Tongli Wang
Associate Professor
Forest Sciences Centre 3008
2424 Main Mall
Vancouver, BC V6T 1Z4
Canada
Research Areas:
My research interests include the following areas:
1. Conservation genetics – The conservation of forest genetic resources is essential to maintain the capacity of forest trees to adapt to changing environments. In British Columbia (BC), the conservation of forest tree species is primarily achieved through in situ conservation in protected areas, complemented by ex situ conservation in seed storage. Dr. Wang is interested in the assessment of the conservation status to identify conservation gaps and prioritize conservation efforts. He has developed a web tool to interactively visualize the current conservation status of 42 native tree species in BC at climateBC.ca.
2. Development of scale-free climate models – High-quality climate data are essential to conducting the studies mentioned above. Although a large volume of climate data has become available in recent years, these datasets are in grid format at various spatial resolutions. The climate models that Dr. Wang (taking the lead) developed are scale-free and location-specific with higher accuracy. The models cover BC (Wang et al. 2006a), North America (Wang et al. 2016a), and Asia Pacific (WANG et al. 2017). These models integrate paleo, historical and future climate data into a single package, and generates a large number of biologically relevant climate variables. These models have over 2000 subscribers and cited for over 2000 times. They have become essential tools for climate and climate change related studies and applications. Wang et al. (2016a) is awarded as Highly Cited Paper (top 1%) in the field of geosciences. More information is available at: https://cfcg.forestry.ubc.ca/projects/climate-data/climatebcwna/
3. Ecological niche modelling – Climate change is resulting in a mismatch between the climate that trees are historically adapted to and the climate that trees will experience in the future. Such a mismatch may lead to maladaptation, which can compromise productivity and increase the vulnerability of forest ecosystems. Climate niche modelling is essential to tackle these problems. Dr. Wang is one of the pioneers in this field, and developed climate niche models for the Biogeoclimatic Ecosystem Classification (BEC) system and projected their shifts under future climates using a machine-learning algorithm (Hamann and Wang 2006, Wang et al. 2012a). These projections have been used to develop stocking standards and regional forest adaptation plans, and the climate-based seed-transfer system by the BC Ministry of Forests Land and Natural Resources Operations (MFLNRO) (O’Neill et al. 2017). His modeling expertise has also been applied to model some major forest species in the Asia Pacific (Wang et al. 2016b). He is in the process of developing climate niche models for all native species in BC. He is also in the process of developing an extended BEC system to cover neighboure provinces in the east and States in the south.
4. Ecological genetics – The importance of ecological genetics has never been so whelming due to the increasing concern of climate change. Local adaptation and among-population variation in relationship with environment, climate variables in particular, are the key areas of ecological genetics. Dr. Tongli Wang has extensive experience and expertise in this field. He has developed a method to generate anchor points (Wang et al. 2006b) and to consider other factors (O’Neill et al. 2007, O’Neill et al. 2008) to improve the traditional climate response functions. More importantly, he has developed a novel approach to integrate environmental (test site) and genetic (seed source) effects of climate into a single model, called the “universal response function” (URF) to predict the performance of a population from any seed source planted at any site (Wang et al. 2010). It allows the genetic and environmental effects to be quantified. This new approach makes the best use of the provenance trials and improves the model accuracy, and has advanced the modelling methodology in this field. This approach has recently been used by researchers in lodgepole pine (Wang et al. 2010), Douglas-fir (Chakraborty et al. 2015, Chakraborty et al. 2016, Chakraborty et al. 2018), white pine and black spruce (Yang et al. 2015).
5. Landscape genomics – With a rapid accumulation of genomic data for several important forest tree species, it has become possible to study the spatial genomic variation among populations and its association with climate variables. Dr. Wang’s expertise in ecological modelling, ecological genetics and genomics modeling (Holliday et al. 2012) make him well positioned in this new field. Results of landscape genomics will play a critical role to define populations (or seed management units) in combination with results from ecological genetics as mentioned above.
Selected Publications
Yue Yu , Sally N. Aitken , Loren H. Rieseberg and Tongli Wang (2022). Using landscape genomics to delineate seed and breeding zones for lodgepole pine New Phytologist 235
Gabriela Barragán, Tongli Wang, Jeanine M Rhemtulla (2022). Trees planted under a global restoration pledge have mixed futures under climate change Restoration Ecology
Zhengyang Ye, Gregory A O'Neill, Tongli Wang (2022). Climate data for field trials: onsite micro stations versus ClimateNA Canadian Journal of Forest Research 52:1028-1041
Bradley St. Clair, Bryce A Richardson, Nikolas Stevenson‐Molnar, Glenn T Howe, Andrew D Bower, Vicky J Erickson, Brendan Ward, Dominique Bachelet, Francis F Kilkenny, Tongli Wang (2022). Seedlot Selection Tool and Climate‐Smart Restoration Tool: Web‐based tools for sourcing seed adapted to future climates Ecosphere 13
Lei Feng, Jiejie Sun, Yousry A El-Kassaby, Xianyu Yang, Xiangni Tian, Tongli Wang (2022). Predicting Potential Habitat of a Plant Species with Small Populations under Climate Change: Ostryarehderiana Forests 13:
Mahony, C. R., Wang, T., Hamann, A., Cannon, A. J. (2022). A global climate model ensemble for downscaled monthly climate normals over North America. International Journal of Climatology
Carbeck, K., Wang, T., Reid, J. M., Arcese, P. (2022). Adaptation to climate change through seasonal migration revealed by climatic versus demographic niche models Global Change Biology
Sun, J., Jiao, W., Wang, Q., Wang, T., ... Wang, W (2021). Potential habitat and productivity loss of Populus deltoides industrial forest plantations due to global warming Forest Ecology and Management 496
T. Wang a, P. Smets, C. Chourmouzis, S.N. Aitken, D. Kolotelo (2020). Conservation status of native tree species in British Columbia Global Ecology and Conservation 24
L. Feng, J. Sun, Y. Shi, G. Wang, T. Wang (2020). Predicting Suitable Habitats of Camptotheca acuminata Considering Both Climatic and Soil Variables Forests 11
M. Marchi, D. Castellanos-Acuña, A. Hamann, T. Wang, D. Ray, A. Menze (2020). ClimateEU, scale-free climate normals, historical time series, and future projections for Europe Scientific Data 7
H. Lin, C. Li, T. Chen, C. Hsieh, G. Wang, T. Wang, J. Hu (2020). Climate‐based approach for modeling the distribution of montane forest vegetation in Taiwan Applied Vegetation Science 23
Mahony CR, MacLachlan IR, Lind BM, Yoder JB, Wang T, Aitken SN (2020). Evaluating genomic data for management of local adaptation in a changing climate: A lodgepole pine case study Evolutionary Applications 13: 116-131.
Hu, X.-G., J.-F. Mao, Y. A. El-Kassaby, K.-H. Jia, S.-Q. Jiao, S.-S. Zhou, Y. Li, N. C. Coops, and T. Wang (2019). Local Adaptation and Response of Platycladus orientalis (L.) Franco Populations to Climate Change Forests 10/622
Guo, Y., J. Guo, X. Shen, G. Wang, and T. Wang (2019). Predicting the Bioclimatic Habitat Suitability of Ginkgo biloba L. in China with Field-Test Validations Forests 10:705
Jia, K.-H., W. Zhao, P. A. Maier, X.-G. Hu, Y. Jin, S. Zhou, S. Jiao, Y.A. El-Kassaby, T. Wang, et al., (2019). Landscape genomics predicts climate change-related genetic offset for the widespread Platycladus orientalis (Cupressaceae) Evolutionary Applications
Y Guo, Y Lu, YA El-Kassaby, L Feng, G Wang, T Wang (2019). Predicting growth and habitat responses of Ginkgo biloba L. to climate change Ann. For. Sci. 76:101
Lin, H. Y., J. M. Hu, T. Y. Chen, C. F. Hsieh, G. Wang, and T. Wang (2018). A dynamic downscaling approach to generate scale-free regional climate data in Taiwan Taiwania
Chakraborty, D., S. Schueler, M. J. Lexer, and T. Wang (2018). Genetic trials improve the transfer of Douglas-fir distribution models across continents Ecography
El-Kassaby, Y. A., Q. Wang, T. Wang, B. Ratcliffe, Q.-X. Bi, Z. Wang, J.-F. Mao, and W. Guan (2018). Concept for gene conservation strategy for the endangered Chinese yellowhorn, Xanthoceras sorbifolium, based on simulation of pairwise kinship coefficients Forest Ecology and Management
MacLachlan IR Wang T Hamann A Smets P Aitken, Sally N. (2017). Selective breeding of lodgepole pine increases growth and maintains climatic adaptation Forest Ecology and Management 391:404-416
Mahony CR, Cannon AJ Wang T Aitken SN (2017). A closer look at novel climates: new methods and insights at continental to landscape scales Global Change Biology 23:3934-3955.
Carroll, Carlos Roberts, David R. Michalak, Julia L. Lawler, Joshua J. Nielsen, Scott E. Stralberg, Diana Hamann, Andreas McRae, Brad H. Wang, Tongli (2017). Scale-dependent complementarity of climatic velocity and environmental diversity for identifying priority areas for conservation under climate change Global Change Biology
WANG, T., WANG, G., INNES, J. L., SEELY, B., CHEN,B. (2017). ClimateAP: an application for dynamic local downscaling of historical and future climate data in Asia Pacific Front. Agr. Sci. Eng.
Hu, X., Wang, T., Liu, S., Jiao, S., Jia, K., Zhou, S.,Jin, Y., Li, Y., El-Kassaby, Y.A., Mao, J. (2017). Predicting Future Seed Sourcing of Platycladus orientalis (L.) for Future Climates Using Climate Niche Models Forests
Yeaman S, Hodgins KA, Lotterhos KE Suren H, Nadeau S, Degner JC, Nurkowski KA, Smets P, Wang T, Gray LK, Liepe KJ, Hamann A, Holliday JA, Whitlock MC, Rieseberg LH, Aitken SN (2016). Convergent local adaptation to climate in distantly related conifers Science, 353: 1431-1433
Haijun Kang, Brad Seely, Guangyu Wang, John Innes, Dexiang Zheng, Pingliu Chen, Tongli Wang, Qinglin Li (2016). Evaluating management tradeoffs between economic fiber production and other ecosystem services in a Chinese-fir dominated forest plantation in Fujian Province Science of the Total Environment 557–558 (2016) 80–90
Wang, G., Wang, T., Kang, H., Mang, S., Riehl, B., Seely, B., Liu, S., Guo, F., Li, Q. and Innes, J.L. (2016). Adaptation of Asia-Pacific forests to climate change J. For. Res. (2016) 27:469-488
Tongli Wang, Andreas Hamann, Dave Spittlehouse, Carlos Carroll (2016). Locally Downscaled and Spatially Customizable Climate Data for Historical and Future Periods for North America PLoS ONE 11(6): e0156720
Y. Liu, T. Wang, and Y. A. El-Kassaby (2016). Contributions of dynamic environmental signals during life-cycle transitions to early life-history traits in lodgepole pine (Pinus contorta Dougl.) Biogeosciences 13, 1–14 doi:10.5194/bgd-12-14105-2015
Tongli Wang, Guangyu Wang, John Innes, Craig Nitschke, Haijun Kang (2016). Climatic niche models and their consensus projections for future climates for four major forest tree species in the Asia–Pacific region Forest Ecology and Management 360 (2016) 357–366
Lei Zhang, Shirong Liu, Pengsen Sun, Tongli Wang, Guangyu Wang, Linlin Wang, Xudong Zhang (2016). Using DEM to predict Abies faxoniana and Quercus aquifolioides distributions in the upstream catchment basin of the Min River in southwest China Ecological Indicators 69 (2016) 91–99
Debojyoti Chakraborty, Tongli Wang, Konrad Andre, Monika Konnert, Manfred J. Lexer, Christoph Matulla, Silvio Schueler (2015). Selecting Populations for Non-Analogous Climate Conditions Using Universal Response Functions: The Case of Douglas-Fir in Central Europe PLoS ONE 10(8): e0136357. doi:10.1371/journal.pone.0136357
Lei Zhang, Shirong Liu, Pengsen Sun, Tongli Wang, Guangyu Wang, Xudong Zhang, Linlin Wang (2015). Consensus Forecasting of Species Distributions: The Effects of Niche Model Performance and Niche Properties PLoS ONE 10(3): e0120056. doi:10.1371/journal.pone.0120056
Lu, Y., N.C. Coops, T. Wang and G. Wang (2015). Comparing Stem Volume Predictions of Coastal Douglas-Fir Stands in British Columbia Using a Simple Physiological Model and LiDAR FOREST SCIENCE 61(3):586–596
Lu, Y., Coops, N.C., Wang, T., Wang, G., (2015). A process-based approach to estimate Chinese Fir (Cunninghamia lanceolata) Distribution and productivity in Southern China under climate change Forests 6(2) 360-379
Amanda R. De La Torre, Tongli Wang, Barry Jaquish and Sally N. Aitken (2014). Adaptation and exogenous selection in a Picea glauca 9 Picea engelmannii hybrid zone: implications for forest management under climate change New Phytologist 201: 687–699
Tongli Wang (2013). Projecting future distributions of ecosystem climate niches in British Columbia Journal of Ecosystems and Management 13(2):1–3
Christopher J. Fettig, Mary L. Reid, Barbara J. Bentz, Sanna Sevanto, David L. Spittlehouse, and Tongli Wang (2013). Changing Climates, Changing Forests: A Western North American Perspective Journal of Forestry 111, 214-228
Tongli Wang, Andreas Hamann, David l. Spittlehouse and Trevor q. Murdock (2012). ClimateWNA—High-Resolution Spatial Climate Data for Western North America Journal of Applied Meteorology and Climatology, 51: 16-29
Jason A. Holliday, Tongli Wang and Sally Aitken (2012). Predicting Adaptive Phenotypes From Multilocus Genotypes in Sitka Spruce (Picea sitchensis) Using Random Forest G3: Genes, Genomes, Genetics , 2, 1085-1093
Wang, T., Campbell, E.M., O'Neill, G.A., Aitken, S.N (2012). Projecting future distributions of ecosystem climate niches: uncertainties and management applications Forest Ecology and Management 279, 128-140
Cortini, F., Comeau, P.G., Wang, T., Hibbs, D.E., Bluhm, A (2012). Climate effects on red alder growth in the Pacific Northwest of North America Forest Ecology and Management 277, 98-106
Coops, N.C., R.H. Waring, C. Beier and T. Wang (2011). Modeling the occurrence of fifteen coniferous tree species throughout the Pacific Northwest of North America using a hybrid approach of a generic process-based growth model and decision tree analysis Applied Vegetation Science, 14: 402–414
Wang, T., G.A. O'Neill and S.N. Aitken (2010). Integrating environmental and genetic effects to predict responses of tree populations to climate Ecological Applications 20: 153-163.
Schroeder, T.A., Hamann, A., Coops, N.C., Wang, T (2009). Occurrence and dominance of six Pacific Northwest conifer species Journal of Vegetation Science DOI:
Mbogga, M., A. Hamann, and T. Wang (2009). Historical and projected climate data for natural resource management in western Canada Agricultural and Forest Meteorology 149:881-890
O'Neill, G.; Hamann, A.; Wang, T (2008). Accounting for population variation improves estimates of climate change impacts on species' growth and distribution Journal of Applied Ecology 45:1040-1049
Aitken, S. N., S. Yeaman, J. A. Holliday, T. Wang, and S. Curtis-McLane (2008). Adaptation, migration or extirpation: Climate change outcomes for tree populations Evolutionary Applications, 1:95-111
O’Neill, G. A., N. Gordon, T. Wang, and P. K. Ottb (2007). Growth response functions improved by accounting for non-climatic site effects Canadian Journal of Forest Research, 37:2724-2730
Wang, T., A. Hamann, A. Yanchuk, G. A. O'Neill, and S. N. Aitken (2006). Use of response functions in selecting lodgepole pine populations for future climate Global Change Biology. 12:2404–2416