Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
versions View all 3 versions
addClaim

The Prairie State: Using Ecological Niche Modeling to Predict Distributions of Early Land Plants

Authors: Ryan, Zoe; von Konrat, Matt;

The Prairie State: Using Ecological Niche Modeling to Predict Distributions of Early Land Plants

Abstract

Bryophytes are environmentally and ecologically significant biological indicators, as their distribution is largely determined by the climate and the land features that shape these factors. Yet it is a challenge to track the ranges of these plants and even more so to predict their future distribution patterns due to their small size and sensitivity to environmental change. This study aims to model the potential distribution of selected bryophyte species in Illinois to investigate the potential impact of global warming and determine what environmental factors affect distribution patterns. Bryophyte occurrences post 1970 of some of the most common epiphytic species and genera were investigated. Over 12,000 georeferenced occurrence records were downloaded from a public biodiversity aggregator, cleaned, and validated. The environmental variables consisted of the WorldClim Bioclim variables and National Land Cover Database land use variables, filtered to remove correlation. The occurrences and environmental variables were run through a MaxEnt model in R to generate heat maps of potential distribution. Statistical evaluation metrics and validation techniques were used to test model accuracy. Overall, current species models showed a higher level of confidence than the genera models, and all models were primarily reliant on the land use variables over the climate variables. Future models only showed minor distribution changes across climate scenarios, suggesting the use of more local indicators and further research on microclimate data. Attempting to quantify bryophyte-environment relationships and ecological niche modeling potentially provides a means of predicting how bryophytes might respond to environmental changes over time. Using such techniques enables us to test for significant differences in the characterization of niches between taxa. Successful models will not only show support for utilizing bryophytes as climate change indicators, but also for this open-source methodology in the niche modeling for other organisms. Overall, these results will possibly have important implications for species distribution patterns, conservation, land management and our understanding of ecological niche modeling using a poorly studied and overlooked group of plants.

This data includes raw data of over 12,000 occurrences were downloaded from the Consortium of Bryophyte Herbaria (www.bryophyteportal.org/portal), that were listed to be in Illinois and included longitude and latitude data. This data set was screened and cleaned to investigate species distribution models as well as generate models of selected bryophytes investigating future changes in distribution across climate change scenarios.

Related Organizations
Keywords

Ecological niche modelling, BIOCLIM, Predictive mapping, Bryophytes, MaxEnt

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
    OpenAIRE UsageCounts
    Usage byUsageCounts
    visibility views 8
    download downloads 9
  • 8
    views
    9
    downloads
    Powered byOpenAIRE UsageCounts
Powered by OpenAIRE graph
Found an issue? Give us feedback
visibility
download
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
0
Average
Average
Average
8
9
Related to Research communities
Italian National Biodiversity Future Center