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Section: Ecology
Topic: Ecology, Biology of interactions
Conference: Euring 2023

Assessing species interactions using integrated predator-prey models

Paquet, Matthieu1  ; Barraquand, Frédéric1  
1 Institute of Mathematics of Bordeaux, University of Bordeaux, CNRS, Bordeaux INP, Talence, France

10.24072/pcjournal.337 - Peer Community Journal, Volume 3 (2023), article no. e105.

Get full text PDF Peer reviewed and recommended by PCI

Inferring the strength of species interactions from demographic data is a challenging task. The Integrated Population Modelling (IPM) approach, bringing together population counts, capture-recapture, and individual-level fecundity data into a unified model framework, has been extended from single species to the community level. This allows to specify IPMs for multiple species with interactions specified as links between vital rates and stage-specific densities. However, there is no evaluation of such models when interactions are actually absent---while any interaction inference method runs the risk of producing false positives. We investigate here whether multispecies IPMs could output interactions where there are in fact none, building on an existing predator-prey IPM. We show that interspecific density-dependence estimates are centered on zero when simulated to be zero, and therefore their estimation is unbiased. Their coverage probability, quantifying how many times credible intervals include zero, is also satisfactory. We further confirm that adding random temporal variation to multispecies density-dependent link functions does not alter these results. This study therefore reaffirms the potential of multispecies IPMs to infer correctly how biotic interactions influence demography, although future studies should investigate model misspecifications.

Published online:
DOI: 10.24072/pcjournal.337
Type: Research article
Keywords: Integrated Population Model; data assimilation; species interactions; predation; density-dependence
Paquet, Matthieu 1; Barraquand, Frédéric 1

1 Institute of Mathematics of Bordeaux, University of Bordeaux, CNRS, Bordeaux INP, Talence, France
License: CC-BY 4.0
Copyrights: The authors retain unrestricted copyrights and publishing rights 
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Paquet, Matthieu; Barraquand, Frédéric. Assessing species interactions using integrated predator-prey models. Peer Community Journal, Volume 3 (2023), article  no. e105. doi : 10.24072/pcjournal.337. https://peercommunityjournal.org/articles/10.24072/pcjournal.337/

Peer reviewed and recommended by PCI : 10.24072/pci.ecology.100522

Conflict of interest of the recommender and peer reviewers:
The recommender in charge of the evaluation of the article and the reviewers declared that they have no conflict of interest (as defined in the code of conduct of PCI) with the authors or with the content of the article.

[1] Abadi, F.; Gimenez, O.; Ullrich, B.; Arlettaz, R.; Schaub, M. Estimation of Immigration Rate Using Integrated Population Models, Journal of Applied Ecology, Volume 47 (2010) no. 2, pp. 393-400 | DOI

[2] Auger-Méthé, M.; Field, C.; Albertsen, C. M.; Derocher, A. E.; Lewis, M. A.; Jonsen, I. D.; Mills Flemming, J. State-Space Models' Dirty Little Secrets: Even Simple Linear Gaussian Models Can Have Estimation Problems, Scientific reports, Volume 6 (2016) no. 1, pp. 1-10 | DOI

[3] Barker, R. J. Joint Analysis of Mark—Recapture, Resighting and Ring-Recovery Data with Age-Dependence and Marking-Effect, Bird study : the journal of the British Trust for Ornithology, Volume 46 (1999) no. sup1, p. S82-S91 | DOI

[4] Barraquand, F.; Gimenez, O. Integrating Multiple Data Sources to Fit Matrix Population Models for Interacting Species, Ecological modelling, Volume 411 (2019), p. 108713 | DOI

[5] Barraquand, F.; Picoche, C.; Detto, M.; Hartig, F. Inferring Species Interactions Using Granger Causality and Convergent Cross Mapping, Theoretical Ecology, Volume 14 (2021) no. 1, pp. 87-105 | DOI

[6] Besbeas, P.; Freeman, S. N.; Morgan, B. J. T.; Catchpole, E. A. Integrating Mark–Recapture–Recovery and Census Data to Estimate Animal Abundance and Demographic Parameters, Biometrics. Journal of the International Biometric Society, Volume 58 (2002) no. 3, pp. 540-547 | DOI

[7] Brooks, S. P.; Gelman, A. General Methods for Monitoring Convergence of Iterative Simulations, Journal of computational and graphical statistics, Volume 7 (1998) no. 4, pp. 434-455 | DOI

[8] Burnham, K. P. Design and Analysis Methods for Fish Survival Experiments Based on Release-Recapture, American Fisheries Society, 1987

[9] Chandler, R. B.; Clark, J. D. Spatially Explicit Integrated Population Models, Methods in Ecology and Evolution, Volume 5 (2014) no. 12, pp. 1351-1360 | DOI

[10] Coulson, T.; Alonso, D. Addressing the Daunting Challenge of Estimating Species Interactions from Count Data, Peer Community in Ecology, Volume 1 (2023), p. 100522 | DOI

[11] Dennis, B.; Ponciano, J. M.; Lele, S. R.; Taper, M. L.; Staples, D. F. Estimating Density Dependence, Process Noise, and Observation Error, Ecological Monographs, Volume 76 (2006) no. 3, pp. 323-341 | DOI

[12] Gelman, A.; Rubin, D. B. Inference from Iterative Simulation Using Multiple Sequences, Statistical science (1992), pp. 457-472 | DOI

[13] Knape, J. Estimability of Density Dependence in Models of Time Series Data, Ecology, Volume 89 (2008) no. 11, pp. 2994-3000 | DOI

[14] Kéry, M.; Schaub, M. Introduction, Bayesian Population Analysis using WinBUGS, Elsevier, 2012, pp. 1-21 | DOI

[15] Lahoz-Monfort, J. J.; Harris, M. P.; Wanless, S.; Freeman, S. N.; Morgan, B. J. T. Bringing It All Together: Multi-Species Integrated Population Modelling of a Breeding Community, Journal of Agricultural, Biological and Environmental Statistics, Volume 22 (2017) no. 2, pp. 140-160 | DOI

[16] McElreath, R. Statistical Rethinking: A Bayesian Course with Examples in R and Stan, Chapman and Hall/CRC, 2020 | DOI

[17] Mutshinda, C. M.; O'Hara, R. B.; Woiwod, I. P. What Drives Community Dynamics?, Proceedings of the Royal Society B: Biological Sciences, Volume 276 (2009) no. 1669, pp. 2923-2929 | DOI

[18] North, P. M.; Morgan, B. J. T. Modelling Heron Survival Using Weather Data, Biometrics. Journal of the International Biometric Society (1979), pp. 667-681 | DOI

[19] Paquet, M.; Arlt, D.; Knape, J.; Low, M.; Forslund, P.; Pärt, T. Quantifying the Links between Land Use and Population Growth Rate in a Declining Farmland Bird, Ecology and evolution, Volume 9 (2019) no. 2, pp. 868-879 | DOI

[20] Paquet, M.; Barraquand, F. Data and Code: Assessing Species Interactions Using Integrated Predator-Prey Models, 2023 | DOI

[21] Paquet, M.; Knape, J.; Arlt, D.; Forslund, P.; Pärt, T.; Flagstad, Ø.; Jones, C. G.; Nicoll, M. A. C.; Norris, K.; Pemberton, J. M.; Sand, H.; Svensson, L.; Tatayah, V.; Wabakken, P.; Wikenros, C.; Åkesson, M.; Low, M. Integrated Population Models Poorly Estimate the Demographic Contribution of Immigration, Methods in Ecology and Evolution, Volume 12 (2021) no. 10, pp. 1899-1910 | DOI

[22] Plard, F.; Turek, D.; Schaub, M. Consequences of Violating Assumptions of Integrated Population Models on Parameter Estimates, Environmental and Ecological Statistics, Volume 28 (2021) no. 3, pp. 667-695 | DOI

[23] Plummer, M. JAGS: A Program for Analysis of Bayesian Graphical Models Using Gibbs Sampling, Proceedings of the 3rd International Workshop on Distributed Statistical Computing, Volume 124, Vienna, Austria., 2003, pp. 1-10

[24] Plummer, M.; Best, N.; Cowles, K.; Vines, K. CODA: Convergence Diagnosis and Output Analysis for MCMC, R News, Volume 6 (2006) no. 1, pp. 7-11 (https://journal.r-project.org/articles/RN-2006-002/RN-2006-002.pdf)

[25] Ponisio, L. C.; de Valpine, P.; Michaud, N.; Turek, D. One Size Does Not Fit All: Customizing MCMC Methods for Hierarchical Models Using NIMBLE, Ecology and evolution, Volume 10 (2020) no. 5, pp. 2385-2416 | DOI

[26] Péron, G.; Koons, D. N. Integrated Modeling of Communities: Parasitism, Competition, and Demographic Synchrony in Sympatric Ducks, Ecology, Volume 93 (2012) no. 11, pp. 2456-2464 | DOI

[27] Quéroué, M.; Barbraud, C.; Barraquand, F.; Turek, D.; Delord, K.; Pacoureau, N.; Gimenez, O. Multispecies Integrated Population Model Reveals Bottom-up Dynamics in a Seabird Predator–Prey System, Ecological monographs, Volume 91 (2021) no. 3, p. e01459 | DOI

[28] R Core Team R: A Language and Environment for Statistical Computing, 2022 (https://www.R-project.org/)

[29] Reynolds, T. J.; King, R.; Harwood, J.; Frederiksen, M.; Harris, M. P.; Wanless, S. Integrated Data Analysis in the Presence of Emigration and Mark Loss, Journal of Agricultural, Biological, and Environmental Statistics, Volume 14 (2009) no. 4, pp. 411-431 | DOI

[30] Sander, E. L.; Wootton, J. T.; Allesina, S. Ecological Network Inference from Long-Term Presence-Absence Data, Scientific reports, Volume 7 (2017) no. 1, pp. 1-12 | DOI

[31] Seber, G. Estimating Survival Rates from Bird-Band Returns, The Journal of Wildlife Management (1972), pp. 405-413 | DOI

[32] Strydom, T.; Catchen, M. D.; Banville, F.; Caron, D.; Dansereau, G.; Desjardins-Proulx, P.; Forero-Muñoz, N. R.; Higino, G.; Mercier, B.; Gonzalez, A.; Gravel, D.; Pollock, L.; Poisot, T. A Roadmap towards Predicting Species Interaction Networks (across Space and Time), Philosophical Transactions of the Royal Society B, Volume 376 (2021) no. 1837, p. 20210063 | DOI

[33] Tibbits, M. M.; Groendyke, C.; Haran, M.; Liechty, J. C. Automated Factor Slice Sampling, Journal of Computational and Graphical Statistics, Volume 23 (2014) no. 2, pp. 543-563 | DOI

[34] Weegman, M. D.; Bearhop, S.; Fox, A. D.; Hilton, G. M.; Walsh, A. J.; McDonald, J. L.; Hodgson, D. J. Integrated Population Modelling Reveals a Perceived Source to Be a Cryptic Sink, Journal of Animal Ecology, Volume 85 (2016) no. 2, pp. 467-475 | DOI

[35] Zhao, Q. On the Sampling Design of Spatially Explicit Integrated Population Models, Methods in Ecology and Evolution, Volume 11 (2020) no. 10, pp. 1207-1220 | DOI

[36] de Valpine, P.; Paciorek, C.; Turek, D.; Michaud, N.; Anderson-Bergman, C.; Obermeyer, F.; Wehrhahn Cortes, C.; Rodríguez, A.; Temple Lang, D.; Paganin, S.; Hug, J. NIMBLE: MCMC, Particle Filtering, and Programmable Hierarchical Modeling, 2022 | DOI

[37] de Valpine, P.; Turek, D.; Paciorek, C.; Anderson-Bergman, C.; Temple Lang, D.; Bodik, R. Programming with Models: Writing Statistical Algorithms for General Model Structures with NIMBLE, Journal of Computational and Graphical Statistics, Volume 26 (2017), pp. 403-417 | DOI

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