
Forest Biodiversity Responses to Changing Climate Across the Americas: Synthesis of Long-term Ecological Data
a series of workshops in 2024 and 2025 by
David Luther (GMU) Lynn Christenson (Vasser) & Nina Laney (USFS)
Funded by NSF DEB # 2227314
Workshop Summary
Forest communities are changing rapidly, but it has been difficult to determine if those changes are attributable to just climate or if other changes, like habitat degradation or pollution are also partially responsible. Many studies follow forest community change over short periods of time, making it difficult to identify drivers of change. Long-term research, often spanning decades of data collection at specific locations, such as Long-term Ecological Research sites, collect local information about different species, individuals and environmental conditions, providing unique opportunities to uncover both patterns and drivers of change. These workshops brought together ecologists, data managers, and statisticians to harmonize data from long-term research sites in forest ecosystems, including Long-term Ecological Research sites (in the US and abroad), National Ecological Observation Network, and National Park Service biodiversity monitoring sites to assess the long-term effects of climate change on forest communities across the Americas that have not been impacted by habitat loss. Results will lead to a strong research network of ecologists that study a broad range of taxonomic groups focused on understanding the long-term changes in forest ecosystems both at local and continental scales.
The explicitly inter-disciplinary nature of the workshop will foster linkages and collaborations that will result in alleviating field sampling and statistical barriers for scaling the information from individual long-term ecological research sites to the macrosystem scale. Such barriers still limit researchers from broadening the scale and scope of their research. The two-day workshop will harmonize data sets from different locations as well as spatial and temporal scales to investigate the effects of climate change on biodiversity in forest ecosystems across the Americas. The resulting synthesis research paper will encompass how forest biodiversity, in locations not affected by habitat destruction, across the Americas has changed over the past ~ 40 years and the role of climate in driving those changes. This workshop will bring together experts in the fields of ecology, data management, statistics and climate change with the overall goal of integrating large data sets that represent both spatial and temporal scales of biodiversity across the Americas under changing climate conditions of the past 40-50 years. The data sets generated during the workshop will be made available through the Environmental Data Initiative, including approaches used to harmonize data. Finally, this workshop provides ongoing professional development for all participants, engaging each in unfamiliar techniques that will support their own future work as well as creating a new network of collaborators.
Contact David Luther dluther@gmu.edu for inquiries.
PRELIMINARY RESULTS
Over the past 20 years bird community data
from intact forests show the following trends
Temperate Broadleaf Forests show stable or
slightly homogenizing community structure
Tropical Forests show increased nestedness
and reduced species turnover, but high
individual site level variation
Temperate Conifer Forests show increasing
evenness and nestedness over time.
NEXT STEPS
Align climate, topography, landuse history and
landscape metrics with species diversity at
each site to investigate their influence on
community composition


Amazon.IA
Actionable Biodiversity Intelligence for the Amazon
Amazon.ia is an ambitious multi-partner initiative to produce timely, actionable intelligence on biodiversity, driving effective conservation and restoration across the Amazon. Fusing satellite and ground sensors in a biome-wide network, the initiative leverages robust, AI-powered techniques to answer Amazonian decision-makers’ most critical conservation questions—accurately, cost-effectively, and in near-real time. With more than a dozen partners, the initiative is developing core data infrastructure and analytical capabilities, testing new dynamic, integrated models, and generating meaningful insights to support local-to-regional decision-making needs. Insights are co-developed with local communities and decision-makers, including change alerts, biodiversity status and ecosystem condition, evidence of protected area effectiveness, and proof of ecosystem recovery.
Why Now?
Recent advances in technology have created opportunities to understand nature at unprecedented speed and scale. Earth observation systems, camera traps, bioacoustic recorders, environmental DNA (eDNA), and autonomous edge-computing hardware can generate more information about ecosystems than ever before. Improved connectivity and cloud computing make it possible to collect and analyze data from even the most remote locations in near real time.
Amazonian organizations have been leading the deployment of these technologies across the region. With new AI techniques and solutions, we have the capacity and opportunity to scale. By combining satellite observations with data collected on the ground, AI can reveal patterns, trends and changes in ecosystems and wildlife that would be impossible to detect from any single data source alone.
What Next?
Amazon.ia is launching in 2026 with founding support from the Bezos Earth Fund. It brings together a diverse network of partners spanning Amazonian research institutions, conservation organizations, leading universities, tech companies, national environmental institutes, and global data and technology platforms. Together, these partners are building the locally led infrastructure, scientific capacity, decision support and technological innovation needed to generate actionable biodiversity intelligence across the Amazon. They include:
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Andes Amazon Fund
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Arizona State University (Asner Lab)
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Associação de Levantamento Florestal do Amazonas (ALFA)
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Bezos Earth Fund
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Conservación Amazónica (ACCA)
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Cornell Lab of Ornithology
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Cornell University (Davis Lab)
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George Mason University (Luther Lab)
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Instituto Nacional de Pesquisas da Amazônia (INPA)
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Instituto de Desenvolvimento Sustentável Mamirauá
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Instituto Humboldt
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International Barcode of Life (iBOL)
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Massachusetts Institute of Technology (Beery Lab)
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Microsoft AI for Good Lab
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Planet Labs PBC
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Smithsonian ForestGEO
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Tiputini Biodiversity Station
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Universidad San Francisco de Quito (Rivas Torres Lab)
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Universitat Politècnica de Catalunya
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University of Guelph, Centre for Biodiversity Genomics
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Wildlife Conservation Society - Bolivia
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Wildlife Insights
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WildMon
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World Resources Institute
Linking remote animal detection and movement data with macrosystem environmental datasets and networks
2016-2018 at the Smithsonian Mason School of Conservation
Front Royal, Virginia
Funded by NSF EAGER # 1450318 to
David Luther and Bill McShea in 2016
Workshop Summary
Technological advances in remote data collection of animal presence and movement have allowed the accumulation of large quantities of location data of individuals or species as well as macrosystem-level environmental data. Examples of technology improving the specificity of animal data are acoustic recordings, camera-traps, radiotelemetry, and geolocators. In addition, remote sensing from satellites and aircraft, reanalysis models and observation networks are providing large quantities of environmental data. These new technologies are allowing animal ecologists to collect distribution and/or fine-scaled movement data on more suites of organisms at broader scales than previously imagined. These advances in technology, along with increased connectivity over the web, have allowed a broader involvement of the public in collecting animal or environmental data. The struggle in many cases is to link the animal-observations information being collected by citizens, and local groups, as well as national and international agencies, to relevant large-scale environmental datasets.
The explicitly inter-disciplinary nature of the workshop proposed here will foster linkages and collaborations that can result in alleviating technical barriers for scaling the information from the animal observation to the macrosystem scale. Such barriers still limit researchers from broadening the scale and scope of their research. We propose to hold a two-day workshop that focuses on how new technologies and capabilities being used to investigate the distribution and movement of animals can be linked to environmental state, flux, and change at the landscape scale. We will bring together experts in the field of remote sensing of the environment and animal detection techniques with the goal of integrating the various technologies and lay the foundation for a review paper on the potential of these combined techniques to answer questions in the fields of ecology and conservation biology.
The workshop aims to address the following questions:
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What is the current state of linking broad-scale environmental data with dynamic animal distributions and movements?
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Is it possible to use current technology and capabilities to monitor animals at broad landscape, regional, or continental scales?
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How can fine-scale individual movement data inform coarser species’ detection efforts?
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What role can volunteer networks play in data acquisition of either animal or environmental data?
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What are the guiding principles and pitfalls in upscaling/downscaling movement and environmental data to link these available environmental data from satellites, LiDAR, weather stations, reanalysis models, and other remote sensing platforms to animal movement data in ways to answer important ecological questions?
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