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Climate, rather than human disturbance, is the main driver of age-specific mortality trajectories in a tropical tree

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  • Gaoue, Orou G.
  • Horvitz, Carol C.
  • Steiner, Ulrich K.
  • Tuljapurkar, Shripad

Abstract

Environmental and anthropogenic stressors can interact (e.g., drought, harvest or herbivory) to shape plant demography and evolutionary strategies with implications for sustainable resource management plans. Harvest or recurrent biomass removal can act as a selective force. However, our understanding of how harvest and changes in climate can synergistically shape plant evolutionary strategies is limited. We used age-from-stage matrix modeling to investigate how chronic anthropogenic disturbance (severe foliage and bark harvest) affects age-specific mortality trajectories of a tropical tree, Khaya senegalensis in two contrasting climatic regions (dry versus moist) in West Africa. We then developed a stochastic model to test if changes in disturbance regime and the environmental conditions in which a cohort is born may alter stochastic age-specific mortality rates. The effect of harvest on age-specific mortality trajectories was modest and only noticeable in the moist region. Age-specific mortality trajectories differed significantly between regions. In the moist region, mortality rates decreased with age for the first 30 years of life to a minimum rate and then increased gradually after to reach an old age mortality plateau. In the dry region, mortality rates decreased with age to reach a plateau asymptotically. This difference in age-specific mortality trajectory is due to a greater delay in reaching reproductive size/age in the dry region. Our findings underscore intraspecific variation in age-specific mortality schedules and indicate that climatic effect may override the impact of anthropogenic activities on plant demography. Harvest, by favoring fast life stage transition to reproductive stages, can buffer the effect of drought.

Suggested Citation

  • Gaoue, Orou G. & Horvitz, Carol C. & Steiner, Ulrich K. & Tuljapurkar, Shripad, 2019. "Climate, rather than human disturbance, is the main driver of age-specific mortality trajectories in a tropical tree," Ecological Modelling, Elsevier, vol. 400(C), pages 34-40.
  • Handle: RePEc:eee:ecomod:v:400:y:2019:i:c:p:34-40
    DOI: 10.1016/j.ecolmodel.2019.03.007
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    References listed on IDEAS

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    1. Nicole Guedje & Jean Lejoly & Bernard Aloys Nkongmeneck & W.B.J. W.B.J. Jonkers, 2003. "Population dynamics of Garcinia lucida (Clusiaceae) in Cameroonian Atlantic forests," ULB Institutional Repository 2013/181113, ULB -- Universite Libre de Bruxelles.
    2. James W. Vaupel & Annette Baudisch & Martin Dölling & Deborah A. Roach & Jutta Gampe, 2004. "The case for negative senescence," MPIDR Working Papers WP-2004-002, Max Planck Institute for Demographic Research, Rostock, Germany.
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