相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。ChatGPT listed as author on research papers: many scientists disapprove
Chris Stokel-Walker
NATURE (2023)
Machine learning in landscape ecological analysis: a review of recent approaches
Mihai-Sorin Stupariu et al.
LANDSCAPE ECOLOGY (2022)
Bridging the research-implementation gap in IUCN Red List assessments
Victor Cazalis et al.
TRENDS IN ECOLOGY & EVOLUTION (2022)
Interpretable machine learning: Fundamental principles and 10 grand challenges
Cynthia Rudin et al.
STATISTICS SURVEYS (2022)
A review of the heterogeneous landscape of biodiversity databases: Opportunities and challenges for a synthesized biodiversity knowledge base
Xiao Feng et al.
GLOBAL ECOLOGY AND BIOGEOGRAPHY (2022)
Conservation planning of the genus Rhododendron in Northeast China based on current and future suitable habitat distributions
Yupeng Lu et al.
BIODIVERSITY AND CONSERVATION (2021)
Potential distribution of Abies, Picea, and Juniperus species in the sub-alpine forest of Minjiang headwater region under current and future climate scenarios and its implications on ecosystem services supply
Niyati Naudiyal et al.
ECOLOGICAL INDICATORS (2021)
Deep learning for supervised classification of temporal data in ecology
Cesar Capinha et al.
ECOLOGICAL INFORMATICS (2021)
Automated detection of wildlife using drones: Synthesis, opportunities and constraints
Evangeline Corcoran et al.
METHODS IN ECOLOGY AND EVOLUTION (2021)
The four antelope species on the Qinghai-Tibet plateau face habitat loss and redistribution to higher latitudes under climate change
Jingjie Zhang et al.
ECOLOGICAL INDICATORS (2021)
The role of artificial intelligence in achieving the Sustainable Development Goals
Ricardo Vinuesa et al.
NATURE COMMUNICATIONS (2020)
A translucent box: interpretable machine learning in ecology
Tim C. D. Lucas
ECOLOGICAL MONOGRAPHS (2020)
Automated Discovery of Relationships, Models, and Principles in Ecology
Pedro Cardoso et al.
FRONTIERS IN ECOLOGY AND EVOLUTION (2020)
Applications for deep learning in ecology
Sylvain Christin et al.
METHODS IN ECOLOGY AND EVOLUTION (2019)
Research applications of primary biodiversity databases in the digital age
Joan E. Ball-Damerow et al.
PLOS ONE (2019)
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
Cynthia Rudin
NATURE MACHINE INTELLIGENCE (2019)
Automated global delineation of human settlements from 40 years of Landsat satellite data archives
Christina Corbane et al.
BIG EARTH DATA (2019)
Global patterns of current and future road infrastructure
Johan R. Meijer et al.
ENVIRONMENTAL RESEARCH LETTERS (2018)
Application of machine-learning methods in forest ecology: recent progress and future challenges
Zelin Liu et al.
ENVIRONMENTAL REVIEWS (2018)
Application of machine-learning methods in forest ecology: recent progress and future challenges
Zelin Liu et al.
ENVIRONMENTAL REVIEWS (2018)
WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas
Stephen E. Fick et al.
INTERNATIONAL JOURNAL OF CLIMATOLOGY (2017)
Data Descriptor: MERRAclim, a high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling
Greta C. Vega et al.
SCIENTIFIC DATA (2017)
Data Descriptor: Climatologies at high resolution for the earth's land surface areas
Dirk Nikolaus Karger et al.
SCIENTIFIC DATA (2017)
Collinearity: a review of methods to deal with it and a simulation study evaluating their performance
Carsten F. Dormann et al.
ECOGRAPHY (2013)
Identification of de facto protected areas in boreal Canada
Margaret E. Andrew et al.
BIOLOGICAL CONSERVATION (2012)
Assessing ecosystem threats from global and regional change: hierarchical modeling of risk to sagebrush ecosystems from climate change, land use and invasive species in Nevada, USA
Bethany A. Bradley
ECOGRAPHY (2010)
Random forests for classification in ecology
D. Richard Cutler et al.
ECOLOGY (2007)
Novel methods improve prediction of species' distributions from occurrence data
J Elith et al.
ECOGRAPHY (2006)
Profiting from prior information in Bayesian analyses of ecological data
MA McCarthy et al.
JOURNAL OF APPLIED ECOLOGY (2005)
Confronting multicollinearity in ecological multiple regression
MH Graham
ECOLOGY (2003)