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A network theoretic study of ecological connectivity in Western Himalayas

Author

Listed:
  • Upadhyay, Shashankaditya
  • Roy, Arijit
  • Ramprakash, M.
  • Idiculla, Jobin
  • Kumar, A. Senthil
  • Bhattacharya, Sudeepto

Abstract

Network theoretic approach has been used to model and study the flow of ecological information, growth and connectivity on landscape level of anemochory (wind dispersal) of Himalayan moist temperate forest species in the Western Himalaya region. A network is formally defined and derived for seed dispersion model of target floral species where vertices represent habitat patches which are connected by an edge if the distance between the patches is less than a threshold distance. We define centrality of a network and computationally identify the habitat patches that are central to the process of seed dispersion to occur across the network. These central patches are located on map and geographical regions critically important for the flow of ecological information across the network are identified as Gharwal region and eastern Himachal Pradesh of Indian Himalaya. We find that the network of habitat patches is a scale-free network and at the same time it also displays small-world property characterized by high clustering and low average shortest path length. As a result, ecological information propagates rapidly and evenly on a local scale. Hubs in the network are identified as important centres for dissemination of ecological information (seeds) and need to be conserved against a potential attack by malicious agents and also ecological shocks. The network showcase a well-formed community structure. As a consequence of these structural properties of the network, anemochory floral species studied in this work are likely to thrive across the ecological network of forest patches in the Western Himalaya region over time.

Suggested Citation

  • Upadhyay, Shashankaditya & Roy, Arijit & Ramprakash, M. & Idiculla, Jobin & Kumar, A. Senthil & Bhattacharya, Sudeepto, 2017. "A network theoretic study of ecological connectivity in Western Himalayas," Ecological Modelling, Elsevier, vol. 359(C), pages 246-257.
  • Handle: RePEc:eee:ecomod:v:359:y:2017:i:c:p:246-257
    DOI: 10.1016/j.ecolmodel.2017.05.027
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    References listed on IDEAS

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    1. Fath, Brian D. & Scharler, Ursula M. & Baird, Dan, 2013. "Dependence of network metrics on model aggregation and throughflow calculations: Demonstration using the Sylt–Rømø Bight Ecosystem," Ecological Modelling, Elsevier, vol. 252(C), pages 214-219.
    2. Scharler, Ursula M. & Fath, Brian D., 2009. "Comparing network analysis methodologies for consumer–resource relations at species and ecosystems scales," Ecological Modelling, Elsevier, vol. 220(22), pages 3210-3218.
    3. Roy, Arijit & Bhattacharya, Sudeepto & Ramprakash, M. & Senthil Kumar, A., 2016. "Modelling critical patches of connectivity for invasive Maling bamboo (Yushania maling) in Darjeeling Himalayas using graph theoretic approach," Ecological Modelling, Elsevier, vol. 329(C), pages 77-85.
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    Cited by:

    1. Men, Dan & Pan, Jinghu, 2023. "Ecological network identification and connectivity robustness evaluation in the Yellow River Basin under a multi-scenario simulation," Ecological Modelling, Elsevier, vol. 482(C).
    2. Upadhyay, Shashankaditya & Banerjee, Anirban & Panigrahi, Prasanta K., 2020. "Causal evolution of global crisis in financial networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
    3. Jianfeng Zhu & Lijun Yu & Yueping Nie & Fang Liu & Yu Sun & Yuanzhi Zhang & Wenping Song, 2019. "Ancient Environmental Preference and the Site Selection Pattern Based on the Edge Effect and Network Structure in An Ecosystem," Sustainability, MDPI, vol. 12(1), pages 1-23, December.
    4. Upadhyay, Shashankaditya & Mukherjee, Indranil & Panigrahi, Prasanta K., 2023. "Inner composition alignment networks reveal financial impacts of COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).

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