{"query_echo":{"q":"","filters":{"analysis_type":["habitat suitability modelling"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'habitat suitability modelling' for facet 'analysis_type' is not in the controlled vocabulary."}]},"total":{"value":1,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=habitat+suitability+modelling","stability":"beta","ai_marking":{"digital_source_type":{"uri":"http://cv.iptc.org/newscodes/digitalsourcetype/trainedAlgorithmicMedia","name":"Created using Generative AI"},"notice":"Summary and key insights are generated using artificial intelligence."},"results":[{"id":"wwf-000407","url":"https://climateinsightsdirectory.org/document/wwf-000407","title":"RED PANDA STATUS IN BHUTAN","publisher":{"name":"WWF International","organization":"wwf-international"},"document_type":"report","language":"en","date_published":"2023","source_url":"https://www.worldwildlife.org/documents/692/3duh1dztfc_red_panda_report_2_.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"A 2023 national survey in Bhutan identified 302 unique red pandas across 15 districts using non-invasive genetic analysis of 482 fecal samples. The study revealed a population structure consisting of three distinct genetic clusters (western, central, and eastern), with evidence of significant inbreeding (mean Fis = 0.55) and a historical population bottleneck approximately 5,000 years ago. While the population is currently in demographic equilibrium, the report emphasizes the need for habitat protection and the enhancement of biological corridors to facilitate gene flow and reduce genetic isolation.","ai_generated":true,"unit":"wwf-000407#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The national survey identified 302 unique red panda individuals from 482 collected fecal samples, with the highest concentrations found in Jigme Khesar Strict Nature Reserve (42 individuals) and Jigme Dorji National Park (39 individuals).","ai_generated":true,"unit":"wwf-000407#insight-1","date_modified":"2026-10-23"},{"text":"Red pandas were detected in 19 of Bhutan's 20 districts, with the only exception being Pemagatshel. The estimated Area of Occupancy (AOO) is 1,436 km², while the Extent of Occurrence (EOO) is 28,651.364 km².","ai_generated":true,"unit":"wwf-000407#insight-2","date_modified":"2026-10-23"},{"text":"Genetic analysis using microsatellites revealed a significant level of inbreeding within the Bhutanese red panda population, with a mean inbreeding coefficient (Fis) of 0.55 ± 0.044.","ai_generated":true,"unit":"wwf-000407#insight-3","date_modified":"2026-10-23"},{"text":"The population is structured into three distinct genetic clusters corresponding to western, central, and eastern Bhutan. The central population shows an admixed pattern, suggesting it may act as a mixing zone for gene flow between the western and eastern groups.","ai_generated":true,"unit":"wwf-000407#insight-4","date_modified":"2026-10-23"},{"text":"Mitochondrial DNA analysis identified 21 haplotypes in Bhutan, with Haplotype H3 being the most common across 13 districts. Haplotype sharing was also observed between red panda populations in Bhutan and India, indicating ancestral gene flow.","ai_generated":true,"unit":"wwf-000407#insight-5","date_modified":"2026-10-23"},{"text":"Demographic analysis suggests the population is currently in equilibrium, but a Bayesian skyline plot indicates a sharp decline in effective population size approximately 5,000 years ago, followed by a more recent expansion.","ai_generated":true,"unit":"wwf-000407#insight-6","date_modified":"2026-10-23"},{"text":"The study identifies several critical threats to red pandas in Bhutan, specifically free-roaming dogs used for livestock protection, habitat degradation caused by climate change, and a lack of ecological awareness among local communities.","ai_generated":true,"unit":"wwf-000407#insight-7","date_modified":"2026-10-23"}],"climate_tags":["climate change","biodiversity conservation"],"geography_discussed":["India","People's Republic of China","Tibet"],"frame_perspective":[],"analysis_type":["population survey","genetic analysis","habitat suitability modelling"]}]}