000048142 001__ 48142
000048142 005__ 20190529115152.0
000048142 0247_ $$2doi$$a10.1186/1756-3305-7-302
000048142 0248_ $$2sideral$$a86617
000048142 037__ $$aART-2014-86617
000048142 041__ $$aeng
000048142 100__ $$0(orcid)0000-0001-7483-046X$$aEstrada-Peña, A.$$uUniversidad de Zaragoza
000048142 245__ $$aA global set of Fourier-transformed remotely sensed covariates for the description of abiotic niche in epidemiological studies of tick vector species
000048142 260__ $$c2014
000048142 5060_ $$aAccess copy available to the general public$$fUnrestricted
000048142 5203_ $$aBackground: Correlative modelling combines observations of species occurrence with environmental variables to capture the niche of organisms. It has been argued for the use of predictors that are ecologically relevant to the target species, instead of the automatic selection of variables. Without such biological background, the forced inclusion of numerous variables can produce models that are highly inflated and biologically irrelevant. The tendency in correlative modelling is to use environmental variables that are interpolated from climate stations,
or monthly estimates of remotely sensed features.
Methods: We produced a global dataset of abiotic variables based on the transformation by harmonic regression (time series Fourier transform) of monthly data derived from the MODIS series of satellites at a nominal resolution of 0.1°. The dataset includes variables, such as day and night temperature or vegetation and water availability, which potentially could affect physiological processes and therefore are surrogates in tracking the abiotic niche. We tested the capacities of the dataset to describe the abiotic niche of parasitic organisms, applying it to discriminate five species of the globally distributed tick subgenus Boophilus and using more than 9,500 published records.
Results: With an average reliability of 82%, the Fourier-transformed dataset outperformed the raw MODIS-derived monthly data for temperature and vegetation stress (62% of reliability) and other popular interpolated climate datasets, which had variable reliability (56%–65%). The transformed abiotic variables always had a collinearity of less than 3
(as measured by the variance inflation factor), in contrast with interpolated datasets, which had values as high as 300.
Conclusions: The new dataset of transformed covariates could address the tracking of abiotic niches without inflation of the models arising from internal issues with the descriptive variables, which appear when variance inflation is higher than 10. The coefficients of the harmonic regressions can also be used to reconstruct the complete original time series, being an adequate complement for ecological, epidemiological, or phylogenetic studies. We provide the dataset as a free download under the GNU general public license as well as the scripts necessary to integrate other time series of data into the calculations of the harmonic coefficients.
000048142 536__ $$9info:eu-repo/grantAgreement/EC/FP7/278976/EU/ANTIcipating the Global Onset of Novel Epidemics/ANTIGONE
000048142 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000048142 590__ $$a3.43$$b2014
000048142 591__ $$aPARASITOLOGY$$b7 / 36 = 0.194$$c2014$$dQ1$$eT1
000048142 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000048142 700__ $$aEstrada-Sánchez, A.
000048142 700__ $$aFuente, J.de la
000048142 7102_ $$11009$$2773$$aUniversidad de Zaragoza$$bDpto. Patología Animal$$cÁrea Sanidad Animal
000048142 773__ $$g7, 302 (2014), [14 pp.]$$pParasites & Vectors$$tParasites and Vectors$$x1756-3305
000048142 8564_ $$s738967$$uhttps://zaguan.unizar.es/record/48142/files/texto_completo.pdf$$yVersión publicada
000048142 8564_ $$s82433$$uhttps://zaguan.unizar.es/record/48142/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000048142 909CO $$ooai:zaguan.unizar.es:48142$$particulos$$pdriver
000048142 951__ $$a2019-05-29-11:34:18
000048142 980__ $$aARTICLE