOctopus$93774491 997 $aUNINA LEADER 04409nam 22006735 450 001 9910254076603321 005 20251116155117.0 010 $a3-319-28893-8 024 7 $a10.1007/978-3-319-28893-2 035 $a(CKB)3710000000667124 035 $a(EBL)4528420 035 $a(DE-He213)978-3-319-28893-2 035 $a(MiAaPQ)EBC4528420 035 $a(PPN)194078027 035 $a(EXLCZ)993710000000667124 100 $a20160513d2016 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aData-driven Modelling of Structured Populations $eA Practical Guide to the Integral Projection Model /$fby Stephen P. Ellner, Dylan Z. Childs, Mark Rees 205 $a1st ed. 2016. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016. 215 $a1 online resource (339 p.) 225 1 $aLecture Notes on Mathematical Modelling in the Life Sciences,$x2193-4789 300 $aDescription based upon print version of record. 311 08$a3-319-28891-1 320 $aIncludes bibliographical references and index. 327 $aIntroduction -- Simple Deterministic IPM -- Basic Analysis 1: Demographic Measures and Events in the Life Cycle -- Basic Analysis 2: Prospective Perturbation Analysis -- Density Dependence -- General Deterministic IPM -- Environmental Stochasticity -- Spatial Models -- Evolutionary Demography -- Future Directions and Advanced Topics. 330 $aThis book is a ?How To? guide for modeling population dynamics using Integral Projection Models (IPM) starting from observational data. It is written by a leading research team in this area and includes code in the R language (in the text and online) to carry out all computations. The intended audience are ecologists, evolutionary biologists, and mathematical biologists interested in developing data-driven models for animal and plant populations. IPMs may seem hard as they involve integrals. The aim of this book is to demystify IPMs, so they become the model of choice for populations structured by size or other continuously varying traits. The book uses real examples of increasing complexity to show how the life-cycle of the study organism naturally leads to the appropriate statistical analysis, which leads directly to the IPM itself. A wide range of model types and analyses are presented, including model construction, computational methods, and the underlying theory, with the more technical material in Boxes and Appendices. Self-contained R code which replicates all of the figures and calculations within the text is available to readers on GitHub. Stephen P. Ellner is Horace White Professor of Ecology and Evolutionary Biology at Cornell University, USA; Dylan Z. Childs is Lecturer and NERC Postdoctoral Fellow in the Department of Animal and Plant Sciences at The University of Sheffield, UK; Mark Rees is Professor in the Department of Animal and Plant Sciences at The University of Sheffield, UK. 410 0$aLecture Notes on Mathematical Modelling in the Life Sciences,$x2193-4789 606 $aBiomathematics 606 $aBioinformatics 606 $aBioinformātica$2lemac 606 $aComputational biology 606 $aBiomatemātica$2lemac 606 $aBiologia computacional$2lemac 606 $aMathematical and Computational Biology$3https://scigraph.springernature.com/ontologies/product-market-codes/M31000 606 $aComputer Appl. in Life Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/L17004 615 0$aBiomathematics. 615 0$aBioinformatics. 615 7$aBioinformātica. 615 0$aComputational biology. 615 7$aBiomatemātica. 615 7$aBiologia computacional. 615 14$aMathematical and Computational Biology. 615 24$aComputer Appl. in Life Sciences. 676 $a333.95411072 700 $aEllner$b Stephen P$4aut$4http://id.loc.gov/vocabulary/relators/aut$0311082 702 $aChilds$b Dylan Z.$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aRees$b Mark$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910254076603321 996 $aData-driven Modelling of Structured Populations$92106912 997 $aUNINA