Canadian Forest Service Publications

Geographic scale and disturbance influence intraspecific trait variability in leaves and roots of North American understorey plants. 2019. Kumordzi, B.B.; Aubin, I.; Cardou, F.; Shipley, B.; Violle, C.; Johnstone, J.; Anand, M.; Arsenault, A.; Bell, F.W.; Bergeron, Y.; Boulangeat, I.; Brousseau, M.; De Grandpré, L.; Delagrange, S.; Fenton, N.J.; Gravel, D.; Macdonald, S.E.; Hamel, B.; Higelin, M.; Hébert, F.; Isabel, N.; Mallik, A.; McIntosh, A.C.S.; McLaren, J.R.; Messier, C.; Morris, D.; Thiffault, N.; Tremblay, J.-P.; Munson, A.D. Functional Ecology

Year: 2019

Available from: Great Lakes Forestry Centre

Catalog ID: 39820

Language: English

CFS Availability: PDF (request by e-mail)

Available from the Journal's Web site.
DOI: 10.1111/1365-2435.13402

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Plain Language Summary

This paper investigates the variability in leaf and root characteristics for six widely distribution understory plant species in Canada. Understory species play an integral role in ecosystem processes especially in northern forest ecosystems. Within a given species, high variability in characteristics enables them to adapt to wide range of environmental conditions and levels of resource availability. We enlisted and coordinated the efforts of 23 research teams across Canada for field sampling of 80 sites in July 2014 (from Newfoundland to Yukon) covering four biophysical regions (about 5000km). When comparing between areas, variability in plant characteristics decreases with increasing study scale, with most variability captured within localities of similar climate and soil conditions. Models showed that site disturbance explained the most variability in plant characteristics, especially for roots. However, the amount of variability within a species differed between leaves and roots, with root characteristics being consistently less variable across all spatial scales. Our study suggests that even for a species occurring across wide geographical ranges, most variability can be found within local populations. This has practical implications for sampling design and trait selection for both local studies and continental scale modelling.