Species distribution modeling with Gaussian processes: A case study with the youngest stages of sea spawning whitefish (Coregonus lavaretus L. s.l.) larvae

Ecological Modelling

Volumn 228, Issue , 2012, Pages 49-58

  Vanhatalo, Jarno ^a   Veneranta, Lari ^b   Hudd, Richard ^b  

^a UNIVERSITY OF HELSINKI   (Finland)

^b FINNISH FOREST RESEARCH INSTITUTE   (Finland)

Author keywords

Average predictive comparison; Bayesian modeling; Covariance function; Gaussian process; Spatial random effect; Species distribution model

Indexed keywords

AVERAGE PREDICTIVE COMPARISON; BAYESIAN MODELING; COVARIANCE FUNCTION; GAUSSIAN PROCESSES; RANDOM EFFECTS; SPECIES DISTRIBUTION MODELS;

BAYESIAN NETWORKS; COASTAL ZONES; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); INFERENCE ENGINES; RANDOM PROCESSES; RESEARCH;

POPULATION DISTRIBUTION;

BAYESIAN ANALYSIS; COASTAL ZONE; GAUSSIAN METHOD; LARVA; NONLINEARITY; NUMERICAL MODEL; POPULATION DISTRIBUTION; SALMONID; SPATIAL ANALYSIS; SPAWNING; WATER DEPTH;

ATLANTIC OCEAN; BALTIC SEA; GULF OF BOTHNIA;

COREGONUS LAVARETUS;

EID: 84855910129     PISSN: 03043800     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ecolmodel.2011.12.025     Document Type: Article

References (34)

1. Andersen J.H., Axe P., Backer H., Carstensen J., Claussen U., Fleming-Lehtinen V., Järvinen M., Kaartokallio H., Knuuttila S., Korpinen S., Laamanen M., Lysiak-Pastuszak E., Martin G., Møhlenberg F., Murray C., Nausch G., Norkko A., Villnäs A. Getting the measure of eutrophication in the Baltic Sea: towards improved assessment principles and methods. Biogeochemistry 2010, 1-20.
2. Aneer, G., Blomqvist, E.M., Hallbäck, H., Mattila, J., Nellbring, S., Skora, K., Urho, L., 1992. Methods for Sampling of Shallow Water Fish. Technical Report 13, The Baltic Marine Biologist.
3. Brown R., Taylor W.W., Assel R.A. Factors affecting the recruitment of lake whitefish in two areas of northern lake Michigan. J. Great Lakes Res. 1993, 19:418-428.
4. Ekebom J., Laihonen P., Suominen T. A gis-based step-wise procedure for assessing physical exposure in fragmented archipelagos. Estuar. Coast. Shelf Sci. 2003, 57:887-898.
5. Elith J., Leathwick J.R. Species distribution models: ecological explanation and prediction across space and time. Annu. Rev. Ecol. Evol. Syst. 2009, 40:677-697.
6. Freeberg M.H., Taylor W.W., Brown R.W. Effect of egg and larval survival on year-class strength of lake whitefish in Grand Traverse Bay, lake Michigan. T. Am. Fish. Soc. 1990, 119:92-100.
7. Gelfand A.E., Dey D.K., Chang H. Model determination using predictive distributions with implementation via sampling-based methods (with discussion). Bayesian Statistics, vol. 4 1992, 147-167. Oxford University Press. J.M. Bernardo, J.O. Berger, A.P. Dawid, A.F.M. Smith (Eds.).
8. Gelfand A.E., Diggle P.J., Fuentes M., Guttorp P. Handbook of Spatial Statistics 2010, CRC Press.
9. Gelman A. Prior distributions for variance parameters in hierarchical models. Bayesian Anal. 2006, 1:515-533.
10. Gelman A., Pardoe I. Average predictive comparisons for models with nonlinearity, interactions, and variance components. Sociol. Methodol. 2007, 37:23-51.
11. Gilks W., Richardson S., Spiegelhalter D. Markov Chain Monte Carlo in Practice 1996, Chapman and Hall.
12. Girolami M., Calderhead B. Riemann manifold Langevin and Hamiltonian Monte Carlo methods. J. Roy. Stat. Soc. B 2011, 73:123-214.
13. Guisan A., Edwards T.C., Hastie T. Generalized linear and generalized additive models in studies of species distributions: setting the scene. Ecol. Model. 2002, 157:89-100.
14. HELCOM Fourth periodic assessment of the state of the marine environment of the Baltic Sea area 1994-1998 volume 82B of Baltic Sea Environment Proceedings 2002, Helsinki Commission.
15. Håkansson B., Alenius P., Brydsten L. Physical environment in the Gulf of Bothnia. Ambio 1996, 5-12.
16. Hudd, R., Hilden, M., Urho, L., Axell, M.B., Jåfs, L.A., 1984. Fiskeriundersökning av Kyrö älvs mynnings-och influensområde 1980-82 (Fishery investigation in 1980-1982 of the Kyrönjoki estuary and its influence area in the Northern Quark of the Baltic Sea). Technical Report 242B, National Board of Waters, Finland.
17. Hudd R., Lehtonen H., Kurttila I. Growth and abundance of fry; factors which influence the year-class strength of whitefish (Coregonus widegreni) in the southern Bothnian Bay (Baltic). Finnish Fish. Res. 1988, 213-220.
18. Latimer A.M., Wu S., Gelfand A.E., Silander J.A. Building statistical models to analyze species distributions. Ecol. Appl. 2006, 16:33-50.
19. Leathwick J., Elith J., Hastie T. Comparative performance of generalized additive models and multivariate adaptive regression splines for statistical modelling of species distributions. Ecol. Model. 2006, 199:188-196.
20. Leskelä A., Hudd R., Lehtonen H., Huhmarniemi A., Sandström O. Habitats of whitefish (Coregonus lavaretus (L.) s.l.) larvae in the Gulf of Bothnia. Aqua Fenn. 1991, 21:145-151.
21. Lindgren F., Rue H., Lindström J. An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach. J. Roy. Stat. Soc. B 2011, 73:423-498.
22. Minka, T., 2001. A Family of Algorithms for Approximate Bayesian Inference. Ph.D. Thesis, Massachusetts Institute of Technology.
23. Moisen G.G., Frescino T.S. Comparing five modelling techniques for predicting forest characteristics. Ecol. Model. 2002, 157:209-225.
24. Munoz J., Felicísimo A.M. Comparison of statistical methods commonly used in predictive modelling. J. Veg. Sci. 2004, 15:285-292.
25. Neal R. Regression and classification using Gaussian process priors. Bayesian Statistics, vol. 6 1998, 475-501. Oxford University Press. J.M. Bernardo, J.O. Berger, A.P. David, A.P.M. Smith (Eds.).
26. Neal R.M. Bayesian Learning for Neural Networks 1996, Springer.
27. Nickisch H., Rasmussen C.E. Approximations for binary Gaussian process classification. J. Mach. Learn. Res. 2008, 9:2035-2078.
28. Olden J.D., Jackson D.A. A comparison of statistical approaches for modelling fish species distributions. Freshwater Biol. 2002, 47:1976-1995.
29. Pitkänen H., Kauppila P., Laine Y. Trends since the late 1980. The State of Finnish Coastal Waters in the 1990. The Finnish Environment, vol. 472 2001, 37-60. Finnish Environment Institute. P. Kauppila, S. Bäck (Eds.).
30. Rasmussen C.E., Williams C.K.I. Gaussian Processes for Machine Learning 2006, The MIT Press.
31. Riihimäki J., Sund R., Vehtari A. Analysing the length of care episode after hip fracture: a nonparametric and a parametric Bayesian approach. Health Care Manage. Sci. 2010, 13:170-181.
32. Seinä A., Peltola J. Duration of the ice seasons and statistics of fast ice thickness along the finnish coast. Finnish Mar. Res. 1991, 1961-1990.
33. Vanhatalo J., Pietiläinen V., Vehtari A. Approximate inference for disease mapping with sparse Gaussian processes. Stat. Med. 2010, 29:1580-1607.
34. Vehtari A., Lampinen J. Bayesian model assessment and comparison using cross-validation predictive densities. Neural Comput. 2002, 14:2439-2468.