000121439 001__ 121439
000121439 005__ 20240319081024.0
000121439 0247_ $$2doi$$a10.1016/j.ecoinf.2022.101810
000121439 0248_ $$2sideral$$a132035
000121439 037__ $$aART-2022-132035
000121439 041__ $$aeng
000121439 100__ $$0(orcid)0000-0001-7663-1202$$aSerrano-Notivoli, Roberto
000121439 245__ $$abioclim: An R package for bioclimatic classifications via adaptive water balance
000121439 260__ $$c2022
000121439 5060_ $$aAccess copy available to the general public$$fUnrestricted
000121439 5203_ $$abioclim is a software package in R language for bioclimatic classification based on the Type of Bioclimatic Regime approach, which combines climatic and soil properties to classify a region according to its suitability for plant vegetative activity. We present the software's operating modes, capabilities and limitations, including real-world usage examples. Using monthly temperature, precipitation, and field capacity as inputs, bioclim follows a straightforward workflow using three functions to compute: i) a comprehensive water balance describing water resource dynamics throughout the year; ii) a bioclimatic balance to estimate plant vegetative activity; and iii) a collection of bioclimatic intensities quantifying vegetative activity changes. The program uses the results of these functions to classify bioclimatic type at zonal, regional and local scales. The three functions' outputs can be calculated independently, strengthening the software's cross-disciplinary application potential, such as climatology and hydrology. bioclim uses numeric and raster formats as input data and contains highly flexible options for a wide range of purposes, from scientific research to end users' representations. The water and bioclimatic balance results can be presented in numerical, graphical, or cartographic forms.
000121439 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000121439 590__ $$a5.1$$b2022
000121439 592__ $$a0.915$$b2022
000121439 591__ $$aECOLOGY$$b27 / 171 = 0.158$$c2022$$dQ1$$eT1
000121439 593__ $$aApplied Mathematics$$c2022$$dQ1
000121439 593__ $$aComputational Theory and Mathematics$$c2022$$dQ1
000121439 593__ $$aEcological Modeling$$c2022$$dQ1
000121439 593__ $$aModeling and Simulation$$c2022$$dQ1
000121439 593__ $$aEcology$$c2022$$dQ1
000121439 593__ $$aEcology, Evolution, Behavior and Systematics$$c2022$$dQ1
000121439 593__ $$aComputer Science Applications$$c2022$$dQ2
000121439 594__ $$a6.1$$b2022
000121439 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000121439 700__ $$0(orcid)0000-0002-9558-1308$$aLongares, Luis Alberto$$uUniversidad de Zaragoza
000121439 700__ $$aCámara, Rafael
000121439 7102_ $$13006$$2430$$aUniversidad de Zaragoza$$bDpto. Geograf. Ordenac.Territ.$$cÁrea Geografía Física
000121439 773__ $$g71 (2022), 101810 [10 pp.]$$pEcological Informatics$$tEcological Informatics$$x1574-9541
000121439 8564_ $$s3404529$$uhttps://zaguan.unizar.es/record/121439/files/texto_completo.pdf$$yVersión publicada
000121439 8564_ $$s2625069$$uhttps://zaguan.unizar.es/record/121439/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000121439 909CO $$ooai:zaguan.unizar.es:121439$$particulos$$pdriver
000121439 951__ $$a2024-03-18-16:29:06
000121439 980__ $$aARTICLE