Conclusion

Spatio-temporal changes in land cover highlight the decline of vegetation cover from 96.57 (1973) to 86.55% (2012). Temporal land use analyses reveal that paved surfaces (built-up) have increased from 0.63% (1973) to 2.35% (2018) and forest cover has decreased from 43.83% (1973) to 34% (2012). The results highlight conversion of forests to commercial agriculture, industrial and cascaded developmental activities acted as major driving forces of degradation. Forest fragmentation analysis highlight that the domination of forests receded during the post-1990s with the formation of non-forest patches. The unauthorized land holdings are another major issue faced by the forests of Shimoga. The Total encroachment of reserve forest in the 3 divisions of Shimoga district accounts for 39599 ha. The political, social, and religious pressures are threatening forests and troubling regulatory agencies in management. The results emphasize the need for an immediate eco-restoration measure to arrest fragmentation, human-animal conflicts, and consequent reduction in goods and services. ESR prioritization of Shimoga based on the collection and compilation of primary data of ecological, geo-climatic, and social aspects depict sensitive regions necessitates for conservation. The village wise ESR demarcation portraits 184 villages as ESR-1, 472 under ESR2, 565, and 364 under ESR 3,4 respectively. ESR1 and 2 depict the zone of highest sensitivity, absolutely no new developmental activities such as mining or dams are to be allowed in this zone. So, the majority of the villages fall under ESR 3 (high sensitivity category), where large scale developmental activities, change in land use and forest encroachment should not be allowed, however small scale industries like IT sectors, agro-processing industries are permitted. The integration and analysis of various heterogeneous data of several ecological, biological, geo-climatic, and social variables resulted in prioritizing sensitive regions will assist as a decision support system, for management and conservation plans. Integration of these data with an appropriate spatial decision support system will benefit various stakeholders and managers to take rationale and formal decisions in the management and conservation-related plans.