What
Data4Nature is a UBC Research Excellence Cluster. This cluster brings together expertise at the interface of ecology, data science, synthesis statistics and data governance to develop new methods and provide local to global leadership in the burgeoning field of environmental data science.
Why
The world’s environment is changing at an ever-accelerating pace. Governments have committed to ambitious conservation goals, such as the Kunming-Montreal Global Biodiversity Framework and Canada’s “30×30” target to protect 30% of its area by 2030. However, to track progress towards these goals, we need large-scale and near-real-time monitoring of species and ecosystems. Although this level of monitoring has not been possible in the past, rapid technological advancements mean that we are now at the cusp of achieving this. This is catalyzed by the development of monitoring technology, artificial intelligence, and synthesis statistics, coupled with large amounts of community-sourced data. While such advances hold enormous promise, realizing this promise requires equitable access for all sectors of society, tempered by respect for data sovereignty, especially in the context of Indigenous reconciliation.
How
The Data4Nature team applies data-intensive computational approaches and innovative community-based monitoring networks to:
- Accelerate the acquisition or integration of data.
- Model trends and scenarios.
- Increase data accessibility while respecting data sovereignty.
Challenges
We focus on three key challenges:
The data acquisition challenge is to quickly and accurately collect large amounts of data on species and ecosystems. We are now approaching the point where near real-time monitoring of species, and even individual organisms, is possible. This revolution includes:
- Technologies such as camera traps, drones, tracking tags and acoustic recordings.
- Genetic methods like eDNA and metabarcoding.
- Analytical methods using artificial intelligence.
- Digital resources like large genomic libraries, satellite and LIDAR imagery.
- Community science platforms such as iNaturalist or eBird.
The data integration challenge is to create sustainable and equitable ways for the many cross-sector monitoring programs already in existence to be synthesized and made accessible within larger networks. Environmental data is often hidden or inaccessible to those who need it most to make decisions. To assist countries in monitoring progress towards GBF goals, the United Nations’ Group on Earth Observatories has developed a system of Biodiversity Observation Networks, or BONs, to monitor species, detect and attribute change, and build scenarios that support policy and action. Following the lead of 20 countries, Canada is in the planning stages for a national BON composed of regional nodes operating outside of government. This provides the Data4Nature team with a unique opportunity to lead the creation of a regional node. We have already started laying the groundwork for an inclusive “BC Biodiversity Network” (BCBN) bringing together provincial agencies, First Nations, NGOs, academics and community organizations.
The data modelling challenge is to develop new ways to analyse large quantities of heterogeneous environmental data to aid decision making through attributing change and building management scenarios. The co-design of such analyses with knowledge users will ensure that the end product is actually useful. Such cross-sectoral approach has been effective in programs like the Intergovernmental Panel on Climate Change and Brazil’s BIOTA. The nascent BCBN is envisioned as having this role, enabling community and policy-relevant data compilation, analysis and interpretation.
Collective expertise
The Data4Nature team covers three UBC faculties, seven departments and two institutes, and our study systems are as diverse as forests, oceans, tundra, tropics, cities and farms. However, what unites us is a common vision for how data-intensive approaches can accelerate our ability to understand and manage the environment.
New technologies.
Many team members are applying AI approaches to species identification from images and acoustic recordings. Such AI methods are particularly powerful when combined with large biodiversity observation networks, from camera trapping to urban wildlife to citizen science. We also scale up traditional field observations by coupling these with drone imagery, satellite data, and bioclimatic models. We use remotely sensed data to analyze animal movement with specialized statistics or build large-scale models of ecosystem services. Other team members use eDNA methods to indirectly monitor insect populations, invasive agricultural pests, or marine organisms.
Data4Nature team members play key roles in national and international initiatives in environmental data science, such as:
- Analytical networks such as AI for Biodiversity Change Global Center and Collaborative Research Team on Hidden Markov Models for Biologging.
- Canadian data synthesis and training organizations, including the Canadian Institute of Ecology and Evolution and the Living Data Project.
- Arctic research networks such as the International Tundra Experiment and High Latitude Drone Ecology Network.
- Monitoring networks like the National Earth Observatory Network, WildCAM camera trapping network, and Urban Wildlife Information Network.
- Agricultural initiatives such as the BC Agricultural Climate Action Research Network, and the Perennial Plant Restoration for Carbon Sequestration in Canadian Agricultural Landscapes project.
Collaborations
Essential to the Data4Nature mandate are the principles of justice, equity, reconciliation and inclusion in all aspects of our work. Members of Data4Nature bring expertise on Indigenous data sovereignty and the development of ethical data governance toolkits, experience co-developing research with Indigenous partners or those in the Global South, and innovative programs to increase representation in research through UBC and national internship programs.
Collaborators and partners are integral to many proposed activities. Confirmed collaborators include: BC Biodiversity Project, Blitz-the-Gap, BUDR, CIEE, DataStream, LDP, Microsoft AI for Earth, MILA Quebec Artificial Intelligence Institute, PERCS, UBC Farm, UBC Campus + Community Planning, and Universidade Federal do Rio de Janeiro. We will also invite partners from provincial and federal ministries, environmental non-governmental organizations, and Indigenous organizations.
