.png){kind=icon}
返回
Relative frequency function models for species distribution modeling
.png){kind=icon}
PRE
AI
DOI：10.1111/j.1600-0587.2012.07389.x.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A new approach to habitat distribution modeling is presented and tested with data on North American plants. The relative frequency function (RFF) algorithm compares the relative frequencies of a species sample points to that of random points or absence points on the landscape to compute a frequency ratio. The relative frequency ratio r is smoothed across the range of values using moving, overlapping windows. The ratio of frequencies at a sample point for each variable is used to compute the geometric mean score for all data with non-missing values. Variables are added using a forward stepwise method. Confidence intervals are computed with bootstrap resampling. The method was tested with artificial and species habitat and geographic range data. The RFF method in all cases gave results comparable to other methods tested. For the species with good geographic range maps, the results were consistent with known biogeography. The RFF method is particularly well-suited to irregularly shaped distributions and can classify sample points even when the data contain missing values. The method is extremely simple to use and comes with a free software tool, does not require a large sample size, does not require absence data, and is more interpretable and portable than certain other methods.
Keyword:
SPATIAL-DISTRIBUTION
LOGISTIC-REGRESSION
HABITAT
CLASSIFICATION
PREDICT
FOREST
PROBABILITY
PERFORMANCE
ALGORITHMS
ABUNDANCE
期刊
IF:
4.7
论文数:
3.4K
被引数:
1.8W
机构
暂无机构信息
引用论文
Novel methods improve prediction of species' distributions from occurrence data改进从发生数据预测物种分布的新方法.png)
ECOGRAPHY
OAAI
ECOGRAPHYIF4.7
OAAI分享收藏Effect of Age of Agave tequilana Weber Blue Variety on Quality and Authenticity Parameters for the Tequila 100% Agave Silver Class: Evaluation at the Industrial Scale LevelFoods
OAAI
FoodsIF0
OAAI分享收藏
查看更多内容