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

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. This article is protected by copyright. All rights reserved.

[1]  Ary A. Hoffmann,et al.  Microclimate modelling at macro scales: a test of a general microclimate model integrated with gridded continental‐scale soil and weather data , 2014 .

[2]  P. Jones,et al.  Representing Twentieth-Century Space–Time Climate Variability. Part I: Development of a 1961–90 Mean Monthly Terrestrial Climatology , 1999 .

[3]  M. Kearney,et al.  Unpacking the mechanisms captured by a correlative species distribution model to improve predictions of climate refugia , 2016, Global change biology.

[4]  Ramakrishna R. Nemani,et al.  MTCLIM: a mountain microclimate simulation model , 1989 .

[5]  Brendan A. Wintle,et al.  Correlative and mechanistic models of species distribution provide congruent forecasts under climate change , 2010 .

[6]  M. Jackson,et al.  Effects of Microclimate on Spring Flowering Phenology , 1966 .

[7]  J. Elith,et al.  Species Distribution Models: Ecological Explanation and Prediction Across Space and Time , 2009 .

[8]  R. J. Russell,et al.  Insects and climate , 1931 .

[9]  S. Pincebourde,et al.  Microclimatic challenges in global change biology , 2013, Global change biology.

[10]  Michael Kearney,et al.  The potential for behavioral thermoregulation to buffer “cold-blooded” animals against climate warming , 2009, Proceedings of the National Academy of Sciences.

[11]  Huug van den Dool,et al.  Performance and analysis of the constructed analogue method applied to U.S. soil moisture over 1981-2001 , 2003 .

[12]  M. Kearney.  Metabolic theory, life history and the distribution of a terrestrial ectotherm , 2012 .

[13]  Murugesu Sivapalan,et al.  Linking Eco-Energetics and Eco-Hydrology to Select Sites for the Assisted Colonization of Australia’s Rarest Reptile , 2012, Biology.

[14]  B. Huntley,et al.  Habitat microclimates drive fine‐scale variation in extreme temperatures , 2011 .

[15]  M. Kearney,et al.  Modelling species distributions without using species distributions: the cane toad in Australia under current and future climates , 2008 .

[16]  W. Dowd,et al.  Biophysics, environmental stochasticity, and the evolution of thermal safety margins in intertidal limpets , 2012, Journal of Experimental Biology.

[17]  J. Duffy,et al.  Fine‐scale climate change: modelling spatial variation in biologically meaningful rates of warming , 2017, Global Change Biology.

[18]  M. Hill,et al.  Slope, aspect and climate: Spatially explicit and implicit models of topographic microclimate in chalk grassland , 2008 .

[19]  W. Porter,et al.  Behavior-Microclimate Relationships in the African Rainbow Lizard, Agama agama , 1979 .

[20]  Michael R Kearney,et al.  Predicting the fate of a living fossil: how will global warming affect sex determination and hatching phenology in tuatara? , 2008, Proceedings of the Royal Society B: Biological Sciences.

[21]  Robert J. Wilson,et al.  Seeing the woods for the trees – when is microclimate important in species distribution models? , 2014, Global change biology.

[22]  W. Beckman,et al.  Behavioral implications of mechanistic ecology , 1973, Oecologia.

[23]  O. Reichman,et al.  Physiology on a Landscape Scale: Plant-Animal Interactions1 , 2002, Integrative and comparative biology.

[24]  W. Porter,et al.  Model of Japanese serow (Capricornis crispus) energetics predicts distribution on Honshu, Japan. , 2007, Ecological applications : a publication of the Ecological Society of America.

[25]  J. Monteith.  Micrometeorology in relation to plant and animal life. , 1960 .

[26]  C. Harley,et al.  Thermal stress on intertidal limpets: long-term hindcasts and lethal limits , 2006, Journal of Experimental Biology.

[27]  B. Helmuth.  How do we Measure the Environment? Linking Intertidal Thermal Physiology and Ecology Through Biophysics1 , 2002, Integrative and comparative biology.

[28]  D. Wethey,et al.  Variation in the sensitivity of organismal body temperature to climate change over local and geographic scales. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[29]  W. Porter,et al.  Using a microclimate model to evaluate impacts of climate change on sea turtles , 2013 .

[30]  W. Porter,et al.  Modeling amphibian energetics, habitat suitability, and movements of western toads, Anaxyrus (=Bufo) boreas, across present and future landscapes , 2010 .

[31]  W. Porter,et al.  Po'ouli landscape bioinformatics models predict energetics, behavior, diets, and distribution on Maui. , 2006, Integrative and comparative biology.

[32]  M. Kearney,et al.  Activity restriction and the mechanistic basis for extinctions under climate warming. , 2013, Ecology letters.

[33]  Huug van den Dool,et al.  Climate Prediction Center global monthly soil moisture data set at 0.5 resolution for 1948 to present , 2004 .

[34]  John Mitchell,et al.  Thermal Model for Prediction of a Desert Iguana’s Daily and Seasonal Behavior , 1973 .

[35]  P. Willmer.  Microclimate and the Environmental Physiology of Insects , 1982 .

[36]  M. Moritz,et al.  Fine-grain modeling of species' response to climate change: holdouts, stepping-stones, and microrefugia. , 2014, Trends in ecology & evolution.

[37]  M. Kearney,et al.  Biomechanics meets the ecological niche: the importance of temporal data resolution , 2012, Journal of Experimental Biology.

[38]  Jérôme Casas,et al.  Regional climate modulates the canopy mosaic of favourable and risky microclimates for insects. , 2007, The Journal of animal ecology.

[39]  M. Kearney,et al.  microclim: Global estimates of hourly microclimate based on long-term monthly climate averages , 2014, Scientific Data.

[40]  B. Helmuth.  INTERTIDAL MUSSEL MICROCLIMATES: PREDICTING THE BODY TEMPERATURE OF A SESSILE INVERTEBRATE , 1998 .

[41]  M. Kearney,et al.  Balancing heat, water and nutrients under environmental change: a thermodynamic niche framework , 2013 .

[42]  E. McCullough,et al.  Computing Clear Day Solar Radiation Spectra for the Terrestrial Ecological Environment , 1971 .

[43]  M. Hulme,et al.  A high-resolution data set of surface climate over global land areas , 2002 .

[44]  John R. Gollan,et al.  Fine‐resolution (25 m) topoclimatic grids of near‐surface (5 cm) extreme temperatures and humidities across various habitats in a large (200 × 300 km) and diverse region , 2011 .

[45]  W. Porter,et al.  Simulating Polar Bear Energetics during a Seasonal Fast Using a Mechanistic Model , 2013, PloS one.

[46]  P. Galli,et al.  Catastrophic 1638 earthquakes in Calabria (southern Italy): New insights from paleoseismological investigation , 2003 .

[47]  B. Huntley,et al.  The relative importance of climate and habitat in determining the distributions of species at different spatial scales: a case study with ground beetles in Great Britain , 2012 .