References

• Asner, G.P., and Mascaro, J. 2014. “Mapping tropical forest carbon: Calibrating plot estimates to a simple LiDAR Metric.” Remote Sensing of Environment, Vol. 140: pp. 614–624. doi:10.1016/j.rse.2013.09.023.
   Web of Science ®Google Scholar
• Asner, G.P., Mascaro, J., Muller-Landau, H.C., Vieilledent, G., Vaudry, R., Rasamoelina, M., Hall, J.S., and van Breugel, M. 2012. “A universal airborne LiDAR approach for tropical forest carbon mapping.” Oecologia, Vol. 168(No. 4): pp. 1147–1160. doi:10.1007/s00442-011-2165-z.
   PubMed Web of Science ®Google Scholar
• Baldwin, K., Allen, L., Basquill, S., Chapman, K., Downing, D., Flynn, N., and MacKenzie, W. 2018. “Vegetation Zones of Canada: A Biogeoclimatic Perspective.” Sault Ste. Marie, ON: Natural Resources Canada, Canadian Forest Service.
   Google Scholar
• Bergeron, Y., Chen, H.Y.H., Kenkel, N.C., Leduc, A.L., and Macdonald, S.E. 2014. “Boreal mixedwood stand dynamics: ecological processes underlying multiple pathways.” The Forestry Chronicle, Vol. 90(No. 02): pp. 202–213. doi:10.5558/tfc2014-039.
   Google Scholar
• Bergeron, Y., and Fenton, N.J. 2012. “Boreal forests of eastern Canada revisited: Old growth, nonfire disturbances, forest succession, and biodiversity.” Botany, Vol. 90(No. 6): pp. 509–523. doi:10.1139/b2012-034.
   Google Scholar
• Bergeron, Y., Leduc, A., Morin, H., and Joyal, H. 1995. “Balsam fir mortality following the last spruce budworm outbreak in northwestern Quebec.” Canadian Journal of Forest Research, Vol. 25(No. 8): pp. 1375–1384. doi:10.1139/x95-150.
   Web of Science ®Google Scholar
• Bivand, R., Keitt, T., Rowlingson, B., Pebesma, E., Sumner, M., Hijmans, R., Rouault, E., Warmerdam, F., Ooms, J., and Rundel, C. 2019. “R package rgdal: Bindings for the ‘geospatial data abstraction library’”. https://cran.r-project.org/web/packages/rgdal/rgdal.pdf
   Google Scholar
• Bolton, D.K., Tompalski, P., Coops, N.C., White, J.C., Wulder, M.A., Hermosilla, T., Queinnec, M., Luther, J.E., van Lier, O., Fournier, R.A., Woods, M., Treitz, P., van Ewijk, K., Graham, G., and Quist, L. 2020. “Optimizing Landsat time series length for regional mapping of lidar-derived forest structure.” Remote Sensing of Environment, Vol. 239: Art. 111645. https://doi.org/10.1016/j.rse.2020.111645
   Google Scholar
• Bouvier, M., Durrieu, S., Fournier, R.A., and Renaud, J. 2015. Generalizing predictive models of forest inventory attributes using an area-based approach with airborne LiDAR data. Remote Sensing of Environment, Vol. 156, 322–334.
   Google Scholar
• Breidenbach, J., Kublin, E., McGaughey, R.J., Andersen, H.E., and Reutebuch, S.E. 2008. “Mixed-effects models for estimating stand volume by means of small footprint airborne laser scanner data.” The Photogrammetric Journal of Finland, Vol. 21(No. 1): pp. 4–15.
   Google Scholar
• Deo, R.K., Russell, M.B., Domke, G.M., Andersen, H.E., Cohen, W.B., and Woodall, C.W. 2017. “Evaluating site-specific and generic spatial models of aboveground forest biomass based on Landsat time-series and LiDAR strip samples in the eastern USA.” Remote Sensing, Vol. 9(No. 6): pp. 598. doi:10.3390/rs9060598.
   Web of Science ®Google Scholar
• D’Eon, S., van Lier, O., Woods, M., and White, J. 2018. “Canadian wood fibre centre e-lecture: Enhanced forest inventory.” https://www.cif-ifc.org/wp-content/uploads/2017/12/CIF-E-Lecture-EFRI-Feb-7-min.pdf.
   Google Scholar
• Downing, D.J., and Pettapiece, W.W. 2006. “Natural regions and subregions of Alberta.” Government of Alberta. Pub. No. T/852. Edmonton, AB, Canada, 2006; ISBN 0778545725.
   Google Scholar
• Eastman, J.R., and Fulk, M. 1993. “Long sequence time series evaluation using standardized principal components.” Photogrammetric Engineering & Remote Sensing, Vol. 59(No. 6): pp. 996. (991:
   Web of Science ®Google Scholar
• Ekstrom, B. 2007. “Forest management plan for the hearst forest.” Hearst, ON. Report 2007-2017-SFL 550053.
   Google Scholar
• Elith, J., Kearney, M., and Phillips, S. 2010. “The art of modelling range-shifting species.” Methods in Ecology and Evolution, Vol. 1(No. 4): pp. 330–342. doi:10.1111/j.2041-210X.2010.00036.x.
   Web of Science ®Google Scholar
• Fekety, P.A., Falkowski, M.J., Hudak, A.T., Jain, T.B., and Evans, J.S. 2018. “Transferability of Lidar-derived basal area and stem density models within a Northern Idaho ecoregion.” Canadian Journal of Remote Sensing, Vol. 44(No. 2): pp. 131–143. doi:10.1080/07038992.2018.1461557.
   Web of Science ®Google Scholar
• Fick, S.E., and Hijmans, R.J. 2017. “WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas.” International Journal of Climatology, Vol. 37(No. 12): pp. 4302–4315. doi:10.1002/joc.5086.
   Web of Science ®Google Scholar
• Fortin, M., Bernier, S., Saucier, J.-P., and Labbé, F. 2009. Une relation hauteur-diamètre tenant compte de l’influence de la station et du climat pour 20 espèces commerciales du Québec. Ministère des Ressources naturelles et de la Faune. Direction de la recherche forestière. Mémoire de recherche forestière n° 153. 22 p.
   Google Scholar
• Fulton, R.J. 1989. “Quaternary geology of Canada and Greenland.” Geological Survey of Canada, Geology of Canada Series no. 1, 839 p. (5 sheets). doi:10.4095/127905
   Google Scholar
• Grandpré, L.D., Morissette, J., and Gauthier, S. 2000. “Long-term post-fire changes in the northeastern boreal forest of Quebec.” Journal of Vegetation Science, Vol. 11(No. 6): pp. 791–800. doi:10.2307/3236549.
   Web of Science ®Google Scholar
• Grandpre, L.D., Waldron, K., Bouchard, M., Gauthier, S., Beaudet, M., Ruel, J.-C., Hebert, C., and Kneeshaw, D.D. 2018. “Incorporating insect and wind disturbances in a natural disturbance-based management framework for the boreal forest.” Forests, Vol. 9(No. 8): pp. 471. doi:10.3390/f9080471.
   Web of Science ®Google Scholar
• Guisan, A., Zimmermann, N.E., Elith, J., Graham, C.H., Phillips, S., and Peterson, A.T. 2007. “What matters for predicting the occurrences of trees: Techniques, data, or species’ characteristics?” Ecological Monographs, Vol. 77(No. 4): pp. 615–630. doi:10.1890/06-1060.1.
   Web of Science ®Google Scholar
• Hansen, A.J., Phillips, L.B., Dubayah, R., Goetz, S., and Hofton, M. 2014. “Regional-scale application of Lidar: Variation in forest canopy structure across the southeastern US.” Forest Ecology and Management, Vol. 329: pp. 214–226. doi:10.1016/j.foreco.2014.06.009.
   Web of Science ®Google Scholar
• Hare, F. K., and Thomas, M. K. 1979. Climate Canada. Toronto: J. Wiley.
   Google Scholar
• Hennigar, C.R., MacLean, D.A., Quiring, D.T., and Kershaw, J.A. Jr. 2008. “Differences in spruce budworm defoliation among balsam fir and white, red, and black spruce.” Forest Science, Vol. 54: pp. 158–166.
   Web of Science ®Google Scholar
• Hijmans, R. 2019. “R package raster: Geographic data analysis and modeling.” https://cran.r-project.org/web/packages/raster/raster.pdf
   Google Scholar
• Hijmans, R.J., Phillips, S., Leathwick, J.R., and Elith, J. 2019. “R package dismo: Species distribution modeling.” https://cran.r-project.org/web/packages/dismo/dismo.pdf
   Google Scholar
• Jiménez-Valverde, A., Lobo, J.M., and Hortal, J. 2008. “Not as good as they seem: The importance of concepts in species distribution modelling.” Diversity and Distributions, Vol. 14(No. 6): pp. 885–890. doi:10.1111/j.1472-4642.2008.00496.x.
   Web of Science ®Google Scholar
• Jucker, T., Asner, G.P., Dalponte, M., Brodrick, P., Christopher, D., Vaughn, N., Arn Teh, Y., Brelsford, C., Burslem, D.F.R.P., and Deere, N.J. 2018. “Estimating aboveground carbon density and its uncertainty in Borneo’s structurally complex tropical forests using airborne laser scanning.” Biosciences, Vol. 15: 3811–3830. doi:10.5194/bg-2018-74.
   Google Scholar
• Kane, V.R., Bakker, J.D., McGaughey, R.J., Lutz, J.A., Gersonde, R.F., and Franklin, J.F. 2010. Examining conifer canopy structural complexity across forest ages and elevations with LiDAR data. Canadian Journal of Forest Research, Vol. 40(No. 4): pp. 774–787.
   Google Scholar
• Kassambra, A., and Mundt, F. 2017. “R package factoextra: Extract and visualize the results of multivariate data analyses.” https://cran.r-project.org/web/packages/factoextra/factoextra.pdf
   Google Scholar
• Keränen, J., Maltamo, M., and Packalen, P. 2016. “Effect of flying altitude, scanning angle and scanning mode on the accuracy of ALS based forest inventory.” International Journal of Applied Earth Observation and Geoinformation, Vol. 52: pp. 349–360. doi:10.1016/j.jag.2016.07.005.
   Web of Science ®Google Scholar
• Kotivuori, E., Korhonen, L., and Packalen, P. 2016. “Nationwide airborne laser scanning based models for volume, biomass and dominant height in Finland.” Silva Fennica, Vol. 50(No. 4): pp. 1–28. doi:10.14214/sf.1567.
   Web of Science ®Google Scholar
• Kuhn, M. 2008. “Building predictive models in R using the caret package.” Journal of Statistical Software, Vol. 28(No. 5): pp. 1–26. doi:10.18637/jss.v028.i05.
   PubMed Web of Science ®Google Scholar
• Latifi, H., and Koch, B. 2012. “Evaluation of most similar neighbour and random forest methods for imputing forest inventory variables using data from target and auxiliary stands.” International Journal of Remote Sensing, Vol. 33(No. 21): pp. 6668–6694. doi:10.1080/01431161.2012.693969.
   Web of Science ®Google Scholar
• Lefsky, M.A., Cohen, W.B., Harding, D.J., Parker, G.G., Acker, S.A., and Gower, S.T. 2002. “Lidar remote sensing of above-ground biomass in three biomes.” Global Ecology and Biogeography, Vol. 11(No. 5): pp. 393–399. doi:10.1046/j.1466-822x.2002.00303.x.
   Web of Science ®Google Scholar
• Liaw, A., and Wiener, M. 2014. “R package randomForest: Breiman and Cutler’s random forests for classification and regression.” http://stat-www.berkeley.edu/users/breiman/RandomForests.
   Google Scholar
• Magnussen, S., Naesset, E., Gobakken, T., and Frazer, G. 2012. “A fine-scale model for area-based predictions of tree-size-related attributes derived from LiDAR canopy heights.” Scandinavian Journal of Forest Research, Vol. 27(No. 3): pp. 312–322. doi:10.1080/02827581.2011.624116.
   Web of Science ®Google Scholar
• Matthiopoulos, J., Hebblewhite, M., Aarts, G., and Fieberg, J. 2011. “Generalized functional responses for species distributions.” Ecology, Vol. 92(No. 3): pp. 583–589. doi:10.1890/10-0751.1.
   PubMed Web of Science ®Google Scholar
• Mulverhill, C., Coops, N., White, J., Tompalski, P., Marshall, P., and Bailey, T. 2018. “Enhancing the estimation of stem-size distributions for unimodal and bimodal stands in a boreal mixedwood forest with airborne laser scanning data.” Forests, Vol. 9(No. 2): pp. 95. https://doi.org/ [Mismatch] doi:10.3390/f9020095..
   Web of Science ®Google Scholar
• Naesset, E. 2005. “Assessing sensor effects and effects of leaf-off and leaf-on canopy conditions on biophysical stand properties derived from small-footprint airborne laser data.” Remote Sensing of Environment, Vol. 98(No. 2–3): pp. 356–370. doi:10.1016/j.rse.2005.07.012.
   Web of Science ®Google Scholar
• Naesset, E. 2009. “Effects of different sensors, flying altitudes, and pulse repetition frequencies on forest canopy metrics and biophysical stand properties derived from small-footprint airborne laser data.” Remote Sensing of Environment, Vol. 113(No. 1): pp. 148–159. doi:10.1016/j.rse.2008.09.001.
   Web of Science ®Google Scholar
• Naesset, E., and Gobakken, T. 2008. “Estimation of above- and below-ground biomass across regions of the boreal forest zone using airborne laser.” Remote Sensing of Environment, Vol. 112(No. 6): pp. 3079–3090. doi:10.1016/j.rse.2008.03.004.
   Web of Science ®Google Scholar
• Naesset, E., Gobakken, T., Holmgren, J., Hyyppä, H., Hyyppä, J., Maltamo, M., Nilsson, M., Olsson, H., Persson, Å., and Söderman, U. 2004. “Laser scanning of forest resources: The Nordic experience.” Scandinavian Journal of Forest Research, Vol. 19(No. 6): pp. 482–499. doi:10.1080/02827580410019553.
   Web of Science ®Google Scholar
• Neter, J., Kutner, M.H., Nachtsheim, C.J., and Wasserman, W. 1996. Applied Linear Regression Models. 3rd ed. Chicago: Irwin.
   Google Scholar
• Nilsson, M., Nordkvist, K., Jonzén, J., Lindgren, N., Axensten, P., Wallerman, J., Egberth, M., et al. 2017. “A nationwide forest attribute map of Sweden predicted using airborne laser scanning data and field data from the national forest inventory.” Remote Sensing of Environment, Vol. 194: pp. 447–454. doi:10.1016/j.rse.2016.10.022.
   Web of Science ®Google Scholar
• Penner, M., Pitt, D.G., and Woods, M.E. 2013. “Parametric vs. nonparametric LiDAR models for operational forest inventory in boreal Ontario.” Canadian Journal of Remote Sensing, Vol. 39(No. 5): pp. 426–443. 10.5589/m13-049.
   Web of Science ®Google Scholar
• Petitpierre, B., Broennimann, O., Kueffer, C., Daehler, C., and Guisan, A. 2017. “Selecting predictors to maximize the transferability of species distribution models: Lessons from cross-continental plant invasions.” Global Ecology and Biogeography, Vol. 26(No. 3): pp. 275–213. doi:10.1111/geb.12530.
   Web of Science ®Google Scholar
• Pitt, D.G., Woods, M., and Penner, M. 2014. “A comparison of point clouds derived from stereo imagery and airborne laser scanning for the area-based estimation of forest inventory attributes in boreal Ontario.” Canadian Journal of Remote Sensing, Vol. 40(No. 3): pp. 214–232. doi:10.1080/07038992.2014.958420.
   Web of Science ®Google Scholar
• R Development Core Team. 2015. “R: A language and environment for statistical computing.” Vienna, Austria: R Foundation for Statistical Computing. http://www.r-project.org.
   Google Scholar
• Robinson, A. 2016. “Package equivalence.” https://cran.r-project.org/web/packages/equivalence/equivalence.pdf
   Google Scholar
• Robinson, A.P., Duursma, R.A., and Marshall, J.D. 2005. “A regression-based equivalence test for model validation: Shifting the burden of proof.” Tree physiology, Vol. 25(No. 7): pp. 903–913. http://www.ncbi.nlm.nih.gov/pubmed/15870057. doi:10.1093/treephys/25.7.903.
   PubMed Web of Science ®Google Scholar
• Robinson, A.P., and Froese, R.E. 2004. “Model validation using equivalence tests.” Ecological Modelling, Vol. 176(No. 3–4): pp. 349–358. doi:10.1016/j.ecolmodel.2004.01.013.
   Web of Science ®Google Scholar
• Roussel, J.R., and Auty, D. 2016. “R package LidR: Airborne LiDAR data manipulations and visualisation for forestry applications.” https://github.com/Jean-Romain/lidR.
   Google Scholar
• Silva, C.A., Klauberg, C., Hudak, A.T., Vierling, L.A., Liesenberg, V., Carvalho, S.P.C., and Rodriguez, L.C.E. 2016. “A principal component approach for predicting the stem volume in eucalyptus plantations in Brazil using airborne LiDAR data.” Forestry, Vol. 89(No. 4): pp. 422–433. doi:10.1093/forestry/cpw016.
   Web of Science ®Google Scholar
• Slave Lake Pulp Corporation. 2004. Permanent Sample Plot Field Manual. Slave Lake: Slave Lake Pulp.
   Google Scholar
• Sutton, A., and Tardif, J.C. 2007. “Dendrochronological reconstruction of forest tent caterpillar outbreaks in time and space, Western Manitoba, Canada.” Canadian Journal of Forest Research, Vol. 37(No. 9): pp. 1643–1657. doi:10.1139/X07-021.
   Google Scholar
• Suvanto, A., and Maltamo, M. 2010. “Using mixed estimation for combining airborne laser scanning data in two different forest areas.” Silva Fennica, Vol. 44(No. 1): pp. 91–107. doi:10.14214/sf.164.
   Web of Science ®Google Scholar
• Talluto, M.V., Boulangeat, I., Ameztegui, A., Aubin, I., Berteaux, D., Butler, A., Doyon, F., et al. 2016. “Cross-scale integration of knowledge for predicting species ranges: A metamodelling framework.” Global Ecology and Biogeography, Vol. 25(No. 2): pp. 238–249. 10.1111/geb.12395.
   PubMed Web of Science ®Google Scholar
• Tompalski, P., White, J.C., Coops, N.C., and Wulder, M.A. 2019. “Demonstrating the transferability of forest inventory attribute models derived using airborne laser scanning data.” Remote Sensing of Environment, Vol. 227: pp. 110–124. (September 2018). doi:10.1016/j.rse.2019.04.006.
   Web of Science ®Google Scholar
• van Ewijk K.Y., Treitz, P.M., and Scott, N.A. 2011. Characterizing forest succession in central Ontario using LiDAR derived indices. Photogrammetric Engineering and Remote Sensing, Vol. 77 (3): 261–270.
   Google Scholar
• Villikka, M., Packalén, P., and Maltamo, M. 2012. “The suitability of leaf-off airborne laser scanning data in an area-based forest inventory of coniferous and deciduous trees.” Silva Fennica, Vol. 46(No. 1): pp. 99–110. doi:10.14214/sf.68.
   Web of Science ®Google Scholar
• Wang, T., Hamann, A., Spittlehouse, D., and Carroll, C. 2016. “Locally downscaled and spatially customizable climate data for historical and future periods for North America.” PLoS One, Vol. 11(No. 6): pp. e0156720. doi:10.1371/journal.pone.0156720.
   PubMed Web of Science ®Google Scholar
• Wenger, S.J., and Olden, J.D. 2012. “Assessing transferability of ecological models: An underappreciated aspect of statistical validation.” Methods in Ecology and Evolution, Vol. 3(No. 2): pp. 260–267. doi:10.1111/j.2041-210X.2011.00170.x.
   Web of Science ®Google Scholar
• Werkowska, W., Márquez, A.L., Real, R., and Acevedo, P. 2017. “A practical overview of transferability in species distribution modeling.” Environmental Reviews, Vol. 25(No. 1): pp. 127–133. (October 2016): doi:10.1139/er-2016-0045.
   Web of Science ®Google Scholar
• West Fraser Timber. 2002. Slave Lake Pulp Corporation 2000, Detailed Forest Management Plan. Slave Lake: Slave Lake Pulp.
   Google Scholar
• White, J.C., Arnett, J.T.T.R., Wulder, M.A., Tompalski, P., and Coops, N.C. 2015. “Evaluating the Impact of Leaf-on and Leaf-off Airborne Laser Scanning Data on the Estimation of Forest Inventory Attributes with the Area-Based Approach.” Canadian Journal of Forest Research, Vol. 45(No. 11): pp. 1498–1513. doi:10.1139/cjfr-2015-0192.
   Google Scholar
• White, J. C., Wulder, M. A., Varhola, A., Vastaranta, M., Coops, N. C., Cook, B. D., Pitt, D., and Woods, M. 2013. “A best practices guide for generating forest inventory attributes from airborne laser scanning data using an area-based approach.” Natural Resources Canada, Canadian Forest Service, Canadian Wood Fibre Centre, Victoria, BC. Information Report FI-X-010.
   Google Scholar
• White, J. C., Tompalski, P., Vastaranta, M., Wulder, M. A., Saarinen, N., Stepper, C., and Coops, N. C. 2017. “A model development and application guide for generating an enhanced forest inventory using airborne laser scanning data and an area-based approach.” Natural Resources Canada, Canadian Forest Service, Canadian Wood Fibre Centre, Victoria, BC. Information Report FI-X-018.
   Google Scholar
• Woods, M.E., Lim, K., and Treitz, P.M. 2008. “Predicting forest stand variables from LiDAR data in the Great Lakes – St Lawrence Forest of Ontario.” The Forestry Chronicle, Vol. 84(No. 6): pp. 827–839. doi:10.5558/tfc84827-6.
   Web of Science ®Google Scholar
• Woods, M., Pitt, D., Penner, M., Lim, K., Nesbitt, D., Etheridge, D., and Treitz, P. 2011. “Operational implementation of a LiDAR inventory in boreal Ontario.” The Forestry Chronicle, Vol. 87(No. 04): pp. 512–528. doi:10.5558/tfc2011-050.
   Google Scholar
• Wulder, M.A., Coops, N.C., Hudak, A.T., Morsdorf, F., Nelson, R.F., Newnham, G.J., and Vastaranta, M. 2013. “Status and prospects for LiDAR remote sensing of forested ecosystems.” Canadian Journal of Remote Sensing, Vol. 39(No. sup1): pp. S1–S5. doi:10.5589/m13-051.
   Web of Science ®Google Scholar
• Yates, K.L., Bouchet, P.J., Caley, M., Mengersen, K., Randin, C.F., Parnell, S., Fielding, A.H., et al. 2018. “Outstanding challenges in the transferability of ecological models.” Trends in ecology & evolution, Vol. 33(No. 10): pp. 790–802. doi:10.1016/j.tree.2018.08.001.
   PubMed Web of Science ®Google Scholar
• Yoga, S., Jean, B., Daigle, G., Riopel, M., and St-Onge, B. 2018. “A generalized Lidar-based model for predicting the merchantable volume of balsam fir of sites located along a bioclimatic gradient in Quebec, Canada.” Forests, Vol. 9(No. 4): pp. 166. doi:10.3390/f9040166.
   Web of Science ®Google Scholar
• Zhu, G.P., and Peterson, A.T. 2017. “Do consensus models outperform individual models? Transferability evaluations of diverse modeling approaches for an invasive moth.” Biological Invasions, Vol. 19(No. 9): pp. 2519–2532. doi:10.1007/s10530-017-1460-y.
   Web of Science ®Google Scholar