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Mechanistic niche models are computational tools developed using biophysical principles to address grand challenges in ecology and evolution, such as the mechanisms that shape the fundamental niche and the adaptive significance of traits. Here, we review the empirical basis of mechanistic niche models in biophysical ecology, which are used to answer a broad array of questions in ecology, evolution and global change biology. We describe the experiments and observations that are frequently used to parameterize these models and how these empirical data are then incorporated into mechanistic niche models to predict performance, growth, survival and reproduction. We focus on the physiological, behavioral and morphological traits that are frequently measured and then integrated into these models. We also review the empirical approaches used to incorporate evolutionary processes, phenotypic plasticity and biotic interactions. We discuss the importance of validation experiments and observations in verifying underlying assumptions and complex processes. Despite the reliance of mechanistic niche models on biophysical theory, empirical data have and will continue to play an essential role in their development and implementation.

 

We examine the evidence linking species’ traits to contemporary range shifts and find they are poor predictors of range shifts that have occurred over decades to a century. We then discuss reasons for the poor performance of traits for describing interspecific variation in range shifts from two perspectives: ( a) factors associated with species’ traits that degrade range-shift signals stemming from the measures used for species’ traits, traits that are typically not analyzed, and the influence of phylogeny on range-shift potential and ( b) issues in quantifying range shifts and relating them to species’ traits due to imperfect detection of species, differences in the responses of altitudinal and latitudinal ranges, and emphasis on testing linear relationships between traits and range shifts instead of nonlinear responses. Improving trait-based approaches requires a recognition that traits within individuals interact in unexpected ways and that different combinations of traits may be functionally equivalent. 

Hybridization between species affects biodiversity and population sustainability in numerous ways, many of which depend on the fitness of the hybrid relative to the parental species. Hybrids can exhibit fitter phenotypes compared to the parental lineages, and this ‘hybrid vigour’ can then lead to the extinction of one or both parental lines.

In this study, we analysed the relationship between water loss and gas exchange to compare physiological performance among three tiger salamander genotypes—the native California tiger salamander (CTS), the invasive barred tiger salamanders (BTS) and CTS × BTS hybrids across multiple temperatures (13.5°C, 20.5°C and 23.5°C). We developed a new index of performance, the water‐gas exchange ratio (WGER), which we define as the ratio of gas exchange to evaporative water loss (μLVO₂/μL H₂O). The ratio describes the ability of an organism to support energetically costly activities with high levels of gas exchange while simultaneously limiting water loss to lower desiccation risk. We used flow through respirometry to measure the thermal sensitivity of metabolic rate and resistance to water loss of each salamander genotype to compare indices of physiological performance.

We found that temperature had a significant effect on metabolic rate and resistance to water loss, with both traits increasing as temperatures warmed. Across genotypes, we found that hybrids have a higher WGER than the native CTS, owing to a higher metabolic rate despite having a lower resistance to water loss.

These results provide a greater insight into the physiological mechanisms driving hybrid vigour and offer a potential explanation for the rapid spread of salamander hybrids. More broadly, our introduction of the WGER may allow for species‐ or lineage‐wide comparisons of physiological performance across changing environmental conditions, highlighting the insight that can be gleaned from multitrait analysis of organism performance.

Read the freePlain Language Summaryfor this article on the Journal blog.

 

Over the past decade, ecologists and physiologists alike have acknowledged the importance of environmental heterogeneity. Meaningful predictions of the responses of organisms to climate will require an explicit understanding of how organismal behavior and physiology are affected by such heterogeneity. Furthermore, the responses of organisms themselves are quite heterogeneous: physiology and behavior vary over different time scales and across different life stages, and because physiological systems do not operate in isolation of one another, they need to be considered in a more integrated fashion. Here, we review case studies from our laboratories to highlight progress that has been made along these fronts and generalizations that might be made to other systems, particularly in the context of predicting responses to climate change.