Estimating Species Abundance from Presence–Absence Maps by Kernel Estimation
學年 112
學期 1
出版（發表）日期 2023-12-01
作品名稱 Estimating Species Abundance from Presence–Absence Maps by Kernel Estimation
作品名稱（其他語言）
著者 Chang, Ya-mei
單位
出版者
著錄名稱、卷期、頁數 Journal of Agricultural, Biological and Environmental Statistics
摘要 We present a novel method for estimating species abundance using presence–absence maps. Our approach takes the spatial context into consideration, distinguishing it from conventional methods. The proposed method is built upon a well-known kernel estimation for point pattern intensity, with the addition of a new parameter representing the mean abundance in each occupied cell. The parameter estimate is obtained through maximum likelihood estimation. The expected abundance corresponds to the integral of the intensity over the study area, which can be estimated by taking the Riemann sum of the intensity. The implementation of our method is straightforward, using existing packages in the R software. We compared various bandwidth selection methods within our approach and assessed the estimation performance against some approaches based on the random placement model or negative binomial model through the simulation study and an empirical forestry data in Barro Colorado Island (BCI), Panama. The results of the simulation and the application demonstrate that our method, with a carefully chosen bandwidth, outperforms the alternatives for highly aggregated data and improves the issue of underestimation. Supplementary materials accompanying this paper appear online.
關鍵字 Spatial aggregation;Bandwidth parameter;Negative binomial
語言 en_US
ISSN 1537-2693; 1085-7117
期刊性質 國外
收錄於 SCI
產學合作
通訊作者
審稿制度 是
國別 USA
公開徵稿
出版型式 ,電子版,紙本
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