NicheMapR - an R package for biophysical modelling: the microclimate model

被引:191
|
作者
Kearney, Michael R. [1 ]
Porter, Warren P. [2 ]
机构
[1] Univ Melbourne, Sch BioSci, Parkville, Vic, Australia
[2] Univ Wisconsin, Dept Zool, Madison, WI 53706 USA
基金
澳大利亚研究理事会;
关键词
CLIMATE-CHANGE; BODY-TEMPERATURE; DATA SET; PREDICTION; PHYSIOLOGY; SCALE; DISTRIBUTIONS; ENERGETICS; RESOLUTION; BEHAVIOR;
D O I
10.1111/ecog.02360
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
Microclimatic variables are necessary for a wide range of pure and applied problems in environmental science. In ecology, microclimatic conditions are prerequisites for modelling the heat and water budgets of organisms, from which climatic constraints on behaviour, life histories, distribution and abundance can be inferred. Despite the critical importance of microclimates, there is no general-purpose, accessible microclimate model available for use in ecological studies. Here we introduce and document the microclimate model of the biophysical modelling package NicheMapR, an R package that includes a suite of programs for mechanistic modelling of heat and mass exchange between organisms and their environments. The NicheMapR microclimate model is based on a Fortran program originally developed by Porter, Mitchell, Beckman and McCullough for predicting hourly above- and below-ground conditions from meteorological, terrain, vegetation and soil data. The model includes routines for computing solar radiation, including effects of shading, slope, aspect and horizon angles (hillshade), and can include variable substrate properties with depth. Here we configure the program to be called from R as part of the NicheMapR package, and describe the model in detail including new functionality for modelling soil water balance and snow, optional input of hourly or daily weather input data, and an R implementation of the Global Aerosol Data Set for obtaining local estimates of aerosol profiles as input to the model. We include scripts for core operation of the model, for building a global, monthly long-term average dataset with all necessary environmental inputs, for computing physical properties of air, and for running the model with the global climate database. Example applications are provided in the paper and in the associated vignettes, including customisation the model to run with user-supplied weather inputs.
引用
收藏
页码:664 / 674
页数:11
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