American Bird Conservancy (ABC) is a non-profit membership organization with the mission of conserving wild birds and their habitats throughout the Americas. Its focus is on threats to birds in the Western Hemisphere – threats which include overuse of pesticides, urban sprawl, habitat destruction, and invasive species.ABC is the second BirdLife International partner in the United States and works in cooperation with other groups and agencies, including The Bird Conservation Alliance, Partners in Flight, and the North American Bird Conservation Initiative. Overall, ABC’s network spans 15 countries and protects over a million acres – benefiting birds large and small.Their partner projects have included publication of bird guides, education on the location and construction of wind turbines, educating farmers to promote bird-friendly agriculture, and raptor conservation. Their Conservation Counterparts Program helps other organizations fundraise for Latin America and Caribbean conservation projects.One of ABC's key strategies involves working with conservation partners to establish and sustain protected reserves across the Americas, including safe havens for Araripe Manakin Antilophia bokermanni in Brazil (with partner Aquasis), and Blue-billed Curassow Crax alberti in Colombia (alongside Fundación ProAves).
A global standard for the identification of Key Biodiversity Areas (KBAs) was published 10 years ago to provide a unified set of criteria for identifying 'sites of significance for the global persistence of biodiversity'. We review the initiative's origins, the KBA identification process, characteristics of the current network, threats, policy uptake, private sector applications and future priorities. KBAs are identified using criteria with quantitative thresholds relating to threatened or geographically restricted species or ecosystems, ecological integrity, biological processes, or irreplaceability. These criteria can be applied in terrestrial, inland water, marine and subterranean environments, and to all taxonomic groups. A total of 16,596 KBAs covering 22.1 million km2 has been identified, with 29% of these sites in marine and 26% in freshwater ecosystems. KBAs range from 0.001 km2 to 712,457 km2 in extent, with a median size of 141 km2 and a mean of 1,364 km2. Most (63%) qualify due to the globally threatened species they support, with 48% being important for biological processes and 39% for geographically restricted species. KBAs have been identified for 18,365 qualifying species in total, of which 37% are plants and 32% are birds. The most prevalent threats are biological resource use (hunting, logging, fishing, etc., impacting 40.8% of sites with available data), unsustainable agriculture (40.7%), human intrusions and disturbance (38.4%) and natural systems modifications (water management and fire; 33.4%). KBAs are important for delivering ecosystem services to people, both locally and globally. KBAs have had widespread impact in informing protected area designation in all regions. In total, 10,054 sites (62%) are covered completely or partially by protected areas. Hence, KBAs are highly relevant to Target 3 (and other targets) in the Kunming-Montreal Global Biodiversity Framework, and to Sustainable Development Goals 14.5, 15.1, and 15.4. Indicators based on KBA data are therefore being used by the Convention on Biological Diversity and United Nations to track progress towards these targets. Many companies and financial institutions use KBAs to assess their exposure to nature-related risks and to identify opportunities for site-level, nature-positive actions. Future priorities include expanding and updating KBA assessments, and strengthening efforts to protect, conserve and safeguard these sites effectively.
Artificial intelligence (AI) can rapidly process large ecological datasets, uncover patterns, and inform conservation decisions, but responsible adoption depends as much on human-centric skills as on technical methods. Ecologists face steep learning curves, an overwhelming and fast-evolving model landscape, uneven access to data and computing, and a growing transparency deficit. These challenges require human-centric skills like time management, critical thinking, collaboration, communication, creativity, and project management to select, implement, interpret, and responsibly translate AI outputs into ecological insight and action. We led a workshop, EcoViz+AI: Visualization and AI for Ecology, that brought together 35 experts to synthesize practical guidance for navigating these challenges across the AI pipeline. Using workshop discussions and experiences as a foundation, this position paper proposes practical solutions and complementary human-centric skill development to address these challenges: (1) educational resources that support opportunity-cost reasoning (time management) and methodological judgment (critical thinking), (2) communities of practice that build inclusive shared expertise (collaboration and mentorship), (3) effective visualizations that improve interpretability and strengthen transparency of model behavior and uncertainty (creativity and communication), and (4) computational resources that reduce implementation burden through shared data, extensible code, and accessible infrastructure (project management and problem-solving). Our workshop compiled resources, including science communication videos for five AI use cases and repositories for ecology-related AI models and communities of practice. Emphasizing human-centric skills and working in tandem with efforts to promote open science and computational literacy can make AI in ecology more rigorous, equitable, and ecologically relevant, advancing research and conservation.
The American bumble bee (Bombus pensylvanicus De Geer, 1773) is an ecologically important pollinator species that was once widespread throughout North America in grasslands, forest edges, and other open cover types. Bombus pensylvanicus appears to have had widespread population declines in recent years. While there has been an increased focus on determining conservation needs of B. pensylvanicus across its range, key information gaps remain, including its population status in various forest cover types, including areas managed for wood production. To better understand how this species uses forests, we compiled results from four studies sampling bee communities in managed pine (Pinus spp.) forests in Alabama, Georgia, and Mississippi, USA. Over two years, wild bees were passively sampled using blue vane and blue, yellow, and white pan traps (240 sampling plots; 80 stands × 3 plots per stand). The four studies captured 907 B. pensylvanicus individuals over 415 sampling days and, as compared to other captured bumble bee species, relative abundances of B. pensylvanicus reached 70
Species interactions can determine species’ population sizes, geographic ranges, evolutionary trajectories, and responses to environmental change. Yet, despite their importance to many fundamental and applied questions, information on species interactions is often lacking due to constraints in data collection. Billions of text comments that have been submitted by millions of citizen scientists around the world have the potential to fill these gaps. Comments can be used to identify biotic interactions using advanced large language models (LLMs), providing a novel source of interaction data that is unusually high in spatiotemporal coverage, breadth, and resolution. This novel approach opens new avenues to evaluate species interactions on a broader scale, and to characterize and conserve biodiversity under pressing global change. Highlights ### Competing Interest Statement The authors have declared no competing interest. David and Lucile Packard Foundation, https://ror.org/032atxq54 U.S. National Science Foundation, https://ror.org/021nxhr62, DEB-2129757, DEB-2224915, 230619 United States Department of Agriculture, https://ror.org/01na82s61, 25-PAF01509 Alfred P. Sloan Foundation, https://ror.org/052csg198
Domestic cats ( Felis catus ) pose major ecological and public health risks when allowed to roam outdoors, particularly in island ecosystems such as Hawai‘i, where they threaten endangered birds and marine mammals and transmit Toxoplasma gondii. While policies aimed at reducing cat impacts enjoy broad support, disagreements remain over preferred strategies, especially containment versus trap–neuter–return. This study examined Hawai‘i residents’ values, beliefs, and preferences toward cat management, and identified distinct audience segments to inform tailored interventions. An online survey of 924 residents measured ownership practices, intentions, perceived risks and benefits, self-efficacy, and support for management strategies targeting owned and unowned cats. Using Value–Belief–Norm theory and two-step cluster analysis, we identified three resident groups: an ecologically focused group (46%) characterized by strong environmental values, high confidence, and support for containment; a community-oriented group (33%) of older, long-term residents supportive in principle but with low follow-through; and a low-efficacy group (21%) with limited confidence, weak intentions, and resistance to restrictions. Findings reveal a persistent gap between support for veterinary responsibilities (e.g., sterilization, microchipping) and low adoption of containment behaviors, reflecting practical and cultural barriers. Comparison with studies in Hawai‘i, Australia, and the UK shows consistent divisions between owners and non-owners, and highlights confidence and feasibility as determinants of behavior. Effective management will require shifting from broad education campaigns toward targeted, value-based strategies that address each group’s motivations and barriers. These insights provide actionable guidance for policymakers and practitioners designing interventions that balance wildlife conservation with animal welfare in Hawai‘i and beyond.
