scholarly journals Can we predict ectotherm responses to climate change using thermal performance curves and body temperatures?

2016 ◽  
Vol 19 (11) ◽  
pp. 1372-1385 ◽  
Author(s):  
Brent J. Sinclair ◽  
Katie E. Marshall ◽  
Mary A. Sewell ◽  
Danielle L. Levesque ◽  
Christopher S. Willett ◽  
...  
Keyword(s):  
Climate Change ◽  
Thermal Performance ◽  
Body Temperatures ◽  
Performance Curves

scholarly journals Use and misuse of temperature normalisation in meta-analyses of thermal responses of biological traits

2017 ◽  
Author(s):  
Dimitrios - Georgios Kontopoulos ◽  
Bernardo García-Carreras ◽  
Sofía Sal ◽  
Thomas P. Smith ◽  
Samraat Pawar
Keyword(s):  
Climate Change ◽  
Thermal Performance ◽  
Alternative Methods ◽  
Biological Traits ◽  
Thermal Physiology ◽  
Wide Range ◽  
Performance Curves ◽  
Biological Impacts ◽  
Using Data ◽  
Meta Analyses

There is currently unprecedented interest in quantifying variation in thermal physiology among organisms in order to understand and predict the biological impacts of climate change. A key parameter in this quantification of thermal physiology is the performance or value of a trait, across individuals or species, at a common temperature (temperature normalisation). An increasingly popular model for fitting thermal performance curves to data – the Sharpe-Schoolfield equation – can yield strongly inflated estimates of temperature-normalised trait values. These deviations occur whenever a key thermodynamic assumption of the model is violated, i.e. when the enzyme governing the performance of the trait is not fully functional at the chosen reference temperature. Using data on 1,758 thermal performance curves across a wide range of species, we identify the conditions that exacerbate this inflation. We then demonstrate that these biases can compromise tests to detect metabolic cold adaptation, which requires comparison of fitness or trait performance of different species or genotypes at some fixed low temperature. Finally, we suggest alternative methods for obtaining unbiased estimates of temperature-normalised trait values for meta-analyses of thermal performance across species in climate change impact studies.

scholarly journals Use and misuse of temperature normalisation in meta-analyses of thermal responses of biological traits

2017 ◽  
Author(s):  
Dimitrios - Georgios Kontopoulos ◽  
Bernardo García-Carreras ◽  
Sofía Sal ◽  
Thomas P. Smith ◽  
Samraat Pawar
Keyword(s):  
Climate Change ◽  
Thermal Performance ◽  
Alternative Methods ◽  
Biological Traits ◽  
Thermal Physiology ◽  
Wide Range ◽  
Performance Curves ◽  
Biological Impacts ◽  
Using Data ◽  
Meta Analyses

There is currently unprecedented interest in quantifying variation in thermal physiology among organisms in order to understand and predict the biological impacts of climate change. A key parameter in this quantification of thermal physiology is the performance or value of a trait, across individuals or species, at a common temperature (temperature normalisation). An increasingly popular model for fitting thermal performance curves to data – the Sharpe-Schoolfield equation – can yield strongly inflated estimates of temperature-normalised trait values. These deviations occur whenever a key thermodynamic assumption of the model is violated, i.e. when the enzyme governing the performance of the trait is not fully functional at the chosen reference temperature. Using data on 1,758 thermal performance curves across a wide range of species, we identify the conditions that exacerbate this inflation. We then demonstrate that these biases can compromise tests to detect metabolic cold adaptation, which requires comparison of fitness or trait performance of different species or genotypes at some fixed low temperature. Finally, we suggest alternative methods for obtaining unbiased estimates of temperature-normalised trait values for meta-analyses of thermal performance across species in climate change impact studies.

scholarly journals Use and misuse of temperature normalisation in meta-analyses of thermal responses of biological traits

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4363 ◽  
Author(s):  
Dimitrios - Georgios Kontopoulos ◽  
Bernardo García-Carreras ◽  
Sofía Sal ◽  
Thomas P. Smith ◽  
Samraat Pawar
Keyword(s):  
Climate Change ◽  
Thermal Performance ◽  
Alternative Methods ◽  
Biological Traits ◽  
Thermal Physiology ◽  
Wide Range ◽  
Performance Curves ◽  
Biological Impacts ◽  
Using Data ◽  
Meta Analyses

There is currently unprecedented interest in quantifying variation in thermal physiology among organisms, especially in order to understand and predict the biological impacts of climate change. A key parameter in this quantification of thermal physiology is the performance or value of a rate, across individuals or species, at a common temperature (temperature normalisation). An increasingly popular model for fitting thermal performance curves to data—the Sharpe-Schoolfield equation—can yield strongly inflated estimates of temperature-normalised rate values. These deviations occur whenever a key thermodynamic assumption of the model is violated, i.e., when the enzyme governing the performance of the rate is not fully functional at the chosen reference temperature. Using data on 1,758 thermal performance curves across a wide range of species, we identify the conditions that exacerbate this inflation. We then demonstrate that these biases can compromise tests to detect metabolic cold adaptation, which requires comparison of fitness or rate performance of different species or genotypes at some fixed low temperature. Finally, we suggest alternative methods for obtaining unbiased estimates of temperature-normalised rate values for meta-analyses of thermal performance across species in climate change impact studies.

scholarly journals Body Temperature Frequency Distributions: A Tool for Assessing Thermal Performance in Endotherms?

2021 ◽  
Vol 12 ◽  
Author(s):  
D.L. Levesque ◽  
J. Nowack ◽  
J.G. Boyles
Keyword(s):  
Body Temperature ◽  
Thermal Performance ◽  
Core Body Temperature ◽  
Ground Squirrels ◽  
Body Temperatures ◽  
Frequency Distributions ◽  
Biologically Relevant ◽  
Performance Curves ◽  
Continuous Body ◽  
Core Body

There is increasing recognition that rather than being fully homeothermic, most endotherms display some degree of flexibility in body temperature. However, the degree to which this occurs varies widely from the relatively strict homeothermy in species, such as humans to the dramatic seasonal hibernation seen in Holarctic ground squirrels, to many points in between. To date, attempts to analyse this variability within the framework generated by the study of thermal performance curves have been lacking. We tested if frequency distribution histograms of continuous body temperature measurements could provide a useful analogue to a thermal performance curve in endotherms. We provide examples from mammals displaying a range of thermoregulatory phenotypes, break down continuous core body temperature traces into various components (active and rest phase modes, spreads and skew) and compare these components to hypothetical performance curves. We did not find analogous patterns to ectotherm thermal performance curves, in either full datasets or by breaking body temperature values into more biologically relevant components. Most species had either bimodal or right-skewed (or both) distributions for both active and rest phase body temperatures, indicating a greater capacity for mammals to tolerate body temperatures elevated above the optimal temperatures than commonly assumed. We suggest that while core body temperature distributions may prove useful in generating optimal body temperatures for thermal performance studies and in various ecological applications, they may not be a good means of assessing the shape and breath of thermal performance in endotherms. We also urge researchers to move beyond only using mean body temperatures and to embrace the full variability in both active and resting temperatures in endotherms.

scholarly journals rTPC and nls.multstart: a new pipeline to fit thermal performance curves in R

2020 ◽  
Author(s):  
Daniel Padfield ◽  
Hannah O’Sullivan ◽  
Samraat Pawar
Keyword(s):  
Climate Change ◽  
Model Selection ◽  
Thermal Performance ◽  
Model Fitting ◽  
Multiple Models ◽  
List Type ◽  
Linear Least Squares ◽  
Wide Range ◽  
Performance Curves ◽  
Weighted Model

AbstractThe quantification of thermal performance curves (TPCs) for biological rates has many applications to problems such as predicting species’ responses to climate change. There is currently no widely used open-source pipeline to fit mathematical TPC models to data, which limits the transparency and reproducibility of the curve fitting process underlying applications of TPCs.We present a new pipeline in R that currently allows for reproducible fitting of 24 different TPC models using non-linear least squares (NLLS) regression. The pipeline consists of two packages – rTPC and nls. multstart – that allow multiple start values for NLLS fitting and provides helper functions for setting start parameters. This pipeline overcomes previous problems that have made NLLS fitting and estimation of key parameters difficult or unreliable.We demonstrate how rTPC and nls.multstart can be combined with other packages in R to robustly and reproducibly fit multiple models to multiple TPC datasets at once. In addition, we show how model selection or averaging, weighted model fitting, and bootstrapping can easily be implemented within the pipeline.This new pipeline provides a flexible and reproducible approach that makes the challenging task of fitting multiple TPC models to data accessible to a wide range of users.

scholarly journals Contrasting capabilities of two ungulate species to cope with extremes of aridity

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Melinda Boyers ◽  
Francesca Parrini ◽  
Norman Owen-Smith ◽  
Barend F. N. Erasmus ◽  
Robyn S. Hetem
Keyword(s):  
Climate Change ◽  
High Water ◽  
Future Climate Change ◽  
Body Temperatures ◽  
Wet Season ◽  
Trade Off ◽  
Ambient Temperatures ◽  
Mammalian Herbivores ◽  
Dry Seasons ◽  
Connochaetes Taurinus

AbstractSouthern Africa is expected to experience increased frequency and intensity of droughts through climate change, which will adversely affect mammalian herbivores. Using bio-loggers, we tested the expectation that wildebeest (Connochaetes taurinus), a grazer with high water-dependence, would be more sensitive to drought conditions than the arid-adapted gemsbok (Oryx gazella gazella). The study, conducted in the Kalahari, encompassed two hot-dry seasons with similar ambient temperatures but differing rainfall patterns during the preceding wet season. In the drier year both ungulates selected similar cooler microclimates, but wildebeest travelled larger distances than gemsbok, presumably in search of water. Body temperatures in both species reached lower daily minimums and higher daily maximums in the drier season but daily fluctuations were wider in wildebeest than in gemsbok. Lower daily minimum body temperatures displayed by wildebeest suggest that wildebeest were under greater nutritional stress than gemsbok. Moving large distances when water is scarce may have compromised the energy balance of the water dependent wildebeest, a trade-off likely to be exacerbated with future climate change.

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