Ecosystem conservation and management: A theoretical framework using biocultural diversity

Despite the crucial role of biocultural diversity in linking natural ecosystems with local communities, its spatially explicit characterization and integration into conservation planning remain limited. This study addresses this gap by developing a quantitative, spatially explicit framework that integrates ecological and cultural dimensions to inform conservation decision-making. Specifically, we (i) mapped biocultural diversity in the Jiroft region, (ii) identified its key drivers, and (iii) delineated spatially explicit conservation priorities. Biocultural diversity was quantified using a composite index that integrates species diversity (Simpson, Margalef, and Evenness indices), habitat quality (InVEST model), cultural diversity (language and religion), and indigenous knowledge derived from questionnaire data. A Bayesian network was applied to identify key drivers, and binary coding was used to assess spatial win-loss relationships. Results revealed significant differences in biocultural diversity across land-use types (p < 0.01), with forests exhibiting the highest values (0.581 ± 0.064) and agricultural lands the lowest (0.280 ± 0.061). Approximately 37% of the study area was classified as high biocultural diversity (conservation priority), while 30% exhibited low levels. The Bayesian network identified elevation, urbanization, and key species as dominant drivers. Notably, key species act as moderating factors, amplifying the positive influence of elevation while mitigating the negative effects of urbanization. Spatial win-loss analysis further indicated that over 20% of the area requires urgent restoration. This study advances existing approaches by linking composite biocultural diversity mapping with probabilistic driver analysis and actionable spatial prioritization. The proposed framework provides a transferable tool for conservation planning in arid landscapes, subject to context-specific indicator calibration and validation.