The obligatory data for HMSC-analyses includes a matrix of species occurrences or abundances and a matrix of environmental covariates. Additional and optional data include information about species traits and phylogenetic relationships, and information about the spatiotemporal context of the sampling design. HMSC partitions variation in species occurrences to components that relate to environmental filtering, species interactions, and random processes. HMSC yields inference both at species and community levels. It can be used to generate simulated communities under given environmental conditions, and thus its predictions can be compared to independent validation data, and it can be used for scenario simulations.
The development version is found on Github.
The old matlab and R versions of HMSC can be found here.
The first copies of the book now exist, fresh from the printing press!
The official publication date (for both the printed book and the ebook) for the UK and Europe has been set as 11th June 2020. Further global publication dates will depend on shipping schedules and will be available on www.cambridge.org.
Click here to order from the publisher's site - use offer code JSDM2020 to get 20% off.
As supporting information to the book, we provide here R-scripts and data files for the three real data examples of the book: the plant example of Section 6.7, the fungal example of Section 7.9, and the bird example of Section 11.1. The scripts were originally developed by Otso Ovaskainen and Nerea Abrego, and Jari Oksanen has made further improvements to them.
We will organize the next joint species distribution course 15-19 August 2022 in the context of the Jyväskylä Summer School (https://www.jyu.fi/en/research/summer-and-winter-schools/jss). This will be a hybrid event, so you can take part either physically (in Jyväskylä, Finland), or through online zoom sessions. The main aim of the course is to teach the participants how to apply joint species distribution modelling in practice with the R-package Hmsc. The course will be a mixture of basic and advanced topics, so it is suitable both as the first course on this topic, as well as giving more profound understanding for those who have already taken a previous course on this topic.
The deadline for officially registering for the course was April 30th. If you plan to participate only remotely, you can register here (google form) until August 1st.
For the course description, see here and the text below.
BIO3: Joint Species Distribution Modelling with Hierarchical Modelling of Species Communities (HMSC)
Study mode: Hybrid
Participants: Master students, PhD students, post docs, senior researchers
Lecturer(s): Otso Ovaskainen, Nerea Abrego, Mirkka Jones, Gleb Tikhonov, Jari Oksanen, Sara Taskinen, Jenni Niku, and others
Coordinator(s): Otso Ovaskainen and Nerea Abrego
Modes of study: Lectures, computer demonstrations, computer exercises, self-reading of course book, small-group discussions
Course book: Ovaskainen, O. and Abrego, N. 2020. Joint Species Distribution Modelling – With Applications in R. Cambridge University Press.
Credits: 3 ECTS
Evaluation: Pass / fail, based on project work report
Contents: This course is designed for students and researchers who are interested in analysing community data in a way that allows placing their results in the context of modern theory. The course follows the book of Ovaskainen and Abrego (2020), thus covering a comprehensive treatment of Hierarchical Modelling of Species Communities (HMSC), including both the technical detail of the statistical methods, as well as the ecological interpretation of the results. With the help of worked out examples, the participants learn how to conduct and interpret statistical analyses in practice with the R-package Hmsc, providing a fast starting point for applying HMSC to their own data. The participants are encouraged to bring also their own data so that they can get hands-on support on HMSC-analyses of their own projects.
Learning outcomes: The participants will learn how to set up R-scripts that run the entire Hmsc pipeline from constructing and fitting the models to producing the result tables and figures, as well as how to write texts for how the analyses were done (for the Material and Methods section for your manuscript) and how to report the results (the Results section of your manuscript).
Prerequisites: Some prior experience on the use of linear models, and some prior experience on the use of the R-environment
Europe, Finland, Helsinki, and online. Five-day-course 2-6 November. Teachers Otso Ovaskainen, Nerea Abrego, Jari Oksanen, and others: Hierarchical Modelling of Species Communities with the R-package Hmsc:
Core papers about HMSC
Ovaskainen, O., Tikhonov, G., Norberg, A., Blanchet, F. G., Duan, L., Dunson, D., Roslin, T. and Abrego, N. 2017a. How to make more out of community data? A conceptual framework and its implementation as models and software. Ecology Letters 20, 561-576. https://doi.org/10.1111/ele.12757
Ovaskainen, O., Tikhonov, G., Dunson, D., Grøtan, V., Engen, S., Sæther, B.-E. and Abrego, N. 2017b. How are species interactions structured in species rich communities? A new method for analysing time-series data. Proceedings of the Royal Society B: Biological Sciences, 284, 20170768. https://doi.org/10.1098/rspb.2017.0768
Tikhonov, G., Abrego, N., Dunson, D. and Ovaskainen, O. 2017. Using joint species distribution models for evaluating how species-to-species associations depend on the environmental context. Methods in Ecology and Evolution 8, 443-452. https://doi.org/10.1111/2041-210X.12723
Tikhonov, G., Opedal, Ø. H., Abrego, N., Lehikoinen, A., de Jonge, M. M., Oksanen, J. and Ovaskainen, O. 2020a. Joint species distribution modelling with the R-package Hmsc. Methods in Ecology and Evolution, in early view, https://doi.org/10.1111/2041-210X.13345
Tikhonov, G., Duan, L., Abrego, N., Newell, G., White, M., Dunson, D. and Ovaskainen, O. 2020b. Computationally efficient joint species distribution modelling of big spatial data. Ecology, e02929. https://doi.org/10.1002/ecy.2929
Ovaskainen, O. and Abrego, N. 2020. Joint Species Distribution Modelling – With Applications in R. Cambridge University Press, in press.
Abrego, N., Norberg, A. and Ovaskainen, O. 2017. Measuring and predicting the influence of traits on the assembly processes of wood-inhabiting fungi. Journal of Ecology 105, 1070-1081. https://doi.org/10.1111/1365-2745.12722
Ovaskainen, O., Roy, D., Fox, R. and Anderson, B. 2016. Uncovering hidden spatial structure in species communities with spatially explicit joint species distribution models. Methods in Ecology and Evolution 7, 428-436. https://doi.org/10.1111/2041-210X.12502
Ovaskainen, O., Abrego, N., Halme, P. and Dunson, D. 2016. Using latent variable models to identify large networks of species-to-species associations at different spatial scales. Methods in Ecology and Evolution 7, 549-555. https://doi.org/10.1111/2041-210X.12501
A review of joint species distribution modelling:
Warton, D., Blanchet, G., O’Hara, R., Ovaskainen, O., Taskinen, S., Walker, S. and Hui, F. K. C. 2015. So many variables: joint modelling in community ecology. Trends in Ecology and Evolution 30, 766-779. https://doi.org/10.1016/j.tree.2015.09.007
How HMSC results link to the underlying community assembly processes:
Ovaskainen, O., Rybicki, J. and Abrego, N. 2019. What can observational data reveal about metacommunity processes? Ecography 42, 1877-1886. https://doi.org/10.1111/ecog.04444
The predictive performance of HMSC in comparison to other SDM methods:
Norberg, A., Abrego, N., Blanchet, F. G., Adler, F., Anderson, B., Anttila, J., Araújo, M., Dallas, T., Dunson, D., Elith, J., Foster, S., Fox, R., Franklin, J., Godsoe, W., Guisan, A., O'Hara, B., Hill, N., Holt, R. D., Hui, F., Husby, M., Kålås, J., Lehikoinen, A., Luoto, M., Mod, H., Newell, G., Renner, I., Roslin, T., Soininen, J., Thuiller, W., Vanhatalo, J., Warton, D., White, M., Zimmermann, N., Gravel, D. and Ovaskainen, O. 2019. A comprehensive evaluation of predictive performance of 33 species distribution models at species and community levels. Ecological Monographs 89, e01370. https://doi.org/10.1002/ecm.1370
Some empirically oriented papers applying HMSC:
Norberg, A., Halme, P., Kotiaho, J. S., Toivanen, T. and Ovaskainen, O. 2019. Experimentally induced community assembly of polypores reveals the importance of both environmental filtering and assembly history. Fungal Ecology 41, 137-146. https://doi.org/10.1016/j.funeco.2019.05.003
Minard, G., Tikhonov, G., Ovaskainen, O. and Saastamoinen, M. 2019. The microbiome of the Melitaea cinxia butterfly shows marked variation but is only little explained by the traits of the butterfly or its hostplant. Environmental Microbiology 21, 4253-4269. https://doi.org/10.1111/1462-2920.14786
Rocha, R., Ovaskainen, O., López-Baucells, A., Farneda, F. Z., Sampaio, E. M., Bobrowiec, P.E.D, Cabeza, M., Palmeirim, J. M. and Meyer, C. F. J. 2018. Secondary forest regeneration benefits old-growth specialist bats in a fragmented tropical landscape. Scientific Reports 8, 3819. https://doi.org/10.1038/s41598-018-21999-2
Häkkilä, M., Abrego, N., Ovaskainen, O. and Mönkkönen, M. 2018. Habitat quality is more important than matrix quality for bird communities in protected areas. Ecology and Evolution 8, 4019-4030. https://doi.org/10.1002/ece3.3923
Lammel, D. R., Barth, G., Ovaskainen, O., Cruz, L. M., Zanatta, J. A., Ryo, M., Souza, E. M. and Pedrosa, F. O. 2018. Direct and indirect effects of a pH gradient bring insights into the mechanisms driving prokaryotic community structures. Microbiome 6, 106. https://doi.org/10.1186/s40168-018-0482-8
Abrego, N., Dunson, D., Halme, P., Salcedo, I. and Ovaskainen, O. 2017. Wood-inhabiting fungi with tight associations with other species have declined as a response to forest management. Oikos 126, 269-275. https://doi.org/10.1111/oik.03674
Rocha, R., Ovaskainen, O., López-Baucells, A., Farneda, F. Z., Ferreira, D. F., Bobrowiec, P.E.D, Cabeza, M., Palmeirim, J. M. and Meyer, C. F. J. 2017. Design matters: an evaluation of the impact of small man-made forest clearings on tropical bats using a before-after-control-impact design. Forest Ecology and Management 401, 8-16. https://doi.org/10.1016/j.foreco.2017.06.053