IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v363y2017icp187-191.html
   My bibliography  Save this article

Aggregation may or may not eliminate reproductive uncertainty

Author

Listed:
  • Logofet, Dmitrii O.

Abstract

In matrix population models, there cannot be any ‘reproductive uncertainty’ when the life cycle graph contains only one reproductive stage. Otherwise, it is logical to expect that aggregating all the reproductive stages into a single one would exclude the very basis of uncertainty. However, can the aggregation change principally the model characteristics such as the dominant eigenvalue λ1 of the projection matrix, thus signifying the aggregation failure? I demonstrate that it can with the data mined in a case study on the dynamics of a local stage-structured population of Eritrichium caucasicum, a short-lived perennial plant species inhabiting an alpine lichen heath. Frobenius Theorem for nonnegative matrices specifies the upper and lower bounds for λ1 via the row (or column) sums of matrix elements, and the lower bound, when it exceeds the maximal possible λ1 of the original, disaggregated matrix, does explain why the aggregation may fail to eliminate reproductive uncertainty.

Suggested Citation

  • Logofet, Dmitrii O., 2017. "Aggregation may or may not eliminate reproductive uncertainty," Ecological Modelling, Elsevier, vol. 363(C), pages 187-191.
    • Handle: RePEc:eee:ecomod:v:363:y:2017:i:c:p:187-191
    DOI: 10.1016/j.ecolmodel.2017.08.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380017303575
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2017.08.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Logofet, Dmitrii O., 2013. "Calamagrostis model revisited: Matrix calibration as a constraint maximization problem," Ecological Modelling, Elsevier, vol. 254(C), pages 71-79.
    2. Logofet, Dmitrii O., 2016. "Estimating the fitness of a local discrete-structured population: From uncertainty to an exact number," Ecological Modelling, Elsevier, vol. 329(C), pages 112-120.
    3. Logofet, Dmitrii O., 2008. "Convexity in projection matrices: Projection to a calibration problem," Ecological Modelling, Elsevier, vol. 216(2), pages 217-228.
    4. Marescot, Lucile & Gimenez, Olivier & Duchamp, Christophe & Marboutin, Eric & Chapron, Guillaume, 2012. "Reducing matrix population models with application to social animal species," Ecological Modelling, Elsevier, vol. 232(C), pages 91-96.
    5. Logofet, Dmitrii O., 2013. "Projection matrices in variable environments: λ1 in theory and practice," Ecological Modelling, Elsevier, vol. 251(C), pages 307-311.
    6. Oborny, B. & Mony, C. & Herben, T., 2012. "From virtual plants to real communities: A review of modelling clonal growth," Ecological Modelling, Elsevier, vol. 234(C), pages 3-19.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Logofet, Dmitrii O., 2019. "Does averaging overestimate or underestimate population growth? It depends," Ecological Modelling, Elsevier, vol. 411(C).
    2. Dmitrii O. Logofet & Leonid L. Golubyatnikov & Elena S. Kazantseva & Nina G. Ulanova, 2021. "“Realistic Choice of Annual Matrices Contracts the Range of λ S Estimates” under Reproductive Uncertainty Too," Mathematics, MDPI, vol. 9(23), pages 1-15, November.
    3. Dmitrii O. Logofet & Valerii N. Razzhevaikin, 2021. "Potential-Growth Indicators Revisited: Higher Generality and Wider Merit of Indication," Mathematics, MDPI, vol. 9(14), pages 1-15, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Logofet, Dmitrii O., 2019. "Does averaging overestimate or underestimate population growth? It depends," Ecological Modelling, Elsevier, vol. 411(C).
    2. Logofet, Dmitrii O., 2016. "Estimating the fitness of a local discrete-structured population: From uncertainty to an exact number," Ecological Modelling, Elsevier, vol. 329(C), pages 112-120.
    3. Logofet, Dmitrii O., 2013. "Projection matrices in variable environments: λ1 in theory and practice," Ecological Modelling, Elsevier, vol. 251(C), pages 307-311.
    4. Dmitrii O. Logofet & Leonid L. Golubyatnikov & Elena S. Kazantseva & Nina G. Ulanova, 2021. "“Realistic Choice of Annual Matrices Contracts the Range of λ S Estimates” under Reproductive Uncertainty Too," Mathematics, MDPI, vol. 9(23), pages 1-15, November.
    5. Bauduin, Sarah & Grente, Oksana & Santostasi, Nina Luisa & Ciucci, Paolo & Duchamp, Christophe & Gimenez, Olivier, 2020. "An individual-based model to explore the impacts of lesser-known social dynamics on wolf populations," Ecological Modelling, Elsevier, vol. 433(C).
    6. Logofet, Dmitrii O., 2013. "Calamagrostis model revisited: Matrix calibration as a constraint maximization problem," Ecological Modelling, Elsevier, vol. 254(C), pages 71-79.
    7. Logofet, Dmitrii O. & Kazantseva, Elena S. & Onipchenko, Vladimir G., 2020. "Seed bank as a persistent problem in matrix population models: From uncertainty to certain bounds," Ecological Modelling, Elsevier, vol. 438(C).
    8. Dmitrii O. Logofet & Leonid L. Golubyatnikov & Nina G. Ulanova, 2020. "Realistic Choice of Annual Matrices Contracts the Range of λ S Estimates," Mathematics, MDPI, vol. 8(12), pages 1-15, December.
    9. Hatlauf, J. & Kunz, F. & Griesberger, P. & Sachser, F. & Hackländer, K., 2024. "A stage-based life cycle implementation for individual-based population viability analyses of grey wolves (Canis lupus) in Europe," Ecological Modelling, Elsevier, vol. 491(C).
    10. Santostasi, Nina Luisa & Ciucci, Paolo & Bearzi, Giovanni & Bonizzoni, Silvia & Gimenez, Olivier, 2020. "Assessing the dynamics of hybridization through a matrix modelling approach," Ecological Modelling, Elsevier, vol. 431(C).
    11. Kim, Daehyun & Phillips, Jonathan D., 2013. "Predicting the structure and mode of vegetation dynamics: An application of graph theory to state-and-transition models," Ecological Modelling, Elsevier, vol. 265(C), pages 64-73.
    12. Chapron, Guillaume & Wikenros, Camilla & Liberg, Olof & Wabakken, Petter & Flagstad, Øystein & Milleret, Cyril & Månsson, Johan & Svensson, Linn & Zimmermann, Barbara & Åkesson, Mikael & Sand, Håkan, 2016. "Estimating wolf (Canis lupus) population size from number of packs and an individual based model," Ecological Modelling, Elsevier, vol. 339(C), pages 33-44.
    13. Dmitrii O. Logofet & Valerii N. Razzhevaikin, 2021. "Potential-Growth Indicators Revisited: Higher Generality and Wider Merit of Indication," Mathematics, MDPI, vol. 9(14), pages 1-15, July.
    14. Vladimir Yu. Protasov & Tatyana I. Zaitseva & Dmitrii O. Logofet, 2022. "Pattern-Multiplicative Average of Nonnegative Matrices: When a Constrained Minimization Problem Requires Versatile Optimization Tools," Mathematics, MDPI, vol. 10(23), pages 1-15, November.
    15. Hamidi, A. El & Garbey, M. & Ali, N., 2012. "A PDE model of clonal plant competition with nonlinear diffusion," Ecological Modelling, Elsevier, vol. 234(C), pages 83-92.
    16. Frisman, E.Y. & Neverova, G.P. & Revutskaya, O.L., 2011. "Complex dynamics of the population with a simple age structure," Ecological Modelling, Elsevier, vol. 222(12), pages 1943-1950.
    17. Logofet, Dmitrii O. & Maslov, Alexander A., 2019. "Bilberry vs. cowberry in a Scots pine boreal forest: Exclusion or coexistence in a post-fire succession?," Ecological Modelling, Elsevier, vol. 401(C), pages 134-143.
    18. Picard, Nicolas & Ouédraogo, Dakis & Bar-Hen, Avner, 2010. "Choosing classes for size projection matrix models," Ecological Modelling, Elsevier, vol. 221(19), pages 2270-2279.
    19. Logofet, Dmitrii O. & Golubyatnikov, Leonid L. & Kazantseva, Elena S. & Belova, Iya N. & Ulanova, Nina G., 2023. "Thirteen years of monitoring an alpine short-lived perennial: Novel methods disprove the former assessment of population viability," Ecological Modelling, Elsevier, vol. 477(C).
    20. Thibaut Couturier & Sarah Bauduin & Guillelme Astruc & Aurélie Blanck & Coline Canonne & Thierry Chambert & Jules Chiffard & Alix Cosquer & Sarah Cubaynes & Laurence Curtet & Emmanuelle Dortel & Nolwe, 2023. "Building spaces of interactions between researchers and managers," Post-Print hal-04125409, HAL.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:363:y:2017:i:c:p:187-191. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.