IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v483y2023ics0304380023001497.html
   My bibliography  Save this article

A common framework to model recovery in disturbed tropical forests

Author

Listed:
  • Maurent, Eliott
  • Hérault, Bruno
  • Piponiot, Camille
  • Derroire, Géraldine
  • Delgado, Diego
  • Finegan, Bryan
  • Kientz, Mélaine Aubry
  • Amani, Bienvenu H.K.
  • Bieng, Marie Ange Ngo

Abstract

1. Despite their exceptional biodiversity and carbon stocks, more than 80% of tropical forests are disturbed. However, a lot of interrogations remain around the ability of vegetation attributes in tropical forests to recover from the various anthropogenic disturbances coexisting in many tropical landscapes. While these different disturbances are usually studied separately, this work provides, for the first time, a common modelling framework of vegetation attribute recovery in differently disturbed forests.

Suggested Citation

  • Maurent, Eliott & Hérault, Bruno & Piponiot, Camille & Derroire, Géraldine & Delgado, Diego & Finegan, Bryan & Kientz, Mélaine Aubry & Amani, Bienvenu H.K. & Bieng, Marie Ange Ngo, 2023. "A common framework to model recovery in disturbed tropical forests," Ecological Modelling, Elsevier, vol. 483(C).
    • Handle: RePEc:eee:ecomod:v:483:y:2023:i:c:s0304380023001497
    DOI: 10.1016/j.ecolmodel.2023.110418
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380023001497
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2023.110418?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. Carpenter, Bob & Gelman, Andrew & Hoffman, Matthew D. & Lee, Daniel & Goodrich, Ben & Betancourt, Michael & Brubaker, Marcus & Guo, Jiqiang & Li, Peter & Riddell, Allen, 2017. "Stan: A Probabilistic Programming Language," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 76(i01).
    2. Marcon, Eric & Hérault, Bruno, 2015. "entropart: An R Package to Measure and Partition Diversity," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i08).
    3. Piponiot, Camille & Derroire, Géraldine & Descroix, Laurent & Mazzei, Lucas & Rutishauser, Ervan & Sist, Plinio & Hérault, Bruno, 2018. "Assessing timber volume recovery after disturbance in tropical forests – A new modelling framework," Ecological Modelling, Elsevier, vol. 384(C), pages 353-369.
    4. Rattan Lal, 2015. "Restoring Soil Quality to Mitigate Soil Degradation," Sustainability, MDPI, vol. 7(5), pages 1-21, May.
    Full references (including those not matched with items on IDEAS)

    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. Ahmad A. Al-Ghamdi & Yilma Tadesse & Nuru Adgaba & Abdulaziz G. Alghamdi, 2021. "Soil Degradation and Restoration in Southwestern Saudi Arabia through Investigation of Soil Physiochemical Characteristics and Nutrient Status as Indicators," Sustainability, MDPI, vol. 13(16), pages 1-19, August.
    2. Francis,David C. & Kubinec ,Robert, 2022. "Beyond Political Connections : A Measurement Model Approach to Estimating Firm-levelPolitical Influence in 41 Economies," Policy Research Working Paper Series 10119, The World Bank.
    3. Yongping Bao & Ludwig Danwitz & Fabian Dvorak & Sebastian Fehrler & Lars Hornuf & Hsuan Yu Lin & Bettina von Helversen, 2022. "Similarity and Consistency in Algorithm-Guided Exploration," CESifo Working Paper Series 10188, CESifo.
    4. Torsten Heinrich & Jangho Yang & Shuanping Dai, 2020. "Growth, development, and structural change at the firm-level: The example of the PR China," Papers 2012.14503, arXiv.org.
    5. Sriroop Chaudhuri & Mimi Roy & Louis M. McDonald & Yves Emendack, 2023. "Land Degradation–Desertification in Relation to Farming Practices in India: An Overview of Current Practices and Agro-Policy Perspectives," Sustainability, MDPI, vol. 15(8), pages 1-27, April.
    6. Xin Xu & Yang Lu & Yupeng Zhou & Zhiguo Fu & Yanjie Fu & Minghao Yin, 2021. "An Information-Explainable Random Walk Based Unsupervised Network Representation Learning Framework on Node Classification Tasks," Mathematics, MDPI, vol. 9(15), pages 1-14, July.
    7. Xiaoyue Xi & Simon E. F. Spencer & Matthew Hall & M. Kate Grabowski & Joseph Kagaayi & Oliver Ratmann & Rakai Health Sciences Program and PANGEA‐HIV, 2022. "Inferring the sources of HIV infection in Africa from deep‐sequence data with semi‐parametric Bayesian Poisson flow models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 517-540, June.
    8. Luo, Nanyu & Ji, Feng & Han, Yuting & He, Jinbo & Zhang, Xiaoya, 2024. "Fitting item response theory models using deep learning computational frameworks," OSF Preprints tjxab, Center for Open Science.
    9. Joseph B. Bak-Coleman & Ian Kennedy & Morgan Wack & Andrew Beers & Joseph S. Schafer & Emma S. Spiro & Kate Starbird & Jevin D. West, 2022. "Combining interventions to reduce the spread of viral misinformation," Nature Human Behaviour, Nature, vol. 6(10), pages 1372-1380, October.
    10. David M. Phillippo & Sofia Dias & A. E. Ades & Mark Belger & Alan Brnabic & Alexander Schacht & Daniel Saure & Zbigniew Kadziola & Nicky J. Welton, 2020. "Multilevel network meta‐regression for population‐adjusted treatment comparisons," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 1189-1210, June.
    11. Romero, Pascual & Navarro, Josefa María & Ordaz, Pablo Botía, 2022. "Towards a sustainable viticulture: The combination of deficit irrigation strategies and agroecological practices in Mediterranean vineyards. A review and update," Agricultural Water Management, Elsevier, vol. 259(C).
    12. Alina Ferecatu & Arnaud Bruyn & Prithwiraj Mukherjee, 2024. "Silently killing your panelists one email at a time: The true cost of email solicitations," Journal of the Academy of Marketing Science, Springer, vol. 52(4), pages 1216-1239, July.
    13. Burbano, Vanessa & Padilla, Nicolas & Meier, Stephan, 2020. "Gender Differences in Preferences for Meaning at Work," IZA Discussion Papers 13053, Institute of Labor Economics (IZA).
    14. Robert Kubinec & Haillie Na‐Kyung Lee & Andrey Tomashevskiy, 2021. "Politically connected companies are less likely to shutdown due to COVID‐19 restrictions," Social Science Quarterly, Southwestern Social Science Association, vol. 102(5), pages 2155-2169, September.
    15. Barrington-Leigh, C.P., 2024. "The econometrics of happiness: Are we underestimating the returns to education and income?," Journal of Public Economics, Elsevier, vol. 230(C).
    16. Grażyna Żukowska & Magdalena Myszura-Dymek & Szymon Roszkowski & Magdalena Olkiewicz, 2023. "Selected Properties of Soil-like Substrates Made from Mine Coal Waste and Their Effect on Plant Yields," Sustainability, MDPI, vol. 15(18), pages 1-19, September.
    17. Salvatore Nunnari & Massimiliano Pozzi, 2022. "Meta-Analysis of Inequality Aversion Estimates," CESifo Working Paper Series 9851, CESifo.
    18. Andreas Kryger Jensen & Claus Thorn Ekstrøm, 2021. "Quantifying the trendiness of trends," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(1), pages 98-121, January.
    19. Lauderdale, Benjamin E. & Bailey, Delia & Blumenau, Jack & Rivers, Douglas, 2020. "Model-based pre-election polling for national and sub-national outcomes in the US and UK," International Journal of Forecasting, Elsevier, vol. 36(2), pages 399-413.
    20. Anna Kocira & Mariola Staniak & Marzena Tomaszewska & Rafał Kornas & Jacek Cymerman & Katarzyna Panasiewicz & Halina Lipińska, 2020. "Legume Cover Crops as One of the Elements of Strategic Weed Management and Soil Quality Improvement. A Review," Agriculture, MDPI, vol. 10(9), pages 1-41, September.

    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:483:y:2023:i:c:s0304380023001497. 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.