Chronosequence predictions are robust in a Neotropical secondary forest, but plots miss the mark. (22nd January 2018)

• Record Type: Journal Article
• Authors: Becknell, Justin M.; Porder, Stephen; Hancock, Steven; Chazdon, Robin L.; Hofton, Michelle A.; Blair, James B.; Kellner, James R.
• Is Part Of: Global change biology. Volume 24:Number 3(2018)
• Page Start: 933
• Page End: 943
• Publication Date: 2018-01-22
• Subjects: biomass -- La Selva -- Land Vegetation and Ice Sensor -- secondary succession -- tropical forest -- waveform lidar; Climatic changes -- Environmental aspects -- Periodicals; Troposphere -- Environmental aspects -- Periodicals; Biodiversity conservation -- Periodicals; Eutrophication -- Periodicals; 551.5
• DOI: 10.1111/gcb.14036
• Languages: English
• ISSNs: 1354-1013

Abstract

Abstract: 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. Abstract : To test the accuracy of height and biomass predictions from a tropical secondary forest (TSF) chronosequence, we compared measurements from airborne lidar separated by 11.5 years and found that observations were within 1.1% and 10.3% of predictions at the landscape‐scale. Next, we quantified how well plot estimates matched these landscape‐scale predictions, and found that sample sizes required to produce estimates close to the landscape mean were larger than those typically used in plot studies. Under‐sampling in ground‐based studies may introduce error into estimates of the TSF carbon sink, but landscape‐scale measurements with lidar can reduce this error.