Siland a R package for estimating the spatial influence of landscape

Abstract The spatial distributions of populations are both influenced by local variables and by characteristics of surrounding landscapes. Understanding how landscape features spatially structure the frequency of a trait in a population, the abundance of a species or the species’ richness remains di...

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Autores principales:	Florence Carpentier, Olivier Martin
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/e5ca4059836845d8a63e8dec6bedac4a
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spelling	oai:doaj.org-article:e5ca4059836845d8a63e8dec6bedac4a2021-12-02T18:15:42ZSiland a R package for estimating the spatial influence of landscape10.1038/s41598-021-86900-02045-2322https://doaj.org/article/e5ca4059836845d8a63e8dec6bedac4a2021-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-86900-0https://doaj.org/toc/2045-2322Abstract The spatial distributions of populations are both influenced by local variables and by characteristics of surrounding landscapes. Understanding how landscape features spatially structure the frequency of a trait in a population, the abundance of a species or the species’ richness remains difficult specially because the spatial scale effects of the landscape variables are unknown. Various methods have been proposed but their results are not easily comparable. Here, we introduce “siland”, a general method for analyzing the effect of landscape features. Based on a sequential procedure of maximum likelihood estimation, it simultaneously estimates the spatial scales and intensities of landscape variable effects. It does not require any information about the scale of effect. It integrates two landscape effects models: one is based on focal sample site (Bsiland, b for buffer) and one is distance weighted using Spatial Influence Function (Fsiland, f for function). We implemented “siland” in the adaptable and user-friendly R eponym package. It performs landscape analysis on georeferenced point observations (described in a Geographic Information System shapefile format) and allows for effects tests, effects maps and models comparison. We illustrated its use on a real dataset by the study of a crop pest (codling moth densities).Florence CarpentierOlivier MartinNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-6 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Florence Carpentier Olivier Martin Siland a R package for estimating the spatial influence of landscape
description	Abstract The spatial distributions of populations are both influenced by local variables and by characteristics of surrounding landscapes. Understanding how landscape features spatially structure the frequency of a trait in a population, the abundance of a species or the species’ richness remains difficult specially because the spatial scale effects of the landscape variables are unknown. Various methods have been proposed but their results are not easily comparable. Here, we introduce “siland”, a general method for analyzing the effect of landscape features. Based on a sequential procedure of maximum likelihood estimation, it simultaneously estimates the spatial scales and intensities of landscape variable effects. It does not require any information about the scale of effect. It integrates two landscape effects models: one is based on focal sample site (Bsiland, b for buffer) and one is distance weighted using Spatial Influence Function (Fsiland, f for function). We implemented “siland” in the adaptable and user-friendly R eponym package. It performs landscape analysis on georeferenced point observations (described in a Geographic Information System shapefile format) and allows for effects tests, effects maps and models comparison. We illustrated its use on a real dataset by the study of a crop pest (codling moth densities).
format	article
author	Florence Carpentier Olivier Martin
author_facet	Florence Carpentier Olivier Martin
author_sort	Florence Carpentier
title	Siland a R package for estimating the spatial influence of landscape
title_short	Siland a R package for estimating the spatial influence of landscape
title_full	Siland a R package for estimating the spatial influence of landscape
title_fullStr	Siland a R package for estimating the spatial influence of landscape
title_full_unstemmed	Siland a R package for estimating the spatial influence of landscape
title_sort	siland a r package for estimating the spatial influence of landscape
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/e5ca4059836845d8a63e8dec6bedac4a
work_keys_str_mv	AT florencecarpentier silandarpackageforestimatingthespatialinfluenceoflandscape AT oliviermartin silandarpackageforestimatingthespatialinfluenceoflandscape
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Siland a R package for estimating the spatial influence of landscape

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