«Unidos por la naturaleza en el camino hacia 2045: una visión estratégica de 20 años para la Unión» articula el compromiso de la UICN con «un mundo justo que valora y conserva la naturaleza» y establece una dirección clara para las próximas dos décadas. Orienta los esfuerzos colectivos para salvaguardar la biodiversidad, inspirar el compromiso social e impulsar un cambio transformador hacia un futuro sostenible.
«Unidos por la naturaleza en el camino hacia 2045: una visión estratégica de 20 años para la Unión» articula el compromiso de la UICN con «un mundo justo que valora y conserva la naturaleza» y establece una dirección clara para las próximas dos décadas. Orienta los esfuerzos colectivos para salvaguardar la biodiversidad, inspirar el compromiso social e impulsar un cambio transformador hacia un futuro sostenible.
«Unidos por la naturaleza en el camino hacia 2045: una visión estratégica de 20 años para la Unión» articula el compromiso de la UICN con «un mundo justo que valora y conserva la naturaleza» y establece una dirección clara para las próximas dos décadas. Orienta los esfuerzos colectivos para salvaguardar la biodiversidad, inspirar el compromiso social e impulsar un cambio transformador hacia un futuro sostenible.
The Smart DESERT project was funded by the French Development Agency (AFD) with a total budget of EUR 10 million and implemented by a consortium of organisations led by IUCN ROWA, targeting the area of the North-East Badia highlands in Jordan. The project was designed to achieve two key objectives: (1) increased year-round income and (2) improved work conditions, with an overarching goal of economic empowerment of Syrian refugees and vulnerable Jordanians in the agricultural sector.
The project addresses key challenges such as water scarcity, land degradation, rural unemployment, and limited market access. By introducing water harvesting systems, regenerative agriculture practices, and digital tools, Smart DESERT helps farmers improve productivity, conserve natural resources, and build climate resilience. It also supports the creation of home-based agribusinesses and facilitates connections to markets and finance.
Un objetivo clave de esta guía es replantear la EIA para ayudar a apoyar la conservación de la biodiversidad y el logro de los objetivos globales relacionados (junto con los objetivos climáticos y otros objetivos de desarrollo social). Esta guía se centra en la biodiversidad y el desarrollo eólico y solar, y está dirigida principalmente a planificadores gubernamentales y promotores de proyectos. Sin embargo, dado que está diseñada para ayudar a abordar algunos de los desafíos existentes en la EIA, su aplicabilidad es potencialmente más amplia.
As a botanical “living fossil,” Cathaya argyrophylla in the Bamianshan Nature Reserve faces severe survival challenges. The extreme drought of 2022 pushed its communities to the brink of withering, exacerbated by habitat fragility, necessitating systematic conservation measures. In 2024, the Bamianshan Nature Reserve launched a specialized protection project for Cathaya argyrophylla. Through labeling individuals, establishing permanent sample plots and monitoring sites, the project systematically investigates population structure and habitat characteristics. These efforts accurately delineate the age composition of Cathaya argyrophylla, assess its natural regeneration capacity, and provide a scientific basis for targeted conservation and climate change adaptation.
I. Background
The Yunnan snub-nosed monkey (Rhinopithecus roxellana) is a species that mainly occurs in the Yunling Mountains between the Jinsha and Lancang Rivers, with about 3,800 extant individuals. Yunnan Yunlong Tianchi National Nature Reserve, as its southernmost distribution site, is a key area for maintaining the survival space of the species. Historically, the population of Yunnan snub-nosed monkeys in the region has been reduced from four to two populations due to habitat fragmentation, human interference and habitat retreat.
II. Solution Application Approach
1. Standardized monitoring and technology upgrading. Standardize data collection norms: monitor the population 8 days a month, 12 hours a day, recording population size, behavioral rhythms, food habits, etc. to ensure data validity.
Upgrade equipment configuration: Equipped with GPS, infrared cameras, etc. to fill the gap of image records. 5 infrared cameras were installed in the Tianchi population area, successfully obtaining fecal samples and activity traces.
2. Expert team and long-term monitoring system. An inter-agency expert team was formed to solve the problem of insufficient expert guidance in the past.
3. Food resources and habitat management. Establishment of a food resource database: Record the 26 species of plants that the Longma Mountain population feeds on and the seasonal changes in food habits to provide a basis for habitat restoration. Habitat corridor restoration: Prioritize the protection of key vegetation types such as fir forests and Yunnan hemlock forests for the five habitat patches where Longma Mountain populations are active.
4. Man-made disturbance control and community participation. Quantify the types of disturbance: focus on monitoring high-frequency disturbance such as mushroom picking in summer, mark the location of disturbance, and set targeted no-entry periods. Community education: Promote residents’ awareness of conservation and reduce the impact of activities on the monkey population.
Core Challenges
1. Population growth bottleneck: the annual growth rate of Longmashan population has dropped from rapid growth before 2011 to a stable state after 2012, confirming that the habitat is close to the environmental capacity and the habitat quality needs to be optimized.
2. Fragmentation of monitoring data: after standardization, the rate of invalid data has dropped from 53% to a manageable range, and the Tianchi population has moved from “data gaps” to “confirmation of existence”.
3. Threat of man-made disturbance: the intensity of disturbance reached 4.23 in summer, and the seasonal control reduced the stress reaction of the monkey population.
4. Risk of survival of small populations: The survival of the Tianchi population was confirmed for the first time through the deployment of infrared cameras and feces analysis, which provided a basis for the construction of the corridor.
Positive Results
1. Stable population growth: the Longmarsaurus population increased from 127 in 2011 to 190 in 2024, a 49% increase, with a stable population structure, close to the environmental capacity but in dynamic equilibrium.
2. Behavioral and ecological adaptation research: clarify the daily activity rhythms and seasonal dietary changes of Yunnan snub-nosed monkeys, and provide scientific support for food resource management.
3. Synergistic effect between technology and community: standardized monitoring has improved the positioning accuracy of human interference, and community participation has reduced the frequency of interference in summer by 15% year-on-year in 2024, providing a replicable model for similar protected areas.
4. Breakthrough in the protection of small populations: The survival of the Tianchi population has been confirmed through fecal and trace monitoring, and as the southernmost population of the Yunnan snub-nosed monkey, it lays the foundation for the study of species distribution boundaries and habitat corridor planning.
Through the integrated strategy of “scientific monitoring-habitat restoration-community governance”, the program effectively mitigated the threats faced by the Yunnan snub-nosed monkeys, such as stagnant population growth, habitat fragmentation and human interference, and provided a closed-loop management paradigm of “monitoring-assessment-intervention” for the protection of the endangered species. This provides a “monitoring-assessment-intervention” paradigm for endangered species conservation.
The Asian elephant remains endangered due to poaching, habitat loss, and growing human-elephant conflict—one of the most pressing conservation challenges globally. In response, our team developed an integrated monitoring and early warning system that combines aerial drones with ground-based infrared cameras. This “sky & ground” network ensures real-time, full-time, and large-scale coverage of elephant activity across Yunnan Province. Drones use thermal imaging and zoom to detect elephants even at night, while 600 infrared cameras enable 24/7 data capture with real-time alerts.
Supported by China’s national and provincial forestry departments, the project trains local youth as monitors and forms community teams. Over 130,000 early warnings have been issued, helping reduce human-elephant conflict and improving safety.
It contributes to GBF Targets A, B, and 1, 4, 20, 21. It strengthens biodiversity protection, enhances community engagement, and offers a scalable model for coexistence.
The Restoration Platform, the core of Forest Cloud, transforms global restoration by simplifying fundraising and ensuring transparency for forest conservation. Since 2018, it has evolved to bring back a trillion trees and conserve 3 trillion existing trees. The open-source, open access, digital solution currently supports scientific restoration initiatives as well as managing and coordinating conservation and restoration efforts globally. It benefits from robust Restoration Standards, proprietary restoration monitoring applications, a robust peer-review system and an ecosystem of ancillary digital solutions – the ‘Forest Cloud’. Proven across 300 restoration initiatives and growing, the Platform unifies restoration organizations (ROs), donors, and scientists. Having demonstrated its success by restoring over 94M trees in 6 years, we now seek to improve its scale and geographic reach and solve the logistical challenges to contribute to a sustainable, thriving future.
WildGuard AI is an Edge AI-powered sensing system by NOARKTECH designed to protect biodiversity and reduce climate-related risks in forest and farm landscapes. Using IIoT (Industrial internet of things) devices connected via LoRaWAN (Long Range Wide Area Network) and LTE (Long Term Evolution), it detects wildfires, heatwaves, and human-wildlife conflict in real time. It combines bioacoustic AI (e.g., elephant and hornbill calls), temperature, and gas sensors to detect anomalies early.
Paired with PAMS (Protected Area Management & Security System), a dashboard for real-time alerts, analytics, and visualization, the system supports proactive action. Piloted in India’s Western Ghats, it helped reduce crop loss, fire spread, and wildlife threats. WildGuard AI and PAMS enable scalable, affordable, and sustainable nature-based intelligence for climate resilience and conservation.
Ribbit is a citizen science web app that uses few-shot transfer machine learning to record, identify, and classify frog and toad calls, contributing crowdsourced data to the Global Biodiversity Information Facility (GBIF) to address data gaps, especially in the Global South. Identification apps offer significant potential for automatic in situ biodiversity monitoring (Global Partnership on Artificial Intelligence, 2022; Tuia et al., 2022; Nieto-Mora et al., 2023). Our app focuses on anurans, as they are crucial ecosystem indicators (Estes-Zumpf et al., 2022), with over 40% of the species at risk of extinction, and their unique vocalizations are ideal for acoustic identification. Beta testers revealed the app’s potential to contribute data to GBIF while empowering citizen scientists to engage in ecological monitoring. By creating an open-access platform for labeling biodiversity data, Ribbit enables conservation organizations to develop strategies for protecting vulnerable populations and preserving critical ecosystems.
This project is developed on rural farms and Civil Society Natural Reserves within the KBA Serranía de los Paraguas, part of the Tropical Andes and Biogeographic Chocó biodiversity hotspots and the DRMI Serranía de los Paraguas protected area. Unsustainable livestock near forests safeguarding water sources has triggered human-wildlife conflicts (HWCs), tied to land-use change, biodiversity and ecosystem service loss, livestock predation, and retaliatory poaching. To address this, we propose a bottom-up approach involving landscape planning, adaptive livestock practices, sustainable energy for rural homes, behavior change toward wildlife, and community-based jaguar monitoring. This promotes long-term coexistence and improves life quality for people and jaguars, contributing to the Global Biodiversity Framework targets and Sustainable Development Goals, aligned with coexistence principles: do no harm, collaborate, understand context, integrate science and policy, and ensure sustainable pathways.
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