TY - JOUR
T1 - Estimating abundance from presence/absence maps
AU - Hwang, Wen Han
AU - He, Fangliang
PY - 2011/10
Y1 - 2011/10
N2 - 1.An important question in macroecology is: Can we estimate a species' abundance from its occurrence on landscape? Answers to this question are useful for estimating population size from more easily acquired distribution data and for understanding the macroecological occupancy-abundance relationship. 2.Several methods have recently been developed to address this question, but no method is general enough to provide a common solution to all species because of the wide variation in spatial distribution of species. 3.In this study, we developed a mixed Gamma-Poisson model that generalizes the negative binomial model and can characterize spatial dependence in the abundance distribution across cells. Under this framework, without any extra information, the clumping parameter and species abundance can be estimated using a map aggregation technique. This model was tested using a set of empirical census data consisting of 299 tree species from a 50-ha stem-mapped plot of Panama. 4.A comparison showed that the new method outperformed the previous methods to an appreciable degree. Particularly for abundant species in a finely gridded map (5×5m), its bias is very small and the method can also reduce the root mean square error up to 30%. Like for previous methods, however, the new method's performance decreases with the increase in cell size. 5.As a by-product, the new method provides an approach to estimate spatial autocorrelation of species distribution which is otherwise difficult to estimate for presence/absence map.
AB - 1.An important question in macroecology is: Can we estimate a species' abundance from its occurrence on landscape? Answers to this question are useful for estimating population size from more easily acquired distribution data and for understanding the macroecological occupancy-abundance relationship. 2.Several methods have recently been developed to address this question, but no method is general enough to provide a common solution to all species because of the wide variation in spatial distribution of species. 3.In this study, we developed a mixed Gamma-Poisson model that generalizes the negative binomial model and can characterize spatial dependence in the abundance distribution across cells. Under this framework, without any extra information, the clumping parameter and species abundance can be estimated using a map aggregation technique. This model was tested using a set of empirical census data consisting of 299 tree species from a 50-ha stem-mapped plot of Panama. 4.A comparison showed that the new method outperformed the previous methods to an appreciable degree. Particularly for abundant species in a finely gridded map (5×5m), its bias is very small and the method can also reduce the root mean square error up to 30%. Like for previous methods, however, the new method's performance decreases with the increase in cell size. 5.As a by-product, the new method provides an approach to estimate spatial autocorrelation of species distribution which is otherwise difficult to estimate for presence/absence map.
KW - Clumping parameter
KW - Gamma-Poisson distribution
KW - Negative binomial distribution
KW - Presence-absence map
KW - Spatial aggregation
KW - Species abundance
UR - https://www.scopus.com/pages/publications/84864280981
U2 - 10.1111/j.2041-210X.2011.00105.x
DO - 10.1111/j.2041-210X.2011.00105.x
M3 - 文章
AN - SCOPUS:84864280981
SN - 2041-210X
VL - 2
SP - 550
EP - 559
JO - Methods in Ecology and Evolution
JF - Methods in Ecology and Evolution
IS - 5
ER -