Biocultural diversity reflects the interplay among biological and cultural diversity within social-ecological systems, shaped by human societies’ unique interactions with nature. This concept encompasses diverse knowledge, beliefs, practices, and values linked to local biodiversity. Despite its growing relevance, research gaps persist, including the need for theoretical clarity and a broader empirical application. To examine biocultural diversity’s role in conservation and sustainability, we conducted a systematic mapping of scientific literature in English and Spanish from 1990 to 2021, using cluster analysis to identify research trends. Including Spanish literature broadened the analysis, offering unique perspectives often overlooked. Results reveal gaps on research, particularly regarding intangible biocultural components (e.g., traditional knowledge, values, or worldviews) and the need for research in underrepresented regions like Africa and Asia. To advance in this direction, we propose a novel classification for biocultural diversity to foster holistic understanding, encourage exploration of intangible components, and promote collaboration among stakeholders.

As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071–2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological responses under climate change scenarios.