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A multi-scaled analysis of forest structure using individual-based modeling in a costa rican rainforest

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  • Armstrong, A.H.
  • Huth, A.
  • Osmanoglu, B.
  • Sun, G.
  • Ranson, K.J.
  • Fischer, R.

Abstract

Consideration of scale is essential when examining structural relationships in forests. In this study, we present a parameterization of the FORMIND individual-based forest model for old growth Atlantic lowland rainforest in La Selva, Costa Rica. Results show that the simulated forest reproduces the structural complexity of Costa Rican rainforest within 2.3% of aboveground biomass values, based on comparisons with CARBONO inventory plot data. The Costa Rica FORMIND simulation was then used to investigate the relationship between canopy height and aboveground biomass (AGB), leaf area index (LAI) and gross primary productivity (GPP) at different spatial scales (20 × 20 m, 60 × 60 m, 100mx100m). The relationship between aboveground biomass and height is of particular importance toward the calibration of various remote sensing products including lidar and radar, whereas the LAI and GPP relationships are understudied in this context. We found that the relationship between all three variables and height varies considerably: the relationship is stronger at finer scales and weaker at coarser resolution. However, in all three comparisons, RMSE also decreased as scales coarsened, with the largest difference shown between 100 m and 10 m resolutions in relating AGB to Lorey's height (R2 decreased by 0.3; RMSE decreased by 114.5 Mg/ha). This suggests that a trade-off between accuracy and precision exists, and further highlights the importance of spatial scale in determining the relatability of forest structure variables.

Suggested Citation

  • Armstrong, A.H. & Huth, A. & Osmanoglu, B. & Sun, G. & Ranson, K.J. & Fischer, R., 2020. "A multi-scaled analysis of forest structure using individual-based modeling in a costa rican rainforest," Ecological Modelling, Elsevier, vol. 433(C).
    • Handle: RePEc:eee:ecomod:v:433:y:2020:i:c:s0304380020302969
    DOI: 10.1016/j.ecolmodel.2020.109226
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    1. Ribeiro, N.S. & Armstrong, Amanda Hildt & Fischer, Rico & Kim, Yeon-Su & Shugart, Herman Henry & Ribeiro-Barros, Ana I. & Chauque, Aniceto & Tear, T. & Washington-Allen, Robert & Bandeira, Romana R., 2021. "Prediction of forest parameters and carbon accounting under different fire regimes in Miombo woodlands, Niassa Special Reserve, Northern Mozambique," Forest Policy and Economics, Elsevier, vol. 133(C).

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