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Field methods for sampling tree height for tropical forest biomass estimation

Overview of attention for article published in Methods in Ecology and Evolution, February 2018
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

Mentioned by

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78 tweeters
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1 Facebook page

Citations

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31 Dimensions

Readers on

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180 Mendeley
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1 CiteULike
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Title
Field methods for sampling tree height for tropical forest biomass estimation
Published in
Methods in Ecology and Evolution, February 2018
DOI 10.1111/2041-210x.12962
Pubmed ID
Authors

Martin J. P. Sullivan, Simon L. Lewis, Wannes Hubau, Lan Qie, Timothy R. Baker, Lindsay F. Banin, Jerôme Chave, Aida Cuni‐Sanchez, Ted R. Feldpausch, Gabriela Lopez‐Gonzalez, Eric Arets, Peter Ashton, Jean‐François Bastin, Nicholas J. Berry, Jan Bogaert, Rene Boot, Francis Q. Brearley, Roel Brienen, David F. R. P. Burslem, Charles Canniere, Markéta Chudomelová, Martin Dančák, Corneille Ewango, Radim Hédl, Jon Lloyd, Jean‐Remy Makana, Yadvinder Malhi, Beatriz S. Marimon, Ben Hur Marimon Junior, Faizah Metali, Sam Moore, Laszlo Nagy, Percy Nuñez Vargas, Colin A. Pendry, Hirma Ramírez‐Angulo, Jan Reitsma, Ervan Rutishauser, Kamariah Abu Salim, Bonaventure Sonké, Rahayu S. Sukri, Terry Sunderland, Martin Svátek, Peter M. Umunay, Rodolfo Vasquez Martinez, Ronald R. E. Vernimmen, Emilio Vilanova Torre, Jason Vleminckx, Vincent Vos, Oliver L. Phillips

Abstract

Quantifying the relationship between tree diameter and height is a key component of efforts to estimate biomass and carbon stocks in tropical forests. Although substantial site-to-site variation in height-diameter allometries has been documented, the time consuming nature of measuring all tree heights in an inventory plot means that most studies do not include height, or else use generic pan-tropical or regional allometric equations to estimate height.Using a pan-tropical dataset of 73 plots where at least 150 trees had in-field ground-based height measurements, we examined how the number of trees sampled affects the performance of locally derived height-diameter allometries, and evaluated the performance of different methods for sampling trees for height measurement.Using cross-validation, we found that allometries constructed with just 20 locally measured values could often predict tree height with lower error than regional or climate-based allometries (mean reduction in prediction error = 0.46 m). The predictive performance of locally derived allometries improved with sample size, but with diminishing returns in performance gains when more than 40 trees were sampled. Estimates of stand-level biomass produced using local allometries to estimate tree height show no over- or under-estimation bias when compared with biomass estimates using field measured heights. We evaluated five strategies to sample trees for height measurement, and found that sampling strategies that included measuring the heights of the ten largest diameter trees in a plot outperformed (in terms of resulting in local height-diameter models with low height prediction error) entirely random or diameter size-class stratified approaches.Our results indicate that even limited sampling of heights can be used to refine height-diameter allometries. We recommend aiming for a conservative threshold of sampling 50 trees per location for height measurement, and including the ten trees with the largest diameter in this sample.

Twitter Demographics

The data shown below were collected from the profiles of 78 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 180 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 180 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 45 25%
Student > Ph. D. Student 30 17%
Student > Master 26 14%
Professor 10 6%
Student > Doctoral Student 9 5%
Other 36 20%
Unknown 24 13%
Readers by discipline Count As %
Environmental Science 63 35%
Agricultural and Biological Sciences 60 33%
Earth and Planetary Sciences 11 6%
Engineering 4 2%
Social Sciences 2 1%
Other 7 4%
Unknown 33 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 49. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 March 2019.
All research outputs
#453,670
of 15,711,421 outputs
Outputs from Methods in Ecology and Evolution
#177
of 1,622 outputs
Outputs of similar age
#18,595
of 407,156 outputs
Outputs of similar age from Methods in Ecology and Evolution
#16
of 77 outputs
Altmetric has tracked 15,711,421 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,622 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 24.3. This one has done well, scoring higher than 89% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 407,156 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 77 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.