Correction of location errors for presence-only species distribution models
نویسندگان
چکیده
منابع مشابه
Logistic methods for resource selection functions and presence-only species distribution models
In order to better protect and conserve biodiversity, ecologists are making increasing use of machine learning and statistical modeling to understand how species respond to their environment and to predict how they will respond to future climate change, habitat loss and other threats. A fundamental modeling task is to estimate the conditional probability that a given species is present in (or u...
متن کاملLogistic Methods for Resource Selection Functions and Presence-Only Species Distribution Models
In order to better protect and conserve biodiversity, ecologists use machine learning and statistics to understand how species respond to their environment and to predict how they will respond to future climate change, habitat loss and other threats. A fundamental modeling task is to estimate the probability that a given species is present in (or uses) a site, conditional on environmental varia...
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In practical situations, distribution network loads are the mixtures of residential, industrial, and commercial types. This paper presents a hybrid optimization algorithm for the optimal placement of shunt capacitor banks in radial distribution networks in the presence of different voltage-dependent load models. The algorithm is based on the combination of Genetic Algorithm (GA) and Binary Part...
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Spatial records of species are commonly misidentified, which can change the predicted distribution of a species obtained from a species distribution model (SDM). Experiments were undertaken to predict the distribution of real and simulated species using MaxEnt and presence-only data contaminated with varying rates of misidentification error. Additionally, the difference between the niche of t...
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ژورنال
عنوان ژورنال: Methods in Ecology and Evolution
سال: 2013
ISSN: 2041-210X
DOI: 10.1111/2041-210x.12144