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Chronosequence predictions are robust in a Neotropical secondary forest, but plots miss the mark
Author(s) -
Becknell Justin M.,
Porder Stephen,
Hancock Steven,
Chazdon Robin L.,
Hofton Michelle A.,
Blair James B.,
Kellner James R.
Publication year - 2018
Publication title -
global change biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.146
H-Index - 255
eISSN - 1365-2486
pISSN - 1354-1013
DOI - 10.1111/gcb.14036
Subject(s) - chronosequence , lidar , environmental science , canopy , secondary forest , carbon sink , tropical forest , biomass (ecology) , physical geography , atmospheric sciences , forestry , ecology , geography , climate change , remote sensing , agroforestry , soil science , geology , biology , soil water
Tropical secondary forests (TSF) are a global carbon sink of 1.6 Pg C/year. However, TSF carbon uptake is estimated using chronosequence studies that assume differently aged forests can be used to predict change in aboveground biomass density (AGBD) over time. We tested this assumption using two airborne lidar datasets separated by 11.5 years over a Neotropical landscape. Using data from 1998, we predicted canopy height and AGBD within 1.1 and 10.3% of observations in 2009, with higher accuracy for forest height than AGBD and for older TSFs in comparison to younger ones. This result indicates that the space‐for‐time assumption is robust at the landscape‐scale. However, since lidar measurements of secondary tropical forest are rare, we used the 1998 lidar dataset to test how well plot‐based studies quantify the mean TSF height and biomass in a landscape. We found that the sample area required to produce estimates of height or AGBD close to the landscape mean is larger than the typical area sampled in secondary forest chronosequence studies. For example, estimating AGBD within 10% of the landscape mean requires more than thirty 0.1 ha plots per age class, and more total area for larger plots. We conclude that under‐sampling in ground‐based studies may introduce error into estimations of the TSF carbon sink, and that this error can be reduced by more extensive use of lidar measurements.