ArticleEcology and evolution2024
A Novel Web-Based Approach for Monitoring Biodiversity.
Article in Ecology and evolution, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Understanding complexities in biodiversity is one of the fundamental goals of ecology and its monitoring is significant for ecosystem sustainability, maintenance, and conservation. However, biodiversity monitoring needs improvement to handle complex datasets and their analyses. This study attempts to understand these ecological complexities quickly, efficiently, and easily. The aim is to provide an alternative to ecologists, researchers, instructors, and stakeholders for biodiversity monitoring with the flexibility to visualize and customize outputs without software knowledge. A novel web-based technique is applied to monitor the biodiversity of a complex mountain ecosystem using a national database. The species-environment relationships of different vegetation types across a mountain ecosystem's elevation gradient are investigated using open-source climatic, physiographic, and socioeconomic variables. The proposed interactive tool to monitor biodiversity and understand its complexities is designed to visualize the data structure, summary, correlations, and sampling effectiveness quickly and easily. Plant species richness patterns and life forms (herb, shrub, and tree) across elevational gradients are investigated. We highlight the preliminary investigation of the data structure and their spatial distribution and apply the multicollinearity test to select variables for modeling. The drop-down menu helps users browse different datasets and select those datasets for instant visualization. Preliminary investigations on interactions between variables and species richness of vegetation types along elevation gradient interactively displayed with options to select variables, plant richness, and an elevational range. Species-environment relationships are investigated using multiple modeling protocols, and results are interactively displayed with options to download in different file formats and colors at the click of a button. This visualization tool helps to understand ecosystem structure, species richness patterns and species-environment relationships easily and efficiently. The R-codes used in this tool are reproducible and can be implemented with multiple datasets to monitor ecosystems.
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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.