Nature paper offers global map to understand changing forests

An international collaboration of hundreds of scientists – led in part by the Forest Advanced Computing and Artificial Intelligence(FACAI) Laboratory in Purdue’s Department of Forestry and Natural Resources – has developed the world’s first global map of tree symbioses. The map is key to understanding how forests are changing and the role climate plays in these shifts.

The findings, reported today in the journal Nature, come from the Global Forest Biodiversity Initiative (GFBI), a consortium of forest scientists and practitioners of which the FACAI Lab is a key hub and global center. Jingjing Liang, a Purdue University assistant professor of quantitative forest ecology, is co-supervisor of the FACAI Lab, coordinator and co-founder of the GFBI and co-lead author of the paper. Mo Zhou, a Purdue assistant professor of forest economics and management, is a senior author of the paper, co-supervisor of the FACAI lab and lead economist of the GFBI.

Purdue’s FACAI lab employs artificial intelligence and machine learning to study global, regional and local forest resource management and biodiversity conservation. For this research, FACAI compiled species abundance data from 55 million tree records in 1.2 million forest sample plots spanning 110 countries. The organization of the data was integral to developing the global map.

“The map and underlying global forest inventory database will serve as the foundation for research on the environmental impacts of forest changes, biological conservation and forest management,” Liang said.

The map identifies the types of mycorrhizal fungi associated with trees in a particular forest. These fungi attach to tree roots, extending a tree’s ability to reach water and nutrients while the tree provides carbon necessary for the fungi’s survival. The two most common types of mycorrhizae are arbuscular, which grow inside the tissues of tree roots and are associated with tree species such as maple, ash and yellow poplar, and ectomycorrhizal, which live on the outside of roots and are associated with tree species such as pine, oak, hickory and beech.

Those associations are important because the mycorrhizae affects the trees’ ability to access nutrients, sequester carbon and withstand the effects of climate change.

“Managing forests for climate change mitigation and sustainable development, therefore, should go well beyond managing only trees,” Zhou said. 

The authors found that climate is the most significant factor affecting the distribution of mycorrhizae. A warming climate is reducing the abundance of ectomycorrhizal tree species by as much as 10 percent. That change is altering forests’ ecological and economic footprints, especially along the boreal-temperate ecotone, the border areas between colder and warmer forest. Losses to ectomycorrhizal species have implications for climate change since these fungi increase the amount of carbon stored in soil.

“Knowing the species composition in the forested area across the world is an important start,” Liang said. “There are many fundamental and socioeconomic questions we can answer now with GFBI data and cutting-edge machine learning techniques.”

The FACAI lab is currently developing collaborations to explore questions about ecology and economics, including self-learning forest models, innovative approaches to biodiversity valuation, locating unknown forest resources and space exploration.

The work aligns with Purdue’s Giant Leaps celebration, acknowledging the university’s global advancements made in health, space, artificial intelligence and sustainability as part of Purdue’s 150th anniversary. Those are the four themes of the yearlong celebration’s Ideas Festival, designed to showcase Purdue as an intellectual center solving real-world issues.

Brian S. Steidinger, a postdoctoral research fellow at Stanford University, and Thomas Ward Crowther, an assistant professor at ETH Zurich, are co-lead authors of the Nature paper with Liang. Sergio de Miguel, an assistant profession and principal investigator of the GFBI Hub at University of Lleida, Spain, and Xiuhai Zhao and Chunyu Zhang, professors at Beijing Forestry University, are among the senior collaborators of this paper.

Data from this research can be downloaded at https://ag.purdue.edu/facai/data/

For full details of this paper, visit here.

Writer: Brian Wallheimer, 765-532-0233, bwallhei@purdue.edu

Sources: Jingjing Liang, 765-496-0254, liang292@purdue.edu

Mo Zhou, 765-494-3098, mozhou@purdue.edu

Forest Scholars Worldwide Team Up For Biodiversity Research

Loss of biodiversity has long been recognized as detrimental for nature, for nature’s sake. Now a team of scholars from 90 institutions in 44 countries show that it also provides enormous economic benefits. The team, formally known as the Global Forest Biodiversity Initiative (GFBI), consolidated field-based forest inventory data from 777,126 permanent plots across the world, and discovered that for forests in every part of the world, those with many tree species are more productive than nearby forests with few. 

The team then estimated that the economic value of biodiversity in maintaining commercial forest productivity alone is worth USD$166–490 billion per year. This benefit- only one of many such benefits of biodiversity- is more than 20 times greater that what is spent each year on global conservation. This finding highlights the need for a worldwide re-assessment of biodiversity values, forest management strategies, and conservation priorities. 

The research, published in the Oct. 14, 2016 issue of Science, marks the first major accomplishment of FACAI and GFBI team.

Prof. Mo Zhou

Google Scholar

  • Curriculum Vitae
  • Email: mozhou@purdue.edu
  • Tel: 001-765-494-3098
  • Department of Forestry and Natural Resources, 715 W. State Street, West Lafayette, IN 47907

Education

  • Beijing Forestry University, Beijing China,  MIS, B.S. 1998
  • Technical University of Munich, Munich Germany, Forestry, M.S. 2000
  • University of Wisconsin-Madison, Madison, WI, Forestry, Ph.D. 2005

Professional experience

  • 2018 – present Assistant Professor of Forest Economics and Management, Purdue University
  • 2011 – 2018   Assistant Professor of Forest Economics, West Virginia University
  • 2008 – 2011   Assistant Professor of Economics, School of Management, University of Alaska
  • 2005 – 2007  Research Associate, Dept. of Forest Ecology and Management, UW-Madison

Editorship

  • Associate Editor of Canadian Journal of Forest Research, 2015-present
  • Associate Editor of Forest Ecosystems, 2013-present

Featured Publications

Zhou, M*. and J. Buongiorno, J. 2019. Optimal forest management under financial risk aversion with discounted Markov decision process models. Canadian Journal of Forest Research. (In press)

Zhou, M*. 2017. “Valuing Environmental Amenities through Inverse Optimization: Theory and Case Study”. Journal of Environmental Economics and Management 83: 217 – 230.

Zhou, M.* 2015. “Adapting Forest Management to Climate Policy Uncertainty: a Conceptual Framework”. Forest Policy and Economics 59, 66-74.

Zhou, M. *and J. Buongiorno. 2011. Effects of Stochastic Interest Rates in Decision Making under Risk: a Markov Decision Process Model for Forest Management. Forest Policy and Economics13: 402-410.

Zhou, M. and Buongiorno, J., 2006. Space-time modeling of timber prices. Journal of agricultural and resource economics, pp.40-56.

Prof. Jingjing Liang

Link to Google Scholar

Link to ResearchGate

Link to Facebook

Curriculum vitae, last updated March 2019

  • Email: jjliang@purdue.edu
  • Tel: 001-765-496-0254
  • Mailing address: Department of Forestry and Natural Resources, 715 W. State Street, West Lafayette, IN 47907

Dr. Liang is an SAF certified forester and enjoys having a boots-on-the-ground experience highlighted by one growing season that he measured 15,000 trees in two days, once every two weeks. One of the many highpoints of Dr. Liang’s career thus far was when he was the leading author of research articles published in Science, Nature, and Proceedings of the National Academy of Sciences of the United States of America (PNAS).

Dr. Liang’s research is interested in global biodiversity patterns and associated environmental and anthropogenic drivers, and he approaches this by utilizing machine learning and big data to help unravel the pressing issues facing the field today. While he’s working on answering today’s tough questions, Dr. Liang believes that the future success of the field will depend heavily on international collaborations and leveraging artificial intelligence to produce high impact research.

When Dr. Liang isn’t busy teaching his Big Data in Forest Research course or training machine learning algorithms, he enjoys going rock-climbing and spending time with his wife who is also a rock-climbing enthusiast and FNR faculty member, Dr. Mo Zhou. Dr. Liang is feeling right at home on the Purdue campus surrounded by our population of ginkgo trees, which he has a special affection for them due to them being incredibly unique and being living fossils.

Education

  • 2005, Ph.D. (Forestry), University of Wisconsin-Madison
  • 2001, B.S. (Ecology- Environmental Sciences), Peking University

Professional experience

  • 2018 – present Assistant Professor of Quantitative Forest Ecology, Department of Forestry and Natural Resources, Purdue University
  • 2017– 2018 Associate Professor of Forest Ecology, School of Natural Resources, West Virginia University
  • 2011—2017 Assistant Professor of Forest Ecology, School of Natural Resources, West Virginia University
  • 2007—2011 Assistant Professor of Forest Biometrics and Management, School of Natural Resources and Agricultural Sciences, University of Alaska Fairbanks
  • 2006—2007 Post-doctoral Biometrician
    Forest Sciences Laboratory, U.S. Department of Agriculture, Rocky Mountain Research Station
  • 2005—2006 Research Associate
    Department of Forest and Wildlife Ecology, University of Wisconsin-Madison
  • 2001—2005 Research Assistant
    Department of Forest and Wildlife Ecology, University of Wisconsin-Madison

Editorship

  • Since 2019, Senior member of the Editorial Team, Scientific Data
  • Since 2018, Senior member of the Editorial Team, Forest Ecosystems

Featured Publications

(Co-first author) Steidinger, B. S., T. W. Crowther, J. Liang, M. E. Van Nuland, G. D. A. Werner, P. B. Reich, G. Nabuurs, S. de-Miguel, M. Zhou, N. Picard, B. Herault, X. Zhao, C. Zhang, D. Routh, K. G. Peay, and GFBI consortium. 2019. Climatic controls of decomposition drive the global biogeography of forest-tree symbioses. Nature 569:404-408.

Details and downloads


Liang, J, T. W. Crowther, N. Picard, S. Wiser, M. Zhou, G. Alberti, E.-D. Schulze, A. D. McGuire, F. Bozzato, H. Pretzsch, S. de-Miguel, A. Paquette, B. Hérault, M. Scherer-Lorenzen, C. B. Barrett, H. B. Glick, G. M. Hengeveld, G.-J. Nabuurs, S. Pfautsch, H. Viana, A. C. Vibrans, C. Ammer, P. Schall, D. Verbyla, N. Tchebakova, M. Fischer, J. V. Watson, H. Y. H. Chen, X. Lei, M.-J. Schelhaas, H. Lu, D. Gianelle, E. I. Parfenova, C. Salas, E. Lee, B. Lee, H. S. Kim, H. Bruelheide, D. A. Coomes, D. Piotto, T. Sunderland, B. Schmid, S. Gourlet-Fleury, B. Sonké, R. Tavani, J. Zhu, S. Brandl, J. Vayreda, F. Kitahara, E. B. Searle, V. J. Neldner, M. R. Ngugi, C. Baraloto, L. Frizzera, R. Bałazy, J. Oleksyn, T. Zawiła-Niedźwiecki, O. Bouriaud, F. Bussotti, L. Finér, B. Jaroszewicz, T. Jucker, F. Valladares, A. M. Jagodzinski, P. L. Peri, C. Gonmadje, W. Marthy, T. O’Brien, E. H. Martin, A. R. Marshall, F. Rovero, R. Bitariho, P. A. Niklaus, P. Alvarez-Loayza, N. Chamuya, R. Valencia, F. Mortier, V. Wortel, N. L. Engone-Obiang, L. V. Ferreira, D. E. Odeke, R. M. Vasquez, S. L. Lewis, and P. B. Reich. 2016. Positive biodiversity-productivity relationship predominant in global forests. Science 354.
Details and downloads


Liang J, Zhou M, Tobin PC, McGuire AD, & Reich PB (2015) Biodiversity influences plant productivity through niche-efficiency. PNAS 112(18):5738-5743.
Details and Downloads


​Liang, J. (2012) Mapping large-scale forest dynamics: a geospatial approach. Landscape Ecology 27(8): 1091-1108.
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