Global strategies to halt the dual crises of biodiversity loss and climate change are often formulated separately, even though they are interdependent and risk failure if pursued in isolation. The Global Safety Net maps how expanded nature conservation addresses both overarching threats. We identify 50% of the terrestrial realm that, if conserved, would reverse further biodiversity loss, prevent CO₂ emissions from land conversion, and enhance natural carbon removal. This framework shows that, beyond the 15.1% land area currently protected, 35.3% of land area is needed to conserve additional sites of particular importance for biodiversity and stabilize the climate. Fifty ecoregions and 20 countries contribute disproportionately to proposed targets. Indigenous lands overlap extensively with the Global Safety Net. Conserving the Global Safety Net could support public health by reducing the potential for zoonotic diseases like COVID-19 from emerging in the future.

The recovery of wild tigers in India and Nepal is a remarkable conservation achievement, but it sets the stage for increased human–wildlife conflict where parks are limited in size and where tigers reside outside reserves. We deployed an innovative technology, the TrailGuard AI camera-alert system, which runs on-the-edge artificial intelligence algorithms to detect tigers and poachers and transmit real-time images to designated authorities responsible for managing prominent tiger landscapes in India. We successfully captured and transmitted the first images of tigers using cameras with embedded AI and detected poachers. Notifications of tiger images were received in real time, approximately 30 seconds from camera trigger to appearing in a smart phone app. We review use cases of this AI-based real-time alert system for managers and local communities and suggest how the system could help monitor tigers and other endangered species, detect poaching, and provide early warnings for human–wildlife conflict.

Assemblages of large mammal species play a disproportionate role in the structure and composition of natural habitats. Loss of these assemblages destabilizes natural systems, while their recovery can restore ecological integrity. Here we take an ecoregion‐based approach to identify landscapes that retain their historically present large mammal assemblages, and map ecoregions where reintroduction of 1–3 species could restore intact assemblages. Intact mammal assemblages occur across more than one‐third of the 730 terrestrial ecoregions where large mammals were historically present, and 22% of these ecoregions retain complete assemblages across > 20% of the ecoregion area. Twenty species, if reintroduced or allowed to recolonize through improved connectivity, can increase the area of the world containing intact large mammal assemblages by 54% (11 116 000 km ² ). Each of these species have at least two large, intact habitat areas (> 10 000 km ² ) in a given ecoregion. Timely integration of recovery efforts for large mammals strengthens area‐based targets being considered under the Convention on Biological Diversity.

Human–elephant conflict has become a conservation challenge in Asia and Africa resulting in considerable human fatalities annually. We deployed an AI‐embedded camera‐alert system in a conflict hotspot in West Bengal, India to determine if AI algorithms could accurately detect elephants and if real‐time alerts that triggered a rapid response could prevent serious incidents. The system successfully detected elephants near villages (266 events) and transmitted real‐time alerts () permitting quick response by field personnel to prevent conflict (, SD = 12.4 min to arrival). Matriarch herds of elephants were detected mostly at night when human traffic was minimal; lone adult bulls, the class most prone to conflict, were detected day and night. Frequent detections of humans (33,217 events) on routes used by elephants highlighted the value of real‐time monitoring especially during daytime. Twelve human fatalities and eighteen serious injuries occurred in the study area between 2019 and 2023 but none during deployment of the AI system, supporting the hypothesis that alerts integrated with rapid response can reduce conflict. Loss of lives and livelihoods underscore the urgency of applying this approach to other elephant ranges and adapting AI models to conflict‐prone species to provide early warning and promote coexistence.

Understanding local encounters with large carnivores is important for promoting sustainable coexistence. The use of smartphones and social media in geographically remote areas offers a novel avenue to study human–wildlife encounters from a local perspective. We conducted a content analysis of mobile videos on social media ( n = 207) to characterize human encounters with snow leopards, gray wolves, and brown bears on the Tibetan Plateau in China. We also used ethnographic interviews to understand the backgrounds and motivations of videographers. Results show large carnivore encounters are not necessarily conflictual. Over half of encounters are neutral without observable interference between people and predators. The likelihood of a “negative encounter” is significantly associated with the target species, the distance between the videographer and the animal, the level of human influence in the surroundings, and the presence of other animals (i.e., dogs and livestock). Local Tibetan herders document unusual encounters with carnivores using videos for various reasons, but what is deemed unusual is context‐dependent and fluid. Our study demonstrates that social media videos can provide valuable insights into the diversity and complexity of human–wildlife interactions. We encourage conservationists to develop visual participatory programs to better engage local people in conservation knowledge production.

Ambitious biodiversity goals to protect 30% or more of the Earth’s surface by 2030 (30x30) require strategic near-term targets. To define areas that must be protected to prevent the most likely and imminent extinctions, we propose Conservation Imperatives—16,825 unprotected sites harboring rare and threatened species and spanning ~164 Mha of the terrestrial realm. We estimate that protecting the Conservation Imperatives would cost approximately US$169 billion [90% probability: $146 — $228 billion]. Globally, 38% of the 16,825 sites are either adjacent to or within 2.5 km of an existing protected area, potentially reducing land acquisition and management costs. These sites should be prioritized for conservation action over the next five years as part of a broader strategy to expand the global protected area network. The expansion of global protected areas between 2018–2023 incorporated only 7% of sites harboring range-limited and threatened species, highlighting a renewed urgency to conserve these habitats. Permanently protecting only 0.74% of land found in the tropics, where Conservation Imperatives are concentrated, could prevent the majority of predicted near-term extinctions once adequately resourced. We estimate this cost to be US$29 billion to US$46 billion per year over the next five years. Multiple approaches will be required to meet long-term protection goals: providing rights and title to Indigenous Peoples and Local Communities (IPLCs) conserving traditional lands, government designation of new protected areas on federal and state lands, and land purchase or long-term leasing of privately held lands.