Evaluating tree root distribution in a tree-based intercropping system with use of ground penetrating radar

Paper presented at the 13th North American Agroforesty Conference, which was held June 19-21, 2013 in Charlottetown, Prince Edward Island, Canada.In Poppy, L., Kort, J., Schroeder, B., Pollock, T., and Soolanayakanahally, R., eds. Agroforestry: Innovations in Agriculture. Proceedings, 13th North American Agroforestry Conference, Charlottetown, Prince Edward Island, Canada, June 19-21, 2013.Within agroforestry systems, tree root architecture is a driver of important ecological processes such as belowground nutrient flows and C storage. Yet the belowground component of trees remains largely under-studied due to methodological restraints. Conventional subsurface sampling can overlook the heterogeneity of root systems, while complete excavations are destructive and unrepeatable. Thus, there is a need to develop non-intrusive technologies, such as ground penetrating radar (GPR), to measure root systems in situ. In this study we used GPR to detect coarse root distributions below five tree species (Quercus rubra, Juglans nigra, Populus sp., Picea abies, and Thuja occidentalis) at a temperate tree-based intercropping site in Guelph, Ontario. GPR geo-imaged transects were collected in 4.5 _ 4.5m grids that were centered on 15 individual trees. Subsequently, tree roots were identified across all geo-images (visualized as radar signal reflections) providing 3-dimensional root distribution data for each target tree. Roots detected by GPR accounted for approximately 80% of large coarse roots (�1cm) and 40% of small coarse roots (<1cm) that were later exposed in a subset of matched soil profiles. Significant inter-specific variations of coarse rooting depth preferences were detected. Additionally, preliminary analyses indicate different tree rooting patterns below the crop rows. To determine fine root distributions, fine roots were extracted from soil cores collected from the tree root study plots. Preliminary analysis indicates fine root length densities vary across species predominately in the upper 20cm. Limitations will be identified and applications will be discussed of GPR to answer ecological questions within agroforestry systems. Notably, we will highlight results from our complementary study that used the same GPR data to effectively estimate belowground biomass.Kira A. Borden (1), Marney E. Isaac (2) and Sean C. Thomas (1) ; 1. Faculty of Forestry, University of Toronto, 33 Willcocks Street, Toronto, Ontario, Canada, M5S 3B3. 2. Department of Physical and Environmental Sciences, University of Toronto at Scarborough, 1265 Military Trail, Toronto, Ontario, Canada, M1C 1A4.Includes bibliographical references

Intraspecific trait variation and coordination: Root and leaf economics spectra in coffee across environmental gradients

Hypotheses on the existence of a universal “Root Economics Spectrum” (RES) have received arguably the least attention of all trait spectra, despite the key role root trait variation plays in resource acquisition potential. There is growing interest in quantifying intraspecific trait variation (ITV) in plants, but there are few studies evaluating (i) the existence of an intraspecific RES within a plant species, or (ii) how a RES may be coordinated with other trait spectra within species, such as a leaf economics spectrum (LES). Using Coffea arabica (Rubiaceae) as a model species, we measured seven morphological and chemical traits of intact lateral roots, which were paired with information on four key LES traits. Field collections were completed across four nested levels of biological organization. The intraspecific trait coefficient of variation (cv) ranged from 25 to 87% with root diameter and specific root tip density showing the lowest and highest cv, respectively. Between 27 and 68% of root ITV was explained by site identity alone for five of the seven traits measured. A single principal component explained 56.2% of root trait covariation, with plants falling along a RES from resource acquiring to conserving traits. Multiple factor analysis revealed significant orthogonal relationships between root and leaf spectra. RES traits were strongly orthogonal with respect to LES traits, suggesting these traits vary independently from one another in response to environmental cues. This study provides among the first evidence that plants from the same species differentiate from one another along an intraspecific RES. We find that in one of the world's most widely cultivated crops, an intraspecific RES is orthogonal to an intraspecific LES, indicating that above and belowground responses of plants to managed (or natural) environmental gradients are likely to occur independently from one another. (Résumé d'auteur

A trait–environment relationship approach to participatory plant breeding for organic agriculture

The extent of intraspecific variation in trait–environment relationships is an open question with limited empirical support in crops. In organic agriculture, with high environmental heterogeneity, this knowledge could guide breeding programs to optimize crop attributes. We propose a three-dimensional framework involving crop performance, crop traits, and environmental axes to uncover the multidimensionality of trait–environment relationships within a crop. We modeled instantaneous photosynthesis (Asat) and water-use efficiency (WUE) as functions of four phenotypic traits, three soil variables, five carrot (Daucus carota) varieties, and their interactions in a national participatory plant breeding program involving a suite of farms across Canada. We used these interactions to describe the resulting 12 trait–environment relationships across varieties. We found one significant trait–environment relationship for Asat (taproot tissue density–soil phosphorus), which was consistent across varieties. For WUE, we found that three relationships (petiole diameter–soil nitrogen, petiole diameter–soil phosphorus, and leaf area–soil phosphorus) varied significantly across varieties. As a result, WUE was maximized by different combinations of trait values and soil conditions depending on the variety. Our three-dimensional framework supports the identification of functional traits behind the differential responses of crop varieties to environmental variation and thus guides breeding programs to optimize crop attributes from an eco-evolutionary perspective.Fil: Rolhauser, Andrés Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; Argentina. University of Toronto; CanadáFil: Windfeld, Emma. University of Toronto; Canadá. University of Calgary; CanadáFil: Hanson, Solveig. University of British Columbia; CanadáFil: Wittman, Hannah. University of British Columbia; CanadáFil: Thoreau, Chris. University of British Columbia; CanadáFil: Lyon, Alexandra. Kwantlen Polytechnic University; Canadá. University of British Columbia; CanadáFil: Isaac, Marney E.. University of Toronto; Canad

Against the odds: Network and institutional pathways enabling agricultural diversification

Farming systems that support locally diverse agricultural production and high levels of biodiversity are in rapid decline, despite evidence of their benefits for climate, environmental health, and food security. Yet, agricultural policies, financial incentives, and market concentration increasingly constrain the viability of diversified farming systems. Here, we present a conceptual framework to identify novel processes that promote the emergence and sustainability of diversified farming systems, using three real-world examples where farming communities have found pathways to diversification despite major structural constraints. By applying our framework to analyze these bright spots in the United States, Brazil, and Malawi, we identify two distinct pathways—network and institutional—to diversification. These pathways emerge through alignment of factors related to social and ecological structure (policies, institutions, and environmental conditions) and agency (values, collective action, and management decisions). We find that, when network and institutional pathways operate in tandem, the potential to scale up diversification across farms and landscapes increases substantially

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives