AIMC Topic: Ecosystem

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The latitudinal gradient in rock-inhabiting bacterial community compositions in Victoria Land, Antarctica.

The Science of the total environment
The harsh conditions in Victoria Land, Antarctica have formed a simple ecosystem dominated by microbes that use rocks as shelters to avoid environmental stressors. The area is composed of basement rocks that illustrate the history of complex deformat...

A Dexterous, Glove-Based Teleoperable Low-Power Soft Robotic Arm for Delicate Deep-Sea Biological Exploration.

Scientific reports
Modern marine biologists seeking to study or interact with deep-sea organisms are confronted with few options beyond industrial robotic arms, claws, and suction samplers. This limits biological interactions to a subset of "rugged" and mostly immotile...

Variable importance for sustaining macrophyte presence via random forests: data imputation and model settings.

Scientific reports
Data sets plagued with missing data and performance-affecting model parameters represent recurrent issues within the field of data mining. Via random forests, the influence of data reduction, outlier and correlated variable removal and missing data i...

Machine learning approaches in GIS-based ecological modeling of the sand fly Phlebotomus papatasi, a vector of zoonotic cutaneous leishmaniasis in Golestan province, Iran.

Acta tropica
The distribution and abundance of Phlebotomus papatasi, the primary vector of zoonotic cutaneous leishmaniasis in most semi-/arid countries, is a major public health challenge. This study compares several approaches to model the spatial distribution ...

Hyperspectral Data and Machine Learning for Estimating CDOM, Chlorophyll , Diatoms, Green Algae and Turbidity.

International journal of environmental research and public health
Inland waters are of great importance for scientists as well as authorities since they are essential ecosystems and well known for their biodiversity. When monitoring their respective water quality, in situ measurements of water quality parameters ar...

Predictive pollen-based biome modeling using machine learning.

PloS one
This paper investigates suitability of supervised machine learning classification methods for classification of biomes using pollen datasets. We assign modern pollen samples from Africa and Arabia to five biome classes using a previously published Af...

Artificial neural networks: Modeling tree survival and mortality in the Atlantic Forest biome in Brazil.

The Science of the total environment
Models to predict tree survival and mortality can help to understand vegetation dynamics and to predict effects of climate change on native forests. The objective of the present study was to use Artificial Neural Networks, based on the competition in...

Robotic bees for crop pollination: Why drones cannot replace biodiversity.

The Science of the total environment
The notion that robotic crop pollination will solve the decline in pollinators has gained wide popularity recently (Fig. 1), and in March 2018 Walmart filed a patent for autonomous robot bees. However, w present six arguments showing that this is a t...

In vitro colonic fermentation of Mexican "taco" from corn-tortilla and black beans in a Simulator of Human Microbial Ecosystem (SHIME®) system.

Food research international (Ottawa, Ont.)
A Mexican staple food prepared with corn "tortilla" (Zea mays L.) and common beans (Phaseolus vulgaris L.) is named as "taco". It was fermented in an in vitro colonic Simulator of Human Microbial Ecosystem (SHIME®) to evaluate the effect in short cha...

Quantifying cell densities and biovolumes of phytoplankton communities and functional groups using scanning flow cytometry, machine learning and unsupervised clustering.

PloS one
Scanning flow cytometry (SFCM) is characterized by the measurement of time-resolved pulses of fluorescence and scattering, enabling the high-throughput quantification of phytoplankton morphology and pigmentation. Quantifying variation at the single c...