Tracking conifer composition change: a ground and satellite based assessment of Quebec’s forests over three decades

Abstract

Studies in Quebec have reported contrasting trends in conifer composition, with some documenting long-term declines while others suggest increases. This study examined changes in conifer basal area percentage (CBAP) from 1985 to 2021 using 1796 permanent forest inventory plots across deciduous, mixed, and boreal forest zones and evaluates Landsat based Cubist regression models from two time periods (1992/1993—2016/2017) to monitor these shifts. Field data showed a consistent increase in CBAP over time, with nearly 50% of all plots showing increases, especially in mixed forests where balsam fir (Abies balsamea) accounted for much of the observed change. This trend may reflect successional processes in stands recovering from the last major spruce budworm outbreak (1972–1986) and forest tent caterpillar outbreaks in the province. Cubist models predicting CBAP and trained on Landsat-8 imagery from 2016/2017 had the best performance overall, with an average R² of 0.679, correlation of 0.82, and lowest average error (14.1%). To improve comparability across sensors and years, we selected a combined model (M24) trained on data from both time periods to generate spatial predictions. The model achieved an R² of 0.633 and used only four untransformed spectral bands within a single rule. This model effectively reproduced the median CBAP values through time at the regional scale, predicting medians of 38.3% (observed: 39.3%) in 1992/1993 and 62.4% (observed: 60.0%) in 2016/2017, though it underestimated values at the extremes. At the plot level, predicted changes in CBAP were only moderately aligned with observed changes (R² = 0.241, MAE = 17.31, RMSE = 22.18). Overall, our findings demonstrate that satellite-based models can reliably detect broad trends in forest composition, and integrating CBAP into remote sensing workflows provides a scalable, interpretable approach for long-term ecological monitoring and forest management.

Keywords

Conifer composition / Remote sensing / Cubist regression / Structural diversity / Quebec

References

[1] Agriculture and Agri-Food Canada (AAFC) (2021) AAFC Land Use Time Series 2000, 2005, 2010, 2015, 2020, Agroclimate, geomatics and earth observation division, science and technology branch. https://open.canada.ca/data/en/dataset/fa84a70f-03ad-4946-b0f8-a3b481dd5248

[2] Atkins JW, Bhatt P, Carrasco L, Francis E, Garabedian JE, Hakkenberg CR, Hardiman BS, Jung J, Koirala A, LaRue EA, Oh S, Shao G, Shao GF, Shugart HH, Spiers A, Stovall AEL, Surasinghe TD, Tai XN, Zhai L, Zhang T, Krause K. Integrating forest structural diversity measurement into ecological research. Ecosphere, 2023, 14(9): e4633

[3] Baker C, Lawrence RL, Montagne C, Patten D. Change detection of wetland ecosystems using Landsat imagery and change vector analysis. Wetlands, 2007, 27(3): 610-619

[4] Boakye EA, Houle D, Bergeron Y, Girardin MP, Drobyshev I. Insect defoliation modulates influence of climate on the growth of tree species in the boreal mixed forests of Eastern Canada. Ecol Evol, 2022, 12(3): e8656

[5] Boisvert-Marsh L, Périé C, de Blois S. Shifting with climate? Evidence for recent changes in tree species distribution at high latitudes. Ecosphere, 2014, 5(7): art83

[6] Bouchard M, Kneeshaw D, Bergeron Y. Mortality and stand renewal patterns following the last spruce budworm outbreak in mixed forests of Western Quebec. For Ecol Manag, 2005, 204(2–3): 297-313

[7] Boucher Y, Arseneault D, Sirois L, Blais L. Logging pattern and landscape changes over the last century at the boreal and deciduous forest transition in Eastern Canada. Landsc Ecol, 2009, 24(2): 171-184

[8] Boucher Y, Auger I, Noël J, Grondin P, Arseneault D. Fire is a stronger driver of forest composition than logging in the boreal forest of Eastern Canada. J Veg Sci, 2017, 28(1): 57-68

[9] Brice MH, Vissault S, Vieira W, Gravel D, Legendre P, Fortin MJ. Moderate disturbances accelerate forest transition dynamics under climate change in the temperate–boreal ecotone of eastern North America. Glob Change Biol, 2020, 26(8): 4418-4435

[10] Cipar J, Cooley T, Lockwood R, Grigsby P (2004) Distinguishing between coniferous and deciduous forests using hyperspectral imagery. In: IGARSS 2004.2004 IEEE International Geoscience and Remote Sensing Symposium, Anchorage, AK, USA. pp 2348–2351. https://doi.org/10.1109/IGARSS.2004.1369758

[11] Cohen J (1988) Statistical power analysis for the behavioral sciences (2nd ed). Lawrence Erlbaum Associates.

[12] Cohen WB, Maiersperger TK, Spies TA, Oetter DR. Modelling forest cover attributes as continuous variables in a regional context with Thematic Mapper data. Int J Remote Sens, 2001, 22(12): 2279-2310

[13] Collier JH, MacLean DA, Taylor AR, D’Orangeville L. Warming adversely affects density but not growth of balsam fir regeneration across a climatic gradient in the Acadian Forest Region of Eastern Canada. Can J for Res, 2024, 54(2): 134-146

[14] Cooke BJ, Robert LE, Sturtevant BR, Kneeshaw D, Thapa B. Confronting the cycle synchronisation paradigm of defoliator outbreaks in space and time: evidence from two systems in a mixed-species forest landscape. J Ecol, 2024, 112(1): 152-173

[15] Crawford CJ, Roy DP, Arab S, Barnes C, Vermote E, Hulley G, Gerace A, Choate M, Engebretson C, Micijevic E, Schmidt G, Anderson C, Anderson M, Bouchard M, Cook B, Dittmeier R, Howard D, Jenkerson C, Kim M, Kleyians T, Maiersperger T, Mueller C, Neigh C, Owen L, Page B, Pahlevan N, Rengarajan R, Roger JC, Sayler K, Scaramuzza P, Skakun S, Yan L, Zhang HK, Zhu Z, Zahn S. The 50-year Landsat collection 2 archive. Sci Remote Sens, 2023, 8 100103

[16] Crête M, Marzell L. Évolution des forêts québécoises au regard des habitats fauniques: analyse des grandes tendances sur trois décennies. For Chron, 2006, 82(3): 368-382

[17] Danneyrolles V, Vellend M, Dupuis S, Boucher Y, Laflamme J, Bergeron Y, Fortin G, Leroyer M, de Römer A, Terrail R, Arseneault D. Scale-dependent changes in tree diversity over more than a century in eastern Canada: landscape diversification and regional homogenization. J Ecol, 2021, 109(1): 273-283

[18] DeFries RS, Townshend JRG, Hansen MC. Continuous fields of vegetation characteristics at the global scale at 1-km resolution. J Geophys Res Atmos, 1999, 104(D14): 16911-16923

[19] Demarquet Q, Rapinel S, Gore O, Dufour S, Hubert-Moy L. Continuous change detection outperforms traditional post-classification change detection for long-term monitoring of wetlands. Int J Appl Earth Obs Geoinf, 2024, 133 104142

[20] Donnini J, Kross A, Alejo C. Spectral diversity as a predictor of tree diversity: exploring challenges and opportunities across forest ecosystems. Can J Remote Sens, 2024, 50(1): 2403495

[21] Duchesne L, Ouimet R. Population dynamics of tree species in southern Quebec, Canada: 1970–2005. For Ecol Manage, 2008, 255(7): 3001-3012

[22] Earth Resources Observation and Science (EROS) Center (2020a) Landsat 4–5 Thematic Mapper Level-2, Collection 2 . U.S. Geological Survey. https://doi.org/10.5066/P9IAXOVV

[23] Earth Resources Observation and Science (EROS) Center (2020b) Landsat 8–9 Operational Land Imager/Thermal Infrared Sensor Level-2, Collection 2 . U.S. Geological Survey. https://doi.org/10.5066/P9OGBGM6

[24] Felton A, Hedwall PO, Trubins R, Lagerstedt J, Felton A, Lindbladh M. From mixtures to monocultures: bird assemblage responses along a production forest conifer-broadleaf gradient. For Ecol Manage, 2021, 494 119299

[25] Fick SE, Hijmans RJ. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int J Climatol, 2017, 37(12): 4302-4315

[26] Filippelli SK, Vogeler JC, Falkowski MJ, Meneguzzo DM. Monitoring conifer cover: leaf-off lidar and image-based tracking of eastern redcedar encroachment in central Nebraska. Remote Sens Environ, 2020, 248 111961

[27] Frank RM (1990) Abies balsamea. In: Silvics of North America: Volume 1. Conifers. USDA, Forest Service, Agriculture Handbook 654. https://research.fs.usda.gov/treesearch/1547

[28] Franklin JF, Cromack KJ, Denison W, McKee A, Maser C, Sedell J, Swanson F, Juday G (1981) Ecological characteristics of old-growth Douglas-fir forests. General Tech Rep PNW-GTR-118. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. https://doi.org/10.2737/PNW-GTR-118

[29] Gitelson AA, Kaufman YJ, Stark R, Rundquist D. Novel algorithms for remote estimation of vegetation fraction. Remote Sens Environ, 2002, 80(1): 76-87

[30] Gouvernement du Québec (2025) Livrée des forêts. In: Animaux sauvages Québec. https://www.quebec.ca/agriculture-environnement-et-ressources-naturelles/faune/animaux-sauvages-quebec/fiches-especes-fauniques/livree-forets

[31] Jactel H, Bauhus J, Boberg J, Bonal D, Castagneyrol B, Gardiner B, Gonzalez-Olabarria JR, Koricheva J, Meurisse N, Brockerhoff EG. Tree diversity drives forest stand resistance to natural disturbances. Curr for Rep, 2017, 3(3): 223-243

[32] Jordan CF. Derivation of leaf-area index from quality of light on the forest floor. Ecology, 1969, 50(4): 663-666

[33] Kent M (2012) Vegetation Description and Analysis: A Practical Approach (2nd Edition). Oxford: Wiley-Blackwell

[34] Kuhn M. Building predictive models in R using the caret package. J Stat Softw, 2008, 28(5): 1-26

[35] Kuhn M, Johnson K. Applied predictive modeling. Springer, New York, 2013,

[36] Kuhn M, Quinlan R (2025) Cubist: rule- and instance-based regression modeling. R package version 0.5.0.9000. https://topepo.github.io/Cubist/

[37] Lang AK, LaRue EA, Kivlin SN, Edwards JD, Phillips RP, Gallion J, Kong N, Parker JD, McCormick MK, Domke G, Fei SL. Forest structural diversity is linked to soil microbial diversity. Ecosphere, 2023, 14(11): e4702

[38] LaRue EA, Knott JA, Domke GM, Chen HY, Guo QF, Hisano M, Oswalt C, Oswalt S, Kong N, Potter KM, Fei SL. Structural diversity as a reliable and novel predictor for ecosystem productivity. Front Ecol Environ, 2023, 21(1): 33-39

[39] Lausch A, Bannehr L, Beckmann M, Boehm C, Feilhauer H, Hacker JM, Heurich M, Jung A, Klenke R, Neumann C, Pause M, Rocchini D, Schaepman ME, Schmidtlein S, Schulz K, Selsam P, Settele J, Skidmore AK, Cord AF. Linking Earth Observation and taxonomic, structural and functional biodiversity: local to ecosystem perspectives. Ecol Indic, 2016, 70: 317-339

[40] Leduc A, Leduc A, Kneeshaw D, Maleki K, Bergeron Y. Advancing and reversing succession as a function of time since fire and insect outbreaks: an 18 year in situ remeasurement of changes in forest composition. J Veg Sci, 2021, 32(1): e12974

[41] Ma HZ, Crowther TW, Mo LD, et al. . The global biogeography of tree leaf form and habit. Nat Plants, 2023, 9: 1795-1809

[42] Macdonald E, Work T, Drapeau P, Bergeron Y, Quideau S, Chen H, Spence J, Lecomte N (2010) Biodiversity and canopy composition in boreal mixedwoods: different roofs - different inhabitants? SFM Network Research Note Series No. 59, Sustainable Forest Management Network. https://doi.org/10.7939/R35Q4RS8F

[43] Man RZ. Twenty-year responses of aspen stands to forest tent caterpillar defoliation and overstory dieback in Northeastern Ontario, Canada. For Ecol Manage, 2024, 561 121869

[44] Mekonnen ZA, Riley WJ, Randerson JT, Grant RF, Rogers BM. Expansion of high-latitude deciduous forests driven by interactions between climate warming and fire. Nat Plants, 2019, 5(9): 952-958

[45] Ministry of Forests, Wildlife and Parks (MFFP) (2015a) Ecoforestry stratification standard, fourth ecoforestry inventory of southern Quebec. October 2008, reissue—September 2015, Forest Inventory Department. https://mffp.gouv.qc.ca/documents/forets/inventaire/norme-stratification.pdf

[46] Ministry of Forests, Wildlife and Parks (MFFP) (2015b) Sustainable forest management strategy. https://mffp.gouv.qc.ca/english/publications/forest/sustainable-forest-managementstrategy.pdf

[47] Ministry of Forests, Wildlife and Parks (MFFP) (2016) Integration of ecological issues into the integrated forest management plans of 2018−2023, Notebook 4.1—Issues related to plant composition. Forest Planning and Environment Department. https://mffp.gouv.qc.ca/documents/forets/amenagement/Cahier_4.1_Composition_vegetale.pdf

[48] Ministry of Natural Resources and Forests (MRNF) (2017) Permanent sample plot , in Données Québec, 2017, updated April 17, 2025. https://www.donneesquebec.ca/recherche/dataset/placettes-echantillons-permanentes-1970-a-aujourd-hui.

[49] Ministry of Natural Resources and Forests (MRNF) (2022) Vegetation zones and bioclimatic domains of Quebec. Government of Quebec. https://mffp.gouv.qc.ca/nos-publications/zones-vegetation-domaines-bioclimatiques/

[50] Moulinier J, Lorenzetti F, Bergeron Y. Effects of a forest tent caterpillar outbreak on the dynamics of mixedwood boreal forests of eastern Canada. Écoscience, 2013, 20(2): 182-193

[51] Noseworthy J, Beckley TM. Borealization of the New England–Acadian forest. Environ Rev, 2020, 28(3): 284-293

[52] Noss RF. Indicators for monitoring biodiversity: a hierarchical approach. Conserv Biol, 1990, 4(4): 355-364

[53] R Core Team. R: a language and environment for statistical computing, 2021, Vienna, Austria. R Foundation for Statistical Computing

[54] Rautiainen M, Lukeš P, Homolová L, Hovi A, Pisek J, Mõttus M. Spectral properties of coniferous forests: a review of in situ and laboratory measurements. Remote Sens, 2018, 10(2): 207

[55] Richardson G, Knudby A, Crowley MA, Sawada M, Chen WJ. Machine learning approaches to Landsat change detection analysis. Can J Remote Sens, 2025, 51(1): 2448169

[56] Roberts DA, Ustin SL, Ogunjemiyo S, Greenberg J, Dobrowski SZ, Chen JQ, Hinckley TM. Spectral and structural measures of northwest forest vegetation at leaf to landscape scales. Ecosystems, 2004, 7(5): 545-562

[57] Rohde WG, Olson CEJr. Multispectral sensing of forest tree species. Photogramm Eng Remote Sens, 1972, 38: 1209-1215

[58] Rouse JW, Haas RH, Schell JA, Deering DW (1974) Monitoring vegetation systems in the Great Plains with ERTS. https://ntrs.nasa.gov/citations/19740022614

[59] Seidl R, Thom D, Kautz M, Martin-Benito D, Peltoniemi M, Vacchiano G, Wild J, Ascoli D, Petr M, Honkaniemi J, Lexer MJ, Trotsiuk V, Mairota P, Svoboda M, Fabrika M, Nagel TA, Reyer CPO. Forest disturbances under climate change. Nat Clim Chang, 2017, 7: 395-402

[60] Sittaro F, Paquette A, Messier C, Nock CA. Tree range expansion in eastern North America fails to keep pace with climate warming at northern range limits. Glob Change Biol, 2017, 23(8): 3292-3301

[61] Tinya F, Kovács B, Bidló A, Dima B, Király I, Kutszegi G, Lakatos F, Mag Z, Márialigeti S, Nascimbene J, Samu F, Siller I, Szél G, Ódor P. Environmental drivers of forest biodiversity in temperate mixed forests–a multi-taxon approach. Sci Total Environ, 2021, 795 148720

[62] Tuanmu MN, Jetz W. A global 1-km consensus land-cover product for biodiversity and ecosystem modelling. Glob Ecol Biogeogr, 2014, 23(9): 1031-1045

[63] Wang K, Wang YY, Wen H, Zhang XT, Yu JH, Wang QG, Han SJ, Wang WJ. Biomass carbon sink stability of conifer and broadleaf boreal forests: differently associated with plant diversity and mycorrhizal symbionts?. Environ Sci Pollut Res Int, 2023, 30(54): 115337-115359

[64] Williams DL. A comparison of spectral reflectance properties at the needle, branch, and canopy level for selected conifer species. Remote Sens Environ, 1991, 35(2–3): 79-93

[65] Xiao XM, Hollinger D, Aber J, Goltz M, Davidson EA, Zhang QY, Moore B. Satellite-based modeling of gross primary production in an evergreen needleleaf forest. Remote Sens Environ, 2004, 89(4): 519-534

[66] Yang RR, Wang L, Tian QJ, Xu NX, Yang YJ. Estimation of the conifer-broadleaf ratio in mixed forests based on time-series data. Remote Sens, 2021, 13(21): 4426

[67] Zhai L, Will RE, Zhang B. Structural diversity is better associated with forest productivity than species or functional diversity. Ecology, 2024, 105(4): e4269

RIGHTS & PERMISSIONS

Northeast Forestry University