Ecological niche modelling with herbarium data: A framework to improve Natura 2000 habitat monitoring. Amici, V., Geri, F., Bonini, I., & Rocchini, D. Applied Ecology and Environmental Research, 12(3):645 – 659, Corvinus University of Budapest, 2014. Cited by: 10; All Open Access, Bronze Open Access![Ecological niche modelling with herbarium data: A framework to improve Natura 2000 habitat monitoring [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex The effectiveness of biodiversity conservation strategies depends on the knowledge about the distribution of habitats or single species. Despite this, efforts on biodiversity monitoring and conservation are currently hindered by a lack of information about the spatial distribution of species on large landscapes. Predictive species distribution models, can provide a powerful tool for solving this ecological problem. The vast majority of data available for modelling plants distribution are herbarium data, which lack reliable records of species absence. Although it has been found that herbarium records do not meet current standards for sampling in ecological studies, they remain often the only available source of sufficient magnitude with regard to relevant distribution data. Modifying existing statistical tools and developing new methods so that herbarium data, despite their shortcomings, can be used for modelling habitat suitability, is currently a growing field. The aim of this paper was to analyse the opportunities and bottlenecks for future application of distribution models in the mapping and monitoring of habitats of conservation interest in a complex Mediterranean area. Here we specifically concentrate on testing the Maximum entropy (Maxent) approach to estimate the distribution of a training habitat through the use of herbarium records and to explore a GIS-based integrated approach. The results obtained highlighted the important role that distribution models can have in individuating the areas where a targeted species or habitat type is most likely to be found, and in showing where to commit the limited available resources for inventories. © 2014, ALÖKI Kft., Budapest, Hungary.
@ARTICLE{Amici2014645,
author = {Amici, V. and Geri, F. and Bonini, I. and Rocchini, D.},
title = {Ecological niche modelling with herbarium data: A framework to improve Natura 2000 habitat monitoring},
year = {2014},
journal = {Applied Ecology and Environmental Research},
volume = {12},
number = {3},
pages = {645 – 659},
doi = {10.15666/aeer/1203_645659},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84906824725&doi=10.15666%2faeer%2f1203_645659&partnerID=40&md5=75368e38a46a24ad46a8dfc62757cd81},
affiliations = {Department of Environmental Science 'G.Sarfatti', University of Siena, 53100 Siena, Via P.A. Mattioli 4, Italy; Laboratory of Ecology DICAM - Department of Civil, Environmental and Mechanical Engineering, University of Trento, 38123 Trento, Via Mesiano 77, Italy; Herbarium Universitatis Senensis, 53100 Siena, Via P.A. Mattioli, 4, Italy; Department of Biodiversity and Molecular Ecology, Research and Innovation Centre, Fondazione Edmund Mach, 38010 S. Michele all'Adige (TN), Via E Mach 1, Italy},
abstract = {The effectiveness of biodiversity conservation strategies depends on the knowledge about the distribution of habitats or single species. Despite this, efforts on biodiversity monitoring and conservation are currently hindered by a lack of information about the spatial distribution of species on large landscapes. Predictive species distribution models, can provide a powerful tool for solving this ecological problem. The vast majority of data available for modelling plants distribution are herbarium data, which lack reliable records of species absence. Although it has been found that herbarium records do not meet current standards for sampling in ecological studies, they remain often the only available source of sufficient magnitude with regard to relevant distribution data. Modifying existing statistical tools and developing new methods so that herbarium data, despite their shortcomings, can be used for modelling habitat suitability, is currently a growing field. The aim of this paper was to analyse the opportunities and bottlenecks for future application of distribution models in the mapping and monitoring of habitats of conservation interest in a complex Mediterranean area. Here we specifically concentrate on testing the Maximum entropy (Maxent) approach to estimate the distribution of a training habitat through the use of herbarium records and to explore a GIS-based integrated approach. The results obtained highlighted the important role that distribution models can have in individuating the areas where a targeted species or habitat type is most likely to be found, and in showing where to commit the limited available resources for inventories. © 2014, ALÖKI Kft., Budapest, Hungary.},
author_keywords = {Ecological niche; GIS; Habitat distribution; Herbarium data; Maxent},
correspondence_address = {V. Amici; Department of Environmental Science 'G.Sarfatti', University of Siena, 53100 Siena, Via P.A. Mattioli 4, Italy; email: valerio.amici@gmail.com},
publisher = {Corvinus University of Budapest},
issn = {15891623},
language = {English},
abbrev_source_title = {Appl. Ecol. Environ. Res.},
type = {Article},
publication_stage = {Final},
source = {Scopus},
note = {Cited by: 10; All Open Access, Bronze Open Access}
}
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