scholarly article | Q13442814 |
P50 | author | Dong Jiang | Q56863133 |
P2093 | author name string | Shuai Chen | |
Jingying Fu | |||
Mengmeng Hao | |||
Fangyu Ding | |||
P2860 | cites work | BIOTIC INVASIONS: CAUSES, EPIDEMIOLOGY, GLOBAL CONSEQUENCES, AND CONTROL | Q28315407 |
Trade, transport and trouble: managing invasive species pathways in an era of globalization | Q28342453 | ||
Mapping spatial pattern in biodiversity for regional conservation planning: where to from here? | Q31061670 | ||
The effects of sampling bias and model complexity on the predictive performance of MaxEnt species distribution models | Q34606307 | ||
Assessing the potential for establishment of western cherry fruit fly using ecological niche modeling. | Q35207189 | ||
Assessing the Global Risk of Establishment of Cydia pomonella (Lepidoptera: Tortricidae) using CLIMEX and MaxEnt Niche Models. | Q35809018 | ||
Molecular phylogeny and population structure of the codling moth (Cydia pomonella) in Central Europe: II. AFLP analysis reflects human-aided local adaptation of a global pest species | Q42028617 | ||
Correction: The Effects of Sampling Bias and Model Complexity on the Predictive Performance of MaxEnt Species Distribution Models. | Q45895750 | ||
Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria. | Q51172584 | ||
Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000 | Q56168542 | ||
WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas | Q56210311 | ||
Novel methods improve prediction of species’ distributions from occurrence data | Q57014231 | ||
Avoiding Pitfalls of Using Species Distribution Models in Conservation Planning | Q57016500 | ||
A statistical explanation of MaxEnt for ecologists | Q57062660 | ||
Response of Cydia pomonella to selection on mobility: laboratory evaluation and field verification | Q57308616 | ||
Flash flood susceptibility assessment in Jeddah city (Kingdom of Saudi Arabia) using bivariate and multivariate statistical models | Q57598112 | ||
Evaluating predictive models of species’ distributions: criteria for selecting optimal models | Q58006385 | ||
P275 | copyright license | Creative Commons Attribution 4.0 International | Q20007257 |
P6216 | copyright status | copyrighted | Q50423863 |
P4510 | describes a project that uses | ArcGIS | Q513297 |
P433 | issue | 1 | |
P407 | language of work or name | English | Q1860 |
P921 | main subject | machine learning | Q2539 |
Cydia pomonella | Q45262 | ||
P304 | page(s) | 13093 | |
P577 | publication date | 2018-08-30 | |
P1433 | published in | Scientific Reports | Q2261792 |
P1476 | title | Mapping the Potential Global Codling Moth (Cydia pomonella L.) Distribution Based on a Machine Learning Method | |
P478 | volume | 8 |
Q96230384 | Predictions of potential geographical distribution of Diaphorina citri (Kuwayama) in China under climate change scenarios | cites work | P2860 |
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