**5. Conclusions**

For the first time, circadian effects on sIgA were evaluated in Asian elephants. This study revealed visible daily quartic trends of sIgA, providing basic knowledge of using sIgA as a biomarker for further studies. Results sugges<sup>t</sup> that, just like for cortisol, time of day should be considered for saliva sample collection protocols for monitoring IgA. Moving forward, it will be important to understand differing response mechanisms when using IgA as a welfare indicator—chronic stressors may cause immune suppression and reductions in IgA, whereas acute illnesses could be associated with increases in IgA as part of an immune response to cope with underlying pathology. Thus, interpretation of IgA measures, just like GCs, may not always be straightforward. Both IgA and GCs have been shown to increase in response to acute stressors of a non-immune nature [13,57], and this certainly warrants further investigation before increased IgA concentrations can be considered a positive welfare indicator. As with other potential indicators of well-being, it is also important to understand normal physiological levels both within and between individuals, as well as in response to specific events. Biomarkers must be put into context, preferably by incorporating longitudinal measurements of multiple indicators, including IgA and GCs, to delineate concentrations indicative of an acute immune response or stressor, compared to those associated with longer-term positive or negative welfare states. The methodology described here provides a robust technique to investigate IgA in elephants, and these data provide a necessary baseline to interpret future data alongside other health and well-being measures, to determine whether incorporating IgA measurements will provide useful insight into elephant welfare.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2076-2615/10/1/157/s1, Figure S1: Individual IgA trends of all elephants, Figure S2: Individual cortisol trends of all elephants, Table S1: Raw data.

**Author Contributions:** Conceptualization, T.P., J.L.B., C.T., A.S.-F., and C.S.; Data curation, T.P., V.P.; Formal analysis, T.P., V.P., and C.S.; Funding acquisition, C.T. and A.S.F.; Investigation, T.P. and C.S.; Methodology, T.P., J.L.B., K.L.E., V.P., P.T., and C.S.; Project administration, T.P. and C.S.; Resources, C.T.; Software, V.P.; Supervision, J.L.B., A.S.-F., and C.S.; Validation, J.L.B., K.L.E., P.T. and C.S.; Visualization, T.P., J.L.B. and C.S.; Writing—original draft, T.P.; Writing—review and editing, T.P., J.L.B., C.T., A.S.-F., V.P. and C.S. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Brian Nixon fund for the protection of elephants in Thailand and partially supported by Chiang Mai University.

**Acknowledgments:** The authors thank the elephant owners and mahouts for cooperating in this study and allowing us to work with the elephants. We are grateful to Jaruwan Khonmee, Pakkanut Bansiddhi, and Pallop Tankaew for providing laboratory assistance. A special thanks to Patiparn Toin, Wachiraporn Toonrongchang, Panida Muanghong, Sarisa Klinhom, Khajohnpat Boonprasert and Siripat Khammesi for assisting in sample collection throughout this study.

**Conflicts of Interest:** The authors declare no conflict of interest.
