tailieunhanh - Niche Modeling: Predictions From Statistical Distributions - Chapter 6

Trong chương này là một số ví dụ của các ứng dụng mới của mô hình thích hợp, lựa chọn chủ yếu để minh họa counterexamples quan trọng. Có thẩm quyền nghiên cứu mô hình thích hợp mô hình phản ứng của các loài như một 'U đảo ngược, và không tuyến tính phản ứng. Những ví dụ minh họa một số phản ứng khác thường hơn và sử dụng các chức năng ứng phó. Đầu tiên, chúng ta thảo luận về một số liệu thống kê để đánh giá kỹ năng của một mô hình thích hợp dựa trên. | Chapter 6 Examples In this chapter are some examples of novel applications of niche modeling selected primarily to illustrate important counterexamples. Most competent niche model studies model the response of the species as an inverted U and not linear responses. These examples illustrate some more unusual responses and uses of response functions. First we discuss a statistic for evaluating the skill of a niche model based on the idea of a draw from a population. The examples follow illustrating the steps followed in developing a niche model the use of presence only or presence absence data the use of a mask and the selection of variables. There are no hard and fast rules about these alternatives but they do influence results. The examples are house price increase Brown Treesnake threat and zebra mussel spread. Obviously house price increases is not a biological subject but is included to illustrate the generality of the approach. Model skill Accuracy is the observed proportion of predicted values correct. Perfect accuracy would look like Table . However the effective accuracy is only relative to the result expected if those predictions were made at random. For example if 100 of test items were labeled P then achieving perfect accuracy would require no skill. There are many way of determining the skill of models. In predicting presence and absence statistics such as the Receiver Operating Statistic ROC HM82 are effective and popular. Considering the specific case of randomly selected presence and absence points the area under the ROC curve is a measure of the probability that the model correctly identifies P and A. 97 2007 by Taylor and Francis Group LLC 98 Niche Modeling TABLE Example of a contingency table with a perfect score. P P A In presence absence analysis PA the absence points are explicitly specified but often absence points are not available. In presence-only analysis P the absence points are generated in some way .