AIMC Topic: Ecology

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Machine learning with the hierarchy-of-hypotheses (HoH) approach discovers novel pattern in studies on biological invasions.

Research synthesis methods Aug 5, 2019
Research synthesis on simple yet general hypotheses and ideas is challenging in scientific disciplines studying highly context-dependent systems such as medical, social, and biological sciences. This study shows that machine learning, equation-free s...
Biology Ecology Asia Decision Trees Data Interpretation, Statistical Algorithms Review Literature as Topic Research Design Reproducibility of Results Animals Geography Ecosystem Models, Statistical Introduced Species Artificial Intelligence Machine Learning
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Insights and approaches using deep learning to classify wildlife.

Scientific reports May 31, 2019
The implementation of intelligent software to identify and classify objects and individuals in visual fields is a technology of growing importance to operatives in many fields, including wildlife conservation and management. To non-experts, the metho...
Africa Deep Learning Image Processing, Computer-Assisted Reproducibility of Results Animals Animals, Wild Pattern Recognition, Automated Species Specificity Computer Graphics Cluster Analysis Biodiversity Ecology Neural Networks, Computer Software Algorithms
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Uncovering Ecological Patterns with Convolutional Neural Networks.

Trends in ecology & evolution May 8, 2019
Using remotely sensed imagery to identify biophysical components across landscapes is an important avenue of investigation for ecologists studying ecosystem dynamics. With high-resolution remotely sensed imagery, algorithmic utilization of image cont...
Neural Networks, Computer Ecology Ecosystem Image Processing, Computer-Assisted
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Environmental metabolomics with data science for investigating ecosystem homeostasis.

Progress in nuclear magnetic resonance spectroscopy Nov 21, 2017
A natural ecosystem can be viewed as the interconnections between complex metabolic reactions and environments. Humans, a part of these ecosystems, and their activities strongly affect the environments. To account for human effects within ecosystems,...
Ecology Humans Biota Multivariate Analysis Animals Machine Learning Nuclear Magnetic Resonance, Biomolecular Homeostasis Ecosystem Databases, Factual Metabolomics
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Predicting the Ecological Quality Status of Marine Environments from eDNA Metabarcoding Data Using Supervised Machine Learning.

Environmental science & technology Jul 25, 2017
Monitoring biodiversity is essential to assess the impacts of increasing anthropogenic activities in marine environments. Traditionally, marine biomonitoring involves the sorting and morphological identification of benthic macro-invertebrates, which ...
Ecology DNA Barcoding, Taxonomic Foraminifera Environmental Monitoring Supervised Machine Learning Biodiversity
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Next-Generation Global Biomonitoring: Large-scale, Automated Reconstruction of Ecological Networks.

Trends in ecology & evolution Mar 27, 2017
We foresee a new global-scale, ecological approach to biomonitoring emerging within the next decade that can detect ecosystem change accurately, cheaply, and generically. Next-generation sequencing of DNA sampled from the Earth's environments would p...
Biodiversity High-Throughput Nucleotide Sequencing Ecology Machine Learning Ecosystem Environmental Monitoring Sequence Analysis, DNA DNA
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Simulated herbivory does not constrain phenotypic plasticity to shade through ontogeny in a relict tree.

Plant biology (Stuttgart, Germany) Apr 7, 2016
Ecological limits to phenotypic plasticity (PP), induced by simultaneous biotic and abiotic factors, can prevent organisms from exhibiting optimal plasticity, and in turn lead to decreased fitness. Herbivory is an important biotic stressor and may li...
Phenotype Plant Leaves Seedlings Plant Roots Models, Biological Herbivory Biological Ontologies Light Stress, Physiological Trees Plant Shoots Ecology
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Typha latifolia (broadleaf cattail) as bioindicator of different types of pollution in aquatic ecosystems-application of self-organizing feature map (neural network).

Environmental science and pollution research international Apr 5, 2016
The contents of Cd, Cu, Fe, Mn, Ni, Pb, and Zn in leaves of Typha latifolia (broadleaf cattail), water and bottom sediment from 72 study sites designated in different regions of Poland were determined using atomic absorption spectrometry. The aim of ...
Typhaceae Ecology Metals, Heavy Geologic Sediments Water Pollutants, Chemical Plant Leaves Environmental Pollution Metals Neural Networks, Computer Agriculture Environmental Monitoring Ecosystem Poland Trace Elements
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Modeling of Beta Diversity in Tunisian Waters: Predictions Using Generalized Dissimilarity Modeling and Bioregionalisation Using Fuzzy Clustering.

PloS one Jul 6, 2015
Spatial patterns of beta diversity are a major focus of ecology. They can be especially valuable in conservation planning. In this study, we used a generalized dissimilarity modeling approach to analyze and predict the spatial patterns of beta divers...
Tunisia Models, Theoretical Mediterranean Sea Fuzzy Logic Biodiversity Ecology
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Process-Informed Neural Networks: A Hybrid Modelling Approach to Improve Predictive Performance and Inference of Neural Networks in Ecology and Beyond.

Ecology letters Nov 1, 2024
Despite deep learning being state of the art for data-driven model predictions, its application in ecology is currently subject to two important constraints: (i) deep-learning methods are powerful in data-rich regimes, but in ecology data are typical...
Deep Learning Models, Biological Forests Ecology Neural Networks, Computer
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