ArticlePeerJ2025
EcoNicheS: enhancing ecological niche modeling, niche overlap and connectivity analysis using the shiny dashboard and R package.
Article in PeerJ, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
EcoNicheS (https://github.com/armandosunny/EcoNicheS) is a comprehensive R package built on a Shiny dashboard that offers an intuitive and streamlined workflow for creating ecological niche models (ENMs) and landscape connectivity models. It incorporates tools for niche modeling, overlap analysis, and connectivity modeling, leveraging robust algorithms from the biomod2 suite. EcoNicheS is designed to simplify the technical complexities of ENMs, bridging the gap between advanced modeling techniques and user accessibility. The package offers an interactive interface for streamlined data input, model parameterization, and result visualization. Its comprehensive toolset includes occurrence data processing, pseudoabsence point generation, urbanization filters, and ecological connectivity modeling, distinguishing it from other platforms. EcoNicheS integrates innovative workflows with dynamic output visualizations while emphasizing reproducibility and comparability across statistical methods. Its practical applications span diverse research fields, including biogeography, epidemiology, evolutionary studies, climate change impacts, landscape connectivity, and biodiversity conservation. This versatility makes EcoNicheS a valuable resource for advancing in ecological and conservation science.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.