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A longstanding debate exists on whether ecological phenomena should be modelled ‘top-down’ (modelling patterns that arise from mechanisms) or ‘bottom-up’ (modelling mechanisms to generate pattern). Recently, the discussion re-emerged in the context of modelling the spread of SARS-CoV-21 . Simply put, the point made by Carlson et al. was that top-down correlative models are inappropriate, whereas bottom-up epidemiological models are fine. Rather than opposing families of models, we argue that all have strengths and limitations and that judicious use of all available tools is the way forward.

As new cases of COVID-19 are being confirmed worldwide pressure is mounting to increase understanding of the factors underlying the spread the disease. Using data on local transmissions until the 23rd of March 2020, we develop an ensemble of 200 ecological niche models to project monthly variation in climate suitability for spread of SARS-CoV-2 throughout a typical climatological year. Although cases of COVID-19 are reported all over the world, most outbreaks display a pattern of clustering in relatively cool and dry areas. The predecessor SARS-CoV-1 was linked to similar climate conditions. Should the spread of SARS CoV-2 continue to follow current trends, asynchronous seasonal global outbreaks could be expected. According to the models, temperate warm and cold climates are more favorable to spread of the virus, whereas arid and tropical climates are less favorable. However, model uncertainties are still high across much of sub-Saharan Africa, Latin America and South East Asia. While models of epidemic spread utilize human demography and mobility as predictors, climate can also help constrain the virus. This is because the environment can mediate human-to-human transmission of SARS-CoV-2, and unsuitable climates can cause the virus to destabilize quickly, hence reducing its capacity to become epidemic.

The widespread observation that heat tolerance is less variable than cold tolerance (‘cold-tolerance asymmetry’) leads to the prediction that species exposed to temperatures near their thermal maxima should have reduced evolutionary potential for adapting to climate warming. However, the prediction is largely supported by species-level global studies based on single estimates of both physiological metrics per taxon. We ask if cold-tolerance asymmetry holds for Iberian lizards after accounting for intraspecific variation in critical thermal maxima (CTmax) and minima (CTmin). To do so, we quantified CTmax and CTmin for 58 populations of 15 Iberian lizard species (299 individuals). Then, we randomly selected one population from each study species (population sample = 15 CTmax and CTmin values), tested for variance homoscedasticity across species, and repeated the test for thousands of population samples as if we had undertaken the same study thousands of times, each time sampling one different population per species. The ratio of variances in CTmax to CTmin across species varied up to 16-fold depending on the populations chosen. Variance ratios show how much CTmax departs from the cross-species mean compared to CTmin, with a unitary ratio indicating equal variance of both thermal limits. Sampling one population per species was six times more likely to result in the observation of greater CTmax variance (‘heat-tolerance asymmetry’) than cold-tolerance asymmetry. The null hypothesis of equal variance was twice as likely for cases of cold-tolerance asymmetry than for the opposite scenario. Range-wide, population-level studies that quantify heat and cold tolerance of individual species are urgently needed to ascertain the global prevalence of cold-tolerance asymmetry. While broad latitudinal clines of cold tolerance have been strongly supported, heat tolerance might respond to smaller-scale climatic and habitat factors hence go unnoticed in global studies. Studies investig