In:
Biogeosciences, Copernicus GmbH, Vol. 17, No. 6 ( 2020-03-30), p. 1673-1683
Abstract:
Abstract. Tropical forests play an important role in the global carbon cycle as
they store a large amount of carbon in their biomass. To estimate the
mean biomass of a forested landscape, sample plots are often used,
assuming that the biomass of these plots represents the biomass of the
surrounding forest. In this study, we investigated the conditions under which a limited
number of sample plots conform to this assumption. Therefore, the minimum
number of sample sizes for predicting the mean biomass of tropical
forest landscapes was determined by combining statistical methods
with simulations of sampling strategies. We examined forest biomass
maps of Barro Colorado Island (50 ha), Panama
(50 000 km2), and South America, Africa, and Southeast Asia
(3 × 106–11 × 106 km2). The results showed that around 100 plots (1–25 ha each) are
necessary for continent-wide biomass estimations if the sampled
plots are randomly distributed. However, locations of current
inventory plots often do not meet this requirement, for example, as their sampling design is based on spatial transects among climatic
gradients. We show that these nonrandom locations lead to a much
higher sampling intensity being required (up to 54 000 plots for accurate
biomass estimates for South America). The number of sample plots
needed can be reduced using large distances (5 km) between the
plots within transects. We also applied novel point pattern reconstruction methods to account
for aggregation of inventory plots in known forest plot
networks. The results implied that current plot networks can have
clustered structures that reduce the accuracy of large-scale estimates
of forest biomass if no further statistical approach is applied. To
establish more reliable biomass predictions across South American
tropical forests, we recommend more spatially randomly distributed
inventory plots (minimum: 100 plots) and ensuring that the analyses of
inventory plot data consider their spatial characteristics. The
precision of forest attribute estimates depends on the sampling
intensity and strategy.
Type of Medium:
Online Resource
ISSN:
1726-4189
DOI:
10.5194/bg-17-1673-2020
DOI:
10.5194/bg-17-1673-2020-supplement
Language:
English
Publisher:
Copernicus GmbH
Publication Date:
2020
detail.hit.zdb_id:
2158181-2
