AIMC Topic: Animal Distribution

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Microclimates, land cover, and socioeconomic vulnerability shape Anopheles hotspots in Maryland, USA.

Infectious diseases of poverty
BACKGROUND: Anopheles mosquitoes pose notable public health concerns as competent vectors of malaria and other diseases. Although malaria is no longer endemic in the United States, recent locally acquired cases in states including Maryland highlight ...

eDNA surveys substantially expand known geographic and ecological niche boundaries of marine fishes.

PLoS biology
Assessing species geographic distributions is critical to approximate their ecological niches, understand how global change may reshape their occurrence patterns, and predict their extinction risks. Yet, species records are over-aggregated across tax...

Species distribution modeling to predict tsetse fly (Glossina spp.) habitat suitability in Kenya.

Parasites & vectors
BACKGROUND: African animal trypanosomosis (AAT) and human African trypanosomosis (HAT) are transmitted and spread primarily by tsetse flies (Glossina spp.) in sub-Saharan Africa. The animal disease poses significant challenges to agropastoral systems...

Trait mediation explains decadal distributional shifts for a wide range of insect taxa.

Nature communications
Shifts in insect distributions have been reported globally, largely attributed to climate and landscape changes. Communities are being reshaped, with species response traits mediating the effects of changing environments. Using a machine-learning app...

Fidelity to territory and mate and the causes and consequences of breeding dispersal in American goshawk (Astur atricapillus).

PloS one
Using mark-resight data, we investigated fidelity to territory and mate as well as breeding dispersal rates and the causes and consequences of breeding dispersal in a 20-year study of American goshawks (Astur atricapillus) in Arizona, USA. Generalize...

Understanding and predicting animal movements and distributions in the Anthropocene.

The Journal of animal ecology
Predicting animal movements and spatial distributions is crucial for our comprehension of ecological processes and provides key evidence for conserving and managing populations, species and ecosystems. Notwithstanding considerable progress in movemen...

Habitat Suitability Modelling for the Red Dwarf Honeybee (Apis florea (Linnaeus)) and Its Distribution Prediction Using Machine Learning and Cloud Computing.

Neotropical entomology
Apis florea bees were recently identified in Egypt, marking the second occurrence of this species on the African continent. The objective of this study was to track the distribution of A. florea in Egypt and evaluate its potential for invasive behavi...

Machine learning provides insights for spatially explicit pest management strategies by integrating information on population connectivity and habitat use in a key agricultural pest.

Pest management science
BACKGROUND: Insect pests have garnered increasing interest because of anthropogenic global change, and their sustainable management requires knowledge of population habitat use and spread patterns. To enhance this knowledge for the prevalent tea pest...

Deep learning identification for citizen science surveillance of tiger mosquitoes.

Scientific reports
Global monitoring of disease vectors is undoubtedly becoming an urgent need as the human population rises and becomes increasingly mobile, international commercial exchanges increase, and climate change expands the habitats of many vector species. Tr...

Predicting geographic location from genetic variation with deep neural networks.

eLife
Most organisms are more closely related to nearby than distant members of their species, creating spatial autocorrelations in genetic data. This allows us to predict the location of origin of a genetic sample by comparing it to a set of samples of kn...