Imaging spectroscopy predicts variable distance decay across contrasting Amazonian tree communities

Frederick C. Draper, Christopher Baraloto, Philip G. Brodrick, Oliver L. Phillips, Rodolfo Vasquez Martinez, Euridice N. Honorio Coronado, Timothy R. Baker, Ricardo Zárate Gómez, Carlos A. Amasifuen Guerra, Manuel Flores, Roosevelt Garcia Villacorta, Paul V. A. Fine, Luis Freitas, Abel Monteagudo-Mendoza, Roel J. W Brienen, Gregory P. Asner

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

The forests of Amazonia are among the most biodiverse on Earth, yet accurately quantifying how species composition varies through space (i.e., beta-diversity) remains a significant challenge. Here, we use high-fidelity airborne imaging spectroscopy from the Carnegie Airborne Observatory to quantify a key component of beta-diversity, the distance decay in species similarity through space, across three landscapes in Northern Peru. We then compared our derived distance decay relationships to theoretical expectations obtained from a Poisson Cluster Process, known to match well with empirical distance decay relationships at local scales. We used an unsupervised machine learning approach to estimate spatial turnover in species composition from the imaging spectroscopy data. We first validated this approach across two landscapes using an independent dataset of forest composition in 49 forest census plots (0.1–1.5 ha). We then applied our approach to three landscapes, which together represented terra firme clay forest, seasonally flooded forest and white-sand forest. We finally used our approach to quantify landscape-scale distance decay relationships and compared these with theoretical distance decay relationships derived from a Poisson Cluster Process. We found a significant correlation of similarity metrics between spectral data and forest plot data, suggesting that beta-diversity within and among forest types can be accurately estimated from airborne spectroscopic data using our unsupervised approach. We also found that estimated distance decay in species similarity varied among forest types, with seasonally flooded forests showing stronger distance decay than white-sand and terra firme forests. Finally, we demonstrated that distance decay relationships derived from the theoretical Poisson Cluster Process compare poorly with our empirical relationships. Synthesis. Our results demonstrate the efficacy of using high-fidelity imaging spectroscopy to estimate beta-diversity and continuous distance decay in lowland tropical forests. Furthermore, our findings suggest that distance decay relationships vary substantially among forest types, which has important implications for conserving these valuable ecosystems. Finally, we demonstrate that a theoretical Poisson Cluster Process poorly predicts distance decay in species similarity as conspecific aggregation occurs across a range of nested scales within larger landscapes.

Original languageEnglish (US)
Pages (from-to)696-710
Number of pages15
JournalJournal of Ecology
Volume107
Issue number2
DOIs
StatePublished - Mar 2019
Externally publishedYes

Fingerprint

spectroscopy
deterioration
image analysis
forest types
sand
species diversity
artificial intelligence
lowland forests
Amazonia
Peru
spectral analysis
tropical forests
tropical forest
census
turnover
clay
observatory
synthesis
ecosystems
ecosystem

Keywords

  • Amazonian forests
  • beta diversity
  • determinants of plant community diversity and structure
  • distance decay
  • imaging spectroscopy
  • remote sensing
  • tree biodiversity
  • unsupervised clustering methods

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Ecology
  • Plant Science

Cite this

Draper, F. C., Baraloto, C., Brodrick, P. G., Phillips, O. L., Martinez, R. V., Honorio Coronado, E. N., ... Asner, G. P. (2019). Imaging spectroscopy predicts variable distance decay across contrasting Amazonian tree communities. Journal of Ecology, 107(2), 696-710. https://doi.org/10.1111/1365-2745.13067

Imaging spectroscopy predicts variable distance decay across contrasting Amazonian tree communities. / Draper, Frederick C.; Baraloto, Christopher; Brodrick, Philip G.; Phillips, Oliver L.; Martinez, Rodolfo Vasquez; Honorio Coronado, Euridice N.; Baker, Timothy R.; Zárate Gómez, Ricardo; Amasifuen Guerra, Carlos A.; Flores, Manuel; Garcia Villacorta, Roosevelt; V. A. Fine, Paul; Freitas, Luis; Monteagudo-Mendoza, Abel; J. W Brienen, Roel; Asner, Gregory P.

In: Journal of Ecology, Vol. 107, No. 2, 03.2019, p. 696-710.

Research output: Contribution to journalArticle

Draper, FC, Baraloto, C, Brodrick, PG, Phillips, OL, Martinez, RV, Honorio Coronado, EN, Baker, TR, Zárate Gómez, R, Amasifuen Guerra, CA, Flores, M, Garcia Villacorta, R, V. A. Fine, P, Freitas, L, Monteagudo-Mendoza, A, J. W Brienen, R & Asner, GP 2019, 'Imaging spectroscopy predicts variable distance decay across contrasting Amazonian tree communities', Journal of Ecology, vol. 107, no. 2, pp. 696-710. https://doi.org/10.1111/1365-2745.13067
Draper FC, Baraloto C, Brodrick PG, Phillips OL, Martinez RV, Honorio Coronado EN et al. Imaging spectroscopy predicts variable distance decay across contrasting Amazonian tree communities. Journal of Ecology. 2019 Mar;107(2):696-710. https://doi.org/10.1111/1365-2745.13067
Draper, Frederick C. ; Baraloto, Christopher ; Brodrick, Philip G. ; Phillips, Oliver L. ; Martinez, Rodolfo Vasquez ; Honorio Coronado, Euridice N. ; Baker, Timothy R. ; Zárate Gómez, Ricardo ; Amasifuen Guerra, Carlos A. ; Flores, Manuel ; Garcia Villacorta, Roosevelt ; V. A. Fine, Paul ; Freitas, Luis ; Monteagudo-Mendoza, Abel ; J. W Brienen, Roel ; Asner, Gregory P. / Imaging spectroscopy predicts variable distance decay across contrasting Amazonian tree communities. In: Journal of Ecology. 2019 ; Vol. 107, No. 2. pp. 696-710.
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AU - Flores, Manuel

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