Can next-generation soil data products improve soil moisture modelling at the continental scale? An assessment using a new microclimate package for the R programming environment

Kearney, Michael R.; Maino, James L.

doi:10.1016/j.jhydrol.2018.04.040

Cited by 35 publications

(59 citation statements)

References 41 publications

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“…This model has been extensively tested for its ability to predict both soil temperature (Kearney et al . ) and soil moisture (Kearney & Maino ) across Australia, with accuracy to within 10% of measurement values. A data set of microclimatic output from this model would thus be valuable for a wide range of pure and applied problems in ecology, conservation, agriculture, health and pest management in the Australian context.…”

Section: Introductionmentioning

confidence: 81%

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MicroclimOz – A microclimate data set for Australia, with example applications

Kearney

2018

Austral Ecology

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Many problems in pure and applied ecology require the quantification of above-and below-ground microclimates. Here I describe a data set of hourly microclimates for the Australian continent, simulated from the years 1990 to 2017 across a grid of 1893 locations approx. 60 km apart. The data were generated with the NicheMapR microclimate model, driven by 0.05°gridded daily meteorological forcing data (air temperature, wind speed, humidity, cloud cover, rainfall), 0.025°elevation and 0.008°soil texture data. The above-ground microclimate variables include horizontal plane solar radiation, solar zenith angle, sky temperature (from which down-welling longwave radiation can be computed), air temperature, relative humidity and wind speed at 1 and 120 cm height, and snow depth. The below-ground variables include soil temperature, pore humidity, soil moisture and soil water potential for 0, 2.5, 5, 10, 15, 20, 30, 50, 100 and 200 cm below-ground. The computations are for four shade levels (0%, 50%, 70% and 90%). The data set can be used for a wide variety of applications, including the computation of heat and water budgets of organisms, the potential for vegetation growth, and the computation of stress and growth indices. The use of daily forcing data also allows assessments of the consequences of extreme events including heat waves. Example applications are provided for computing plant growth potential, grasshopper egg development, lizard body temperature and mammalian energy and water requirements.

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Section: Introductionmentioning

confidence: 81%

“…To generate the microclimOz data set, the model was run as described in Kearney and Maino (), from the years 1990 to 2017 inclusive across a grid of 1836 locations approximately 60 km apart. At each site, daily forcing data from the Australian Water Availability Project (AWAP; Jones et al .…”

Section: Methodsmentioning

confidence: 99%

MicroclimOz – A microclimate data set for Australia, with example applications

Kearney

2018

Austral Ecology

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“…8 The code specific to this analysis can also be found online. 9 The microclimate model, when applied in Australia using interpolated daily weather data (air temperature, rainfall, wind speed, vapor pressure, and solar radiation) and a continent-wide soil database as input, can predict hourly soil temperatures within 10% of observed values across a wide range of environments Maino 2018). We implemented the model as reported in Kearney et al (2014) with two additions.…”

Section: Biophysical Modelingmentioning

confidence: 99%

“…First, we integrated a daily gridded mean wind speed product (McVicar et al 2008), assuming maximum wind speed was double, and minimum wind speed was half, the mean value used long-term monthly mean values). Second, we incorporated a soil moisture model (Campbell 1985, Kearney andMaino 2018), primarily to model the dynamics of the sleepy lizard food plants and burrow humidity (see Dynamic energy budget model and Modeling food and its water content). We ran the microclimate model for the geographical coordinates of the Bundey Bore study site for each day of the years 1991-2010.…”

Section: Biophysical Modelingmentioning

confidence: 99%

“…However, burrow humidity will depend on the depth and distance from the burrow entrance as well as the degree of ventilation of the burrow (Shimmin et al 2002). The NicheMapR microclimate model computes site-specific soil humidity given soil moisture predictions Porter 2017, Kearney andMaino 2018). To estimate burrow humidity, we computed a weighted mean of ambient (1 cm above ground) and soil vapor pressure whereby the fractional weighting to soil vapor pressure increased linearly with soil depth from 0 to 0.9, in 0.1 increments.…”

Section: Simulating Burrow Environmentsmentioning

confidence: 99%

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Field tests of a general ectotherm niche model show how water can limit lizard activity and distribution

Kearney

Munns

Moore

et al. 2018

Ecological Monographs

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Mechanistic forecasts of how species will respond to climate change are highly desired but difficult to achieve. Because processes at different scales are explicit in such models, careful assessments of their predictive abilities can provide valuable insights that will be relevant to functionally similar species. However, there are surprisingly few comprehensive field tests of mechanistic niche models in the literature. We applied a general, thermodynamically grounded modeling framework to determine the fundamental niche of an extremely well‐studied herbivorous ectotherm, the sleepy lizard Tiliqua rugosa. We then compared the model predictions with detailed long‐term field observations that included sub‐hourly data on microclimate, activity levels, home ranges, and body temperatures as well as annual to decadal patterns of body condition and growth. Body temperature predictions inferred from gridded climatic data were within 10% of empirically observed values and explained >70% of observed daytime activity patterns across all lizards. However, some periods of activity restriction were explained by predicted desiccation level rather than by temperature, and metabolically driven activity requirements were much lower than potential activity time. Decadal trajectories of field growth and body condition could also be explained to within 10% of observed values, with the variance in trajectories being attributable to whether individuals had access to permanent water. Continent‐wide applications of the model partly captured the inland distribution limit, but only after accounting for water limitations. Predicted changes in habitat suitability under six climate change scenarios were generally positive within the species’ current range, but varied strongly with predicted rainfall. Temperature is regarded as the major factor that will restrict the distribution and abundance of lizards and other terrestrial ectotherms under climate change. Yet our findings show how water can be more important than temperature in constraining the activity, habitat requirements, and distribution limits of terrestrial ectotherms. Our results demonstrate the feasibility of first‐principles computation of the climatic limits on terrestrial animals from gridded environmental data, providing a coherent picture for how species will respond to climate change at different scales of space and time.

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Modeling the distribution of niche space and risk for a freeze‐tolerant ectotherm, Lithobates sylvaticus

et al. 2019

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Many animals depend on stable below‐the‐snow (subnivium) conditions to survive winter in seasonally cold regions. Freeze‐tolerant ectotherms may experience increased ice content and/or energy expenditure in suboptimal subnivium conditions, with implications for overwinter survival and body reserves available for spring reproduction. We used a novel mechanistic modeling approach to explore effects of winter climate on the microclimate conditions, energy expenditure, and ice dynamics of the freeze‐tolerant, subnivium‐dwelling wood frog (Lithobates sylvaticus) in the Upper Midwest and Great Lakes Basin region of the United States. We hypothesized that (1) frogs would experience the greatest energy cost to survive winter in southern regions of our study area, where air temperatures are warmer and shallower snow could allow for increased numbers of freeze–thaw cycles, and (2) frogs would be most vulnerable to lethal freezing in the cold, dry northwest portion of our study region. We found that total winter energy expenditure changed little with latitude because the effect of warmer soil temperatures (higher metabolic rates) to the south was offset by a shorter winter duration. Energy expenditures were greatest in the snowbelts of the Great Lakes, characterized by more persistent snow cover and relatively warm soil temperatures. In contrast, highest ice contents occurred in the northwest of the study region where air temperatures were coldest and snow was shallow. Thus, it appears that wood frogs experience a trade‐off between risk of lethal ice content and extensive use of body reserves across geographic space. Simulations showed that interpopulation differences in burrow depth and cryoprotectant concentration can influence risk of lethal ice content and overuse of body reserves prior to spring breeding, and those risks vary in relation to winter climate. Our mechanistic modeling approach is a novel tool for predicting risk and shifting niche space for cold‐adapted and subnivium‐dependent species.

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Can next-generation soil data products improve soil moisture modelling at the continental scale? An assessment using a new microclimate package for the R programming environment

Cited by 35 publications

References 41 publications

MicroclimOz – A microclimate data set for Australia, with example applications

MicroclimOz – A microclimate data set for Australia, with example applications

Field tests of a general ectotherm niche model show how water can limit lizard activity and distribution

Modeling the distribution of niche space and risk for a freeze‐tolerant ectotherm, Lithobates sylvaticus

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