*4.6. Statistical Analysis*

One-way ANOVA, Duncan, and Student's t tests were applied for data analysis using the SPSS 25® program. A confidence level of 95% (*p* = 0.05) was adopted for all statistical tests. A comparison between regions districts was performed (different lowercase letters refer to a significant difference) in terms of AGB/BGB, R1, R2, P1, P2, and P3 (Tables 1, 3, and 5). A comparison between villages of different districts was performed (different capital letters refer to a significant difference) as well as between AGB and BGB (different lowercase letters refer to a significant difference (Tables 2, 4, and 6). In a similar vein, a comparison between grasses and legume types in terms of yield, and compositional elements (N, P, K, crude fiber and crude protein), was performed (different letters refer to a significant difference) (Tables 7 and 8).

#### **5. Conclusions**

Kashmir Valley rangelands (northern, central and southern Kashmir regions) were investigated for their AGB, BGB, and total biomass (grasses/legumes) yields in three site types (grazed, protected, and seed-sown) along with their leaf nutritional profiles (N, P, K, crude fiber, and crude protein contents). Results showed an overall moderate grazing with a low to moderate effect on biomass. AGB, BGB, and total biomass yields were the highest in central Kashmir, followed by southern, and northern Kashmir. AGB and total biomass yields recorded the highest values in the protected sites of central Kashmir region, whereas, BGB yield scored the highest value in the protected sites of southern Kashmir region. On the other hand, Agrostis grass showed the highest crude fiber and crude protein contents among grasses found in the studied regions, whereas the highest crude fiber and crude protein contents among prominent legumes were recorded for red clover and white clover, respectively. Those findings concluded the successful management of Kashmir rangelands in protected sites, resulting in high biomass yields along with the considerable nutritional value of grasses and legumes.

**Author Contributions:** Conceptualization, J.A.M. and M.u.d.K.; methodology, J.A.M. and M.u.d.K.; software, P.K. and S.A.F.; validation, M.u.d.D., I.S., H.F.A., A.A.B., S.A.A., A.M.A., P.K. and S.A.F.; formal analysis, S.A.F.; investigation, S.A.F.; resources, H.F.A., A.A.B., S.A.A. and A.M.A.; data curation, S.A.F.; writing—original draft preparation, M.u.d.K. and S.A.F.; writing—review and editing, I.S., P.K. and S.A.F.; visualization, M.u.d.D., I.S., H.F.A., P.K. and S.A.F.; supervision, M.u.d.K. and S.A.F.; project administration, S.A.F.; funding acquisition, H.F.A. and S.A.F. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was funded by Institutional Fund Projects under grant No. (IFPIP: 394-130-1443), Ministry of Education in Saudi Arabia.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** All data used in the present study are included in the manuscript.

**Acknowledgments:** This research work was funded by Institutional Fund Projects under grant No. (IFPIP: 394-130-1443). The authors gratefully acknowledge technical and financial support provided by the Ministry of Education and King Abdulaziz University, DSR, Jeddah, Saudi Arabia.

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