## 1 Introduction  
Genotype by environment interactions (GxE) in dairy cows have been reported widely [1; 2; 3; 4]. There are many different approaches to prove GxE, such as creating a cross-classified research design for, e.g., climate or feeding groups [2], or calculating correlations between the same trait recorded in different environments [3; 4; 5]. Another approach focusses on continuous environmental descriptors such as temperature, herd production level, or herd size and the application of random regression or reaction norm methodology [3]. In genomic studies, [PERSON] et al. [3] and [PERSON] et al. [6] enhanced their genome-wide association studies (GWAS) by considering GxE effects. In a two-step approach, they estimated intercept and slope effects for each single-nucleotide polymorphism (SNP) and found environment-sensitive and environment-robust SNPs. Similarly, [PERSON] et al. [1] conducted a GWAS for milk protein yield using average herd somatic cell score (SCS) as an environmental descriptor. Dependent variables in their genome-wide association models were intercept and slope from reaction norm models. New animal-friendly \"free walk\" housing systems, such as compost farming, reduce environmental stress, implying improved animal welfare [7]. However, the open-bedded pack area, as a mixture of composting material, microbes, and feces, increases the risk for specific bacterial infections and mastitis [7; 8; 9]. In this regard, several studies pointed out the associations between bedding management and physiological cow responses and addressed overall immunity [7; 10; 11]. A possible breeding approach is the selection of mastitis-resistant animals in a challenging environment [11; 12]. Selection of animals in harsh environments implied a pronounced genetic differentiation in udder health indicator traits [13]. Nevertheless, such a selection strategy, in specific environments, raises concerns regarding site suitability for conventional farming systems, and vice versa. Furthermore, selection on mastitis resistance is hampered due to the trait definitions and the complex polygenic mode of inheritance [12; 14]. Heritabilities for SCS and overall clinical mastitis were very small and lower than 0.05 [15; 16; 17]. Regarding accurate trait definitions, difficulties in distinguishing between cases of clinical and subclinical mastitis were reported [11; 16; 18]. SCS is considered a mastitis indicator in overall dairy cattle breeding goals or selection indices, due to a genetic correlation of approximately 0.75 [19]. However, the genetic correlation being substantially smaller than one suggests alternative and more precise mastitis indicators, such as differential somatic cell count, should be considered. Previous studies indicate that mastitis is caused by different pathogens to which the cow may respond differently [11]. [PERSON] et al. reported that genetic correlations between pathogen-specific mastitis traits ranged widely from 0.45 to 0.77 [14]. In their study, the lowest correlation of 0.45 was estimated between _Staphylococcus aureus_ and _Escherichia coli_, possibly due to the different immune responses of these two pathogens. The highest correlation of 0.77 was detected between _Streptococcus dysgalaciae_ and _Streptococcus uberis_. Both pathogens belong to the same genus and trigger a similar cascade of immune reactions in the udder [14]. The moderate genetic correlations suggest consideration that different mastitis pathogens can impact different traits in genetic evaluations for udder health. Addressing the farming effect, different bedding materials and different compost temperatures were associated with specific types of mastitis [7]. In this regard, _Coagulase-negative staphylococci_ (CNS) and _Corynebacterium sp_. (COR), as well as minor pathogens, are of increasing importance [20; 21]. Accordingly, due to pathogen-specific reactions of the immune system, [PERSON] et al. [22] suggested pathogen-specific mastitis analyses instead of the only moderately correlated indictor trait SCS.