Intelligent multi-modeling reveals biological relationships and adaptive phenotypes for dairy cow adaptation to climate change

The adaptation of animals to thermal stress involves various variables and adaptive mechanisms. These mechanisms are complex and interconnected, involving both linear and non-linear interactions and dependencies. In this study, we develop a systematic methodology with multivariate models and machine learning algorithms to (i) model complex patterns of relationships or multi-phenotypic differences between the thermal environment and thermoregulatory, hormonal, biochemical, hematological and productive responses; and (ii) identify potential associations among biological relationships that may underlie shared and specific phenotypic patterns of adaptive responses. Thirty clinically healthy multiparous lactating cows with body condition score 3–4 under the same nutritional, health and reproductive management conditions were used in the study. A simple correlation matrix revealed weak and nonexistent correlations between the variables. However, when canonical correlation analysis was used, 12 out of 15 of the canonical correlations evaluated were significant (p < 0.05). Moderate levels of canonical correlations (0.300 ≤ $r_c$ ≤ 0.628) and low values of squared canonical correlation (0.141 ≤ $r_c^2$ ≤ 0.384) between indicators (thermal environment, thermoregulatory responses, biochemistry, hormonal profile, hematological responses and milk composition) were reported. Exceptionally, the thermal environment × biochemistry pair demonstrated notably high values ($r_c$ = 0.8468 and $r_c^2$= 0.7171). Biological analysis formed seven distinct mechanisms, each associated with specific biological functions and climate-driven effects on physiological and productive traits. 1) Blood traits were related to all milk components; 2) Lipid and energy metabolism, as well as kidney function, are related to the regulation of body temperature and milk composition; 3) Immunity and thyroid hormones are related to radiant thermal load; and 4) Homeostasis is the organic balance maintained between thermoregulatory, hormonal, hematological, productive, and biochemical functions, which are influenced by environmental variables. Applying the random forest method to classify predictions of adaptive responses based on climatic variables showed that all thermoregulatory, hormonal, biochemical, and hematological responses are important, except for urea and T₃ concentrations, which had negative importance values. We conclude that adaptation results from an integration between energy and lipid metabolism, renal function, hormonal profile, and thermoregulatory, hematological, and productive responses. Finally, we recommend the use of multi-models to reveal the complexity of adaptation mechanisms and identify biomarkers that can be used to monitor the dairy flocks, to employ strategies which mitigate the impacts of climate change in animals and promote sustainability of animal production.