Eduard Mauri Ortuno 1 , Frédérik Doyon 2 , Alison Munson 1

1. Georeferenciation DB compilation Stepwise logistic regression GIS spatial DB Modeling the distribution of Pinus strobus L. at the beginning of the 19th century in central Quebec (Canada) using presettlement land survey records Eduard Mauri Ortuno1, Frédérik Doyon2, Alison Munson1 1 Centre d’étude de la forêt, Faculté de foresterie, géographie et géomatique, Université Laval 2 Université du Québec en Outaouais, Institut québécois d’aménagement de la forêt feuillue Introduction Eastern white pine (WP) is one of the most valuable conifers in eastern North America and part of our ecological heritage. In the province of Quebec, according to historical records, by 1900 the most accessible mature specimens had been selectively logged, particularly along the St. Lawrence River and its major tributa-ries, leaving relic populations that are poorly representative of its presettlement distribution 1, 2, 4, 5, 8. For example, in the study area, mature WP prevalence decrea-sed from 28 % in the 19th century (land survey observations) to a current 14 %, while conserving a high site fidelity 6. In La Mauricie national park (province of Quebec), WP volume passed from 12.5 % in the 19th century to a current 0.5 % 7, 10. Because WP presettlement abundance is unknown and its present distribution has been largely reduced, we aim to develop a tool to guide its ecological restoration. Study area It is limited by the intersection of the Mauricie region (province of Quebec) and the Acer saccharum-Betula alleghaniensis bioclimatic domain (about 7,000 km2), part of the Great Lakes-St. Lawrence forest. Landscape is mainly covered by glacial and fluvio-glacial deposits, with a relief composed of hills and high-hills, with moderate and steep slopes. Climate is continental subpolar, subhumid, with an average temperature of 3°C, 900 to 1,400 mm rainfall, and 160 to 180 growing season days 9. Methods 19th century WP (WP19) WP presence/absence is obtained from 13 land survey logbooks dating from 1795 to 1895. 2614 observation points were extracted. Associations with WP19 The order of abundance of each taxon was transformed to frequency using the broken stick model 3. Retaining taxa present in more than 1% of observation points, a hierarchical cluster analysis was performed on the 737 points containing WP19 to create six cover associations. Environmental conditions (env) Obtained from photo interpretation or digital elevation model. • Current WP traces (traces20) • Obtained from 421 randomly chosen land survey points: • 222 with WP19 • 199 without WP19 • The plot radius of 20 m was established as the depth the surveyor could distinguish the vegetation. • Traces20 were the abundance of: • WP stumps • Mature WP • WP saplings • WP seedlings • Management history • 1830 – 1850: beginning of WP selective cuts • 1850 – 1890: WP is still the most exploited species • 1890: mature WP depletion 2, 3, 5. Old white pine stump Eastern white pine (Pinus strobus L.) The species is a long-lasting pioneer favoured by surface fires, which burn the organic horizon and expose the mineral soil needed for seed germination. Because of its sensitivity to light competition at a young age, it is usually relegated to well-drained, coarse-textured sites 11, where the cover takes more time to close. Eastern white pine is present through all successional stages, among conifers as well as shade tolerant and intolerant hardwoods, but it rarely forms pure stands 12. study area survey point with WP19 survey point without WP19 This represents a state where WP was still within natural ranges. 20 km Results WP19 = f (env) Drainage was correlated with soil deposits, and slope did not add any extra information. Associations WP19 = f (env) The multinomial logistic regression was not significant, nor univariate regression with only one environmental predictor at a time. WP ecological restoration tool Probabilities from the model WP19 = f (env) are calculated for a 19 x 19 m cell grid, covering the study area where environmental predictors are available. There are 72 possible environmental combina-tions. Of these combinations, 60, covering 99.4 % of the study area, are taken into account by the model. 49 % of this area, according to the 0.28 threshold, has a higher chance of WP19presence than absence. Probability of WP19 presence ranges from 0.08 to 0.50. • Discussion • The model WP19 = f (env) is similar to known WP autoecology. Its weak prediction is due to the high frequency of glacial deposits (66 % of survey points), which are not statistically significant to predict WP19 presence/absence. Because glaciolacustrine and marine deposits (well drained and coarse textured) are situated near the Saint Lawrence Lowlands where settlement started, WP would have already been harvested there before land surveys were carried out. • A more accurate model is WP19 = f (traces20), but it has two main handicaps: • no possible remote sensing for traces20, • stump decomposition will erase this past evidence. • Using abundance of WP19 and traces20, instead of pre-sence/absence did not improve the models’ prediction. • The frequency of each cover association with WP19 can be used to guide a more comprehensive restoration. • In the region, major users would be: • Projet Triade: forest ecosystem management, • La Mauricie national park: WP restoration program. • Models presented here can be extended to the entire ecological region but not to the Saint Lawrence valley, due to major differences in topography and soil deposits. However, similar studies could be carried out. Steven Katovich, USDA Forest Service Objective and hypothesis Understand the presettlement distribution of WP in the central Mauricie region (province of Quebec), by relating past WP presence, as described by primeval land survey records, to environmental variables and current traces. Create a tool to guide the ecological restoration of WP, and its forests types, for the central Mauricie region. The hypotheses are: WP19 = f (traces20) Stumps, seedlings and saplings are positively related to WP19 presence. Acknowledgments References (1) Bouchard, P. 1999. Étude sur l'importance relative du pin blanc à l'intérieur des forêts naturelles du parc national de La Mauricie. Del Degan, Massé et Associés inc., Québec, QC. (2) Brisson, J., and Bouchard, A. 2003. In the past two centuries, human activities have caused major changes in the tree species composition of southern Quebec, Canada. Ecoscience 10(2): 236-246. (3) Frontier, S. 1976. Decrease of eigenvalues in princiapal component analysis - comparison with broken stick model. Journal of Experimental Marine Biology and Ecology 25(1): 67-75. (4) Gélinas, C. 1984. L'exploitation et la conservation forestière au parc national de La Mauricie 1830-1940 : dossier documentaire. Parcs Canada, Québec, QC. (5) Lafleur, N. 1970. La drave en Mauricie, des origines à nos jours : histoire et traditions. 1st ed. Éditions du Bien public, Trois-Rivières, QC. (6) Mauri Ortuno, E., Doyon, F., and Munson, A. 2008. Poster: Modélisation de la distribution du pin blanc au début du 19e siècle dans la Moyenne-Mauricie. Colloque Triade. Shawinigan, QC, september 25-26, 2008. (7) Pelletier, H. 1998. Plan de conservation des écosystèmes terrestres, parc national de La Mauricie. Service de la conservation des ressources naturelles, Parcs Canada, Québec, QC. (8) Quenneville, R., and Thériault, R. 2001. La restauration des écosystèmes de pin blanc (Pinus strobus) - Un enjeu majeur pour le parc national de La Mauricie. Le Naturaliste canadien 125(2): 39-42. (9) Robitaille, A., and Saucier, J.-P. 1998. Paysages régionaux du Québec méridional. 1st ed. Les Publications du Québec, Sainte-Foy, QC. (10) Service de conservation des ressources naturelles. 1998. Cadre la restauration écologique du pin blanc au parc national de la Mauricie. Parcs Canada, Québec, QC. (11) Vlasiu, P.D., Nolet, P., and Doyon, F. 2001. Le pin blanc - Revue de littérature. Institut québécois d’aménagement de la forêt feuillue, QC. (12) Wendel, G.W., and Smith, H.C. 1990. Eastern White Pine. In Conifers. Edited by R. M. Burns, and B. H. Honkala. United States Department of Agriculture, Forest Service, Washington, DC.