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キーワード:
Carbon dioxide
Global environmental change
Long-term monitoring
Modelling
Neotropics
Palaeotropics
Permanent sample plot
Rain forest
Tree
Tropical forest dynamics
Rain-forest
Evaluating turnover
Dynamics
Diversity
Amazon
Scale
Plots
Communities
Vegetation
Biomass
要旨:
1. Mathematical proofs show that rate estimates, for example of mortality and recruitment, will decrease with increasing census interval when obtained from censuses of non-homogeneous populations. This census interval effect could be confounding or perhaps even driving conclusions from comparative studies involving such rate estimates. correction methods and re-assess some previously published conclusions about forest dynamics. Latin America, Asia and Australia were used as subpopulations to simulate stand-level mortality rates in a heterogeneous population when census intervals varied: all sites showed decreasing stand mortality rates with increasing census interval length. plots from Africa, Latin America, Asia and Australia also showed that, on average, mortality rates decreased with increasing census interval length. interval lengths can be compared using the mean rate of decline from the 14 long-term plots to standardize estimates to a common census length using lambda(corr) = lambda x t(0.08), where lambda is the rate and t is time between censuses in years. This simple general correction should reduce the bias associated with census interval variation, where it is unavoidable. increase in stem turnover rates over the late 20th century cannot be attributed to combining data with differing census intervals. In addition, after correction, Old World tropical forests do not have significantly lower turnover rates than New World sites, as previously reported. Our pan-tropical best estimate adjusted stem turnover rate is 1.81 ± 0.16% a(-1) (mean ± 95% CI, n = 65). recruitment and turnover rates, and can lead to erroneous conclusions, standardized field methods, the calculation of local correction factors at sites where adequate data are available, or the use of our general standardizing formula to take account of sample intervals, are to be recommended. [References: 49]
