Tree Establishment on Post-Mining Waste Soils: Species, Density, and Mixture Effects

Tree establishment to restore degraded boreal post-mining lands is challenged by low soil productivity, a harsh microclimate, and potentially high contaminant levels. The use of mixed vegetation can facilitate the microclimate but increase competition for soil resources. A statistical accounting of plant–plant interactions and adaptation to multispecies conditions is hard to achieve in field experiments; trials under controlled conditions can distinguish effects of planting density and species interactions in the early stages of plant establishment. A greenhouse trial was established in containers (“mesocosms”) with waste rock or fine tailings from gold mines. Pregerminated (1-week-old) seedlings (Alnus viridis subsp. crispa, Picea glauca, Populus tremuloides, Salix arbusculoides) were planted using a Nelder density gradient design, modified for species combinations. A relative competition effect was estimated as a competitiveness index for each species combination, calculated as a ratio of α coefficients in the Holliday growth equation. The specific leaf area (SLA) was measured to indicate plant water stress adaptation. All species grew better in monoculture on fine tailings, while only P. tremuloides grew better in all mixtures on waste rock. Although net positive effects of density on SLA increment during early growth suggested microclimate improvement on fine tailings, no mixture provided advantages for both species in paired combinations

Hi-sAFe: a 3D agroforestry model for integrating dynamic tree–crop interactions

Agroforestry, the intentional integration of trees with crops and/or livestock, can lead to multiple economic and ecological benefits compared to trees and crops/livestock grown separately. Field experimentation has been the primary approach to understanding the tree–crop interactions inherent in agroforestry. However, the number of field experiments has been limited by slow tree maturation and difficulty in obtaining consistent funding. Models have the potential to overcome these hurdles and rapidly advance understanding of agroforestry systems. Hi-sAFe is a mechanistic, biophysical model designed to explore the interactions within agroforestry systems that mix trees with crops. The model couples the pre-existing STICS crop model to a new tree model that includes several plasticity mechanisms responsive to tree–tree and tree–crop competition for light, water, and nitrogen. Monoculture crop and tree systems can also be simulated, enabling calculation of the land equivalent ratio. The model’s 3D and spatially explicit form is key for accurately representing many competition and facilitation processes. Hi-sAFe is a novel tool for exploring agroforestry designs (e.g., tree spacing, crop type, tree row orientation), management strategies (e.g., thinning, branch pruning, root pruning, fertilization, irrigation), and responses to environmental variation (e.g., latitude, climate change, soil depth, soil structure and fertility, fluctuating water table). By improving our understanding of the complex interactions within agroforestry systems, Hi-sAFe can ultimately facilitate adoption of agroforestry as a sustainable land-use practice

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

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.Rest of authors: Decky Junaedi, Robert R. Junker, Eric Justes, Richard Kabzems, Jeffrey Kane, Zdenek Kaplan, Teja Kattenborn, Lyudmila Kavelenova, Elizabeth Kearsley, Anne Kempel, Tanaka Kenzo, Andrew Kerkhoff, Mohammed I. Khalil, Nicole L. Kinlock, Wilm Daniel Kissling, Kaoru Kitajima, Thomas Kitzberger, Rasmus Kjøller, Tamir Klein, Michael Kleyer, Jitka Klimešová, Joice Klipel, Brian Kloeppel, Stefan Klotz, Johannes M. H. Knops, Takashi Kohyama, Fumito Koike, Johannes Kollmann, Benjamin Komac, Kimberly Komatsu, Christian König, Nathan J. B. Kraft, Koen Kramer, Holger Kreft, Ingolf Kühn, Dushan Kumarathunge, Jonas Kuppler, Hiroko Kurokawa, Yoko Kurosawa, Shem Kuyah, Jean-Paul Laclau, Benoit Lafleur, Erik Lallai, Eric Lamb, Andrea Lamprecht, Daniel J. Larkin, Daniel Laughlin, Yoann Le Bagousse-Pinguet, Guerric le Maire, Peter C. le Roux, Elizabeth le Roux, Tali Lee, Frederic Lens, Simon L. Lewis, Barbara Lhotsky, Yuanzhi Li, Xine Li, Jeremy W. Lichstein, Mario Liebergesell, Jun Ying Lim, Yan-Shih Lin, Juan Carlos Linares, Chunjiang Liu, Daijun Liu, Udayangani Liu, Stuart Livingstone, Joan Llusià, Madelon Lohbeck, Álvaro López-García, Gabriela Lopez-Gonzalez, Zdeňka Lososová, Frédérique Louault, Balázs A. Lukács, Petr Lukeš, Yunjian Luo, Michele Lussu, Siyan Ma, Camilla Maciel Rabelo Pereira, Michelle Mack, Vincent Maire, Annikki Mäkelä, Harri Mäkinen, Ana Claudia Mendes Malhado, Azim Mallik, Peter Manning, Stefano Manzoni, Zuleica Marchetti, Luca Marchino, Vinicius Marcilio-Silva, Eric Marcon, Michela Marignani, Lars Markesteijn, Adam Martin, Cristina Martínez-Garza, Jordi Martínez-Vilalta, Tereza Mašková, Kelly Mason, Norman Mason, Tara Joy Massad, Jacynthe Masse, Itay Mayrose, James McCarthy, M. Luke McCormack, Katherine McCulloh, Ian R. McFadden, Brian J. McGill, Mara Y. McPartland, Juliana S. Medeiros, Belinda Medlyn, Pierre Meerts, Zia Mehrabi, Patrick Meir, Felipe P. L. Melo, Maurizio Mencuccini, Céline Meredieu, Julie Messier, Ilona Mészáros, Juha Metsaranta, Sean T. Michaletz, Chrysanthi Michelaki, Svetlana Migalina, Ruben Milla, Jesse E. D. Miller, Vanessa Minden, Ray Ming, Karel Mokany, Angela T. Moles, Attila Molnár V, Jane Molofsky, Martin Molz, Rebecca A. Montgomery, Arnaud Monty, Lenka Moravcová, Alvaro Moreno-Martínez, Marco Moretti, Akira S. Mori, Shigeta Mori, Dave Morris, Jane Morrison, Ladislav Mucina, Sandra Mueller, Christopher D. Muir, Sandra Cristina Müller, François Munoz, Isla H. Myers-Smith, Randall W. Myster, Masahiro Nagano, Shawna Naidu, Ayyappan Narayanan, Balachandran Natesan, Luka Negoita, Andrew S. Nelson, Eike Lena Neuschulz, Jian Ni, Georg Niedrist, Jhon Nieto, Ülo Niinemets, Rachael Nolan, Henning Nottebrock, Yann Nouvellon, Alexander Novakovskiy, The Nutrient Network, Kristin Odden Nystuen, Anthony O'Grady, Kevin O'Hara, Andrew O'Reilly-Nugent, Simon Oakley, Walter Oberhuber, Toshiyuki Ohtsuka, Ricardo Oliveira, Kinga Öllerer, Mark E. Olson, Vladimir Onipchenko, Yusuke Onoda, Renske E. Onstein, Jenny C. Ordonez, Noriyuki Osada, Ivika Ostonen, Gianluigi Ottaviani, Sarah Otto, Gerhard E. Overbeck, Wim A. Ozinga, Anna T. Pahl, C. E. Timothy Paine, Robin J. Pakeman, Aristotelis C. Papageorgiou, Evgeniya Parfionova, Meelis Pärtel, Marco Patacca, Susana Paula, Juraj Paule, Harald Pauli, Juli G. Pausas, Begoña Peco, Josep Penuelas, Antonio Perea, Pablo Luis Peri, Ana Carolina Petisco-Souza, Alessandro Petraglia, Any Mary Petritan, Oliver L. Phillips, Simon Pierce, Valério D. Pillar, Jan Pisek, Alexandr Pomogaybin, Hendrik Poorter, Angelika Portsmuth, Peter Poschlod, Catherine Potvin, Devon Pounds, A. Shafer Powell, Sally A. Power, Andreas Prinzing, Giacomo Puglielli, Petr Pyšek, Valerie Raevel, Anja Rammig, Johannes Ransijn, Courtenay A. Ray, Peter B. Reich, Markus Reichstein, Douglas E. B. Reid, Maxime Réjou-Méchain, Victor Resco de Dios, Sabina Ribeiro, Sarah Richardson, Kersti Riibak, Matthias C. Rillig, Fiamma Riviera, Elisabeth M. R. Robert, Scott Roberts, Bjorn Robroek, Adam Roddy, Arthur Vinicius Rodrigues, Alistair Rogers, Emily Rollinson, Victor Rolo, Christine Römermann, Dina Ronzhina, Christiane Roscher, Julieta A. Rosell, Milena Fermina Rosenfield, Christian Rossi, David B. Roy, Samuel Royer-Tardif, Nadja Rüger, Ricardo Ruiz-Peinado, Sabine B. Rumpf, Graciela M. Rusch, Masahiro Ryo, Lawren Sack, Angela Saldaña, Beatriz Salgado-Negret, Roberto Salguero-Gomez, Ignacio Santa-Regina, Ana Carolina Santacruz-García, Joaquim Santos, Jordi Sardans, Brandon Schamp, Michael Scherer-Lorenzen, Matthias Schleuning, Bernhard Schmid, Marco Schmidt, Sylvain Schmitt, Julio V. Schneider, Simon D. Schowanek, Julian Schrader, Franziska Schrodt, Bernhard Schuldt, Frank Schurr, Galia Selaya Garvizu, Marina Semchenko, Colleen Seymour, Julia C. Sfair, Joanne M. Sharpe, Christine S. Sheppard, Serge Sheremetiev, Satomi Shiodera, Bill Shipley, Tanvir Ahmed Shovon, Alrun Siebenkäs, Carlos Sierra, Vasco Silva, Mateus Silva, Tommaso Sitzia, Henrik Sjöman, Martijn Slot, Nicholas G. Smith, Darwin Sodhi, Pamela Soltis, Douglas Soltis, Ben Somers, Grégory Sonnier, Mia Vedel Sørensen, Enio Egon Sosinski Jr, Nadejda A. Soudzilovskaia, Alexandre F. Souza, Marko Spasojevic, Marta Gaia Sperandii, Amanda B. Stan, James Stegen, Klaus Steinbauer, Jörg G. Stephan, Frank Sterck, Dejan B. Stojanovic, Tanya Strydom, Maria Laura Suarez, Jens-Christian Svenning, Ivana Svitková, Marek Svitok, Miroslav Svoboda, Emily Swaine, Nathan Swenson, Marcelo Tabarelli, Kentaro Takagi, Ulrike Tappeiner, Rubén Tarifa, Simon Tauugourdeau, Cagatay Tavsanoglu, Mariska te Beest, Leho Tedersoo, Nelson Thiffault, Dominik Thom, Evert Thomas, Ken Thompson, Peter E. Thornton, Wilfried Thuiller, Lubomír Tichý, David Tissue, Mark G. Tjoelker, David Yue Phin Tng, Joseph Tobias, Péter Török, Tonantzin Tarin, José M. Torres-Ruiz, Béla Tóthmérész, Martina Treurnicht, Valeria Trivellone, Franck Trolliet, Volodymyr Trotsiuk, James L. Tsakalos, Ioannis Tsiripidis, Niklas Tysklind, Toru Umehara, Vladimir Usoltsev, Matthew Vadeboncoeur, Jamil Vaezi, Fernando Valladares, Jana Vamosi, Peter M. van Bodegom, Michiel van Breugel, Elisa Van Cleemput, Martine van de Weg, Stephni van der Merwe, Fons van der Plas, Masha T. van der Sande, Mark van Kleunen, Koenraad Van Meerbeek, Mark Vanderwel, Kim André Vanselow, Angelica Vårhammar, Laura Varone, Maribel Yesenia Vasquez Valderrama, Kiril Vassilev, Mark Vellend, Erik J. Veneklaas, Hans Verbeeck, Kris Verheyen, Alexander Vibrans, Ima Vieira, Jaime Villacís, Cyrille Violle, Pandi Vivek, Katrin Wagner, Matthew Waldram, Anthony Waldron, Anthony P. Walker, Martyn Waller, Gabriel Walther, Han Wang, Feng Wang, Weiqi Wang, Harry Watkins, James Watkins, Ulrich Weber, James T. Weedon, Liping Wei, Patrick Weigelt, Evan Weiher, Aidan W. Wells, Camilla Wellstein, Elizabeth Wenk, Mark Westoby, Alana Westwood, Philip John White, Mark Whitten, Mathew Williams, Daniel E. Winkler, Klaus Winter, Chevonne Womack, Ian J. Wright, S. Joseph Wright, Justin Wright, Bruno X. Pinho, Fabiano Ximenes, Toshihiro Yamada, Keiko Yamaji, Ruth Yanai, Nikolay Yankov, Benjamin Yguel, Kátia Janaina Zanini, Amy E. Zanne, David Zelený, Yun-Peng Zhao, Jingming Zheng, Ji Zheng, Kasia Ziemińska, Chad R. Zirbel, Georg Zizka, Irié Casimir Zo-Bi, Gerhard Zotz, Christian Wirth.Max Planck Institute for Biogeochemistry; Max Planck Society; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig; International Programme of Biodiversity Science (DIVERSITAS); International Geosphere-Biosphere Programme (IGBP); Future Earth; French Foundation for Biodiversity Research (FRB); GIS ‘Climat, Environnement et Société'.http://wileyonlinelibrary.com/journal/gcbhj2021Plant Production and Soil Scienc

Agroforestry on post-mining restoration : a challenge beyond plant mixture systems

L'agroforesterie est un système dynamique d'aménagement écologique des ressources naturelles renouvelables, qui en intégrant les espèces ligneuses aux champs agricoles, fermes et autres paysages, diversifie, augmente la production et engendre des bénéfices socioéconomiques et environnementaux. En tant que solution pour la fourniture des services écosystémiques, son application à la restauration des écosystèmes dégradés, endommagés ou détruits devient très importante. Les terres dégradées, endommagées ou détruites (3-D) par l’exploitation minière sont caractérisées par un sol de faible fertilité et parfois des niveaux élevés des contaminants. Ces conditions les rendent difficile l'obtention d'un avantage à court terme de l'agroforesterie en comparaison aux terres arables, mais sa principale fonction restaurative consistant à rétablir les services écosystémiques et à accroître la résilience peut être bénéfique à long terme. Le défi consiste à développer la meilleure stratégie pour accélérer la productivité des plantes tout en améliorant le sol et l’écosystème grâce à une combinaison des techniques d’ingénierie écologique pour la biorestauration des milieux miniers. Nous explorons ici le mélange de plantes, d’inoculation microbienne et d’amendement en biochar, dans un système agroforestier ligneux-herbacé. L’objectif est de trouver le meilleur scénario de biorestauration à partir des effets combinés de mélange de plantes et d’autres facteurs écologiques connexes. Des recherches antérieures sur l'agroforesterie et la restauration ont été révisées à travers le monde entier, y compris l’application du concept agroforestier en biorestauration des terres post-minières. La stratégie de restauration connue dans un milieu donné ne constitue pas une solution universelle. Ainsi, l'identification de tout aspect important des travaux antérieurs sur la restauration et l'agroforesterie est cruciale. La stratégie de mélange des plantes est un facteur important dans les processus de succession. Dans cette recherche, nous avons appliqué le concept de parcelles de Nelder modifié pour la combinaison d'espèces de plantes dans une expérience en serre sur les stériles et les résidus fins afin d'explorer l'interaction au début de la plantation. Nous avons aussi appliqué l’inoculum microbien et le biochar sur le mélange de plantes dans des essais en serre et sur le terrain sur les stériles et les résidus fins comme matériau de sol d’un site post-extraction de l’or. La performance de la co-plantation de quatre espèces ligneuses (Alnus viridis (Chaix) DC. ssp. crispa (Aiton) Turrill, Picea glauca (Moench) Voss, Populus tremuloides Michx. et Salix arbusculoides Andersson) avec les les espèces de plantes herbacées (Avena sativa L., Festuca rubra L. et Trifolium repens L.) a été évaluée. Le mélange de plantes est un principe très important dans les pratiques de restauration, étant donné son rôle connu pour augmenter la biodiversité et la diversité fonctionnelle dans le système écologique durable. Bien que la stratégie de mélange ait été rarement explorée, nous avons constaté que la combinaison des espèces avait un effet neutre (ni avantages, ni inconvénients) par rapport à une seule espèce dans l’expérience de parcelles de Nelder. En même temps, l'effet positif de la densité suggérait que l'amélioration du microclimat avait joué un rôle dans la croissance précoce des plantations. L'essai sur le terrain confirme l'effet positif de la modification du microclimat sur la productivité des plantes lorsque la densité de plantation est élevée. Le compromis sur la concurrence des plantes a montré que la densité la plus élevée ne constitue pas nécessairement une condition optimale pour la productivité des plantes. L'effet d'interaction du biochar et du traitement d'inoculation montre l'intérêt de ce traitement, mais l'impact varie selon la densité de plantation. La densité de plantation a été démontrée comme le facteur le plus important pour générer l'effet positif net. Nous suggérons que le mécanisme était corrélé à l'amélioration du microclimat par la conservation de l'eau des plantes du sol et l'amélioration de l'activité microbienne par rapport à la modification de la température du sol. Par conséquent, mettre l'accent sur l'amélioration du microclimat, ainsi que sur d'autres facteurs combinés, y compris l'inoculation microbienne et l'amendement du biochar, est très important pour accélérer les processus de restauration.Agroforestry is a dynamic system of ecological management of renewable natural resources, which by integrating woody species into agricultural fields, farms and other landscapes, diversifies and sustains production for increased socio-economic and environmental benefits. As a solution for the provision of ecosystem services, its application to the restoration of degraded damaged, or destroyed ecosystems becomes very important. Degraded, damaged, or destroyed (3-D) lands by mining is characterized by low fertility soil and sometimes high levels of contaminants. These conditions make them difficult to obtain a short-term advantage from agroforestry compared to arable lands, but its main restorative function of restoring ecosystem services and increasing resilience can be beneficial in the long term. The challenge is to develop the best strategy to accelerate plant productivity while improving the soil and the ecosystem through a combination of ecological engineering techniques for bioremediation of mining areas. Here we explore the mixture of plants, microbial inoculation, and biochar amendment, in a woody-herbaceous agroforestry system. The goal is to find the best bioremediation scenario from the combined effects of mixing plants and other related ecological factors. Previous research on agroforestry and restoration has been reviewed worldwide, including the application of the agroforestry concept in bioremediation of post-mining land area. The known restoration strategy in a given environment is not a universal solution. Thus, the identification of any important aspect of previous work on restoration and agroforestry is crucial. The strategy of mixing plants is an important factor in the successional process. But a statistical accounting of plant-plant interactions and adaptation to multi-species conditions is hard to achieve in field experiments; trials under controlled conditions can distinguish effects of planting density and species interactions in the early stages of plant establishment. In this research, we applied the concept of modified Nelder plots for the combination of plant species in a greenhouse experiment on waste rock and fine tailing to explore the interaction at the start of planting. We also applied microbial inoculum and biochar to the plant mixture in greenhouse and field tests on waste rock and fine tailing as soil material on a post-gold mining site. The performance of the co-planting of four woody species: green alder (Alnus viridis (Chaix) DC. ssp. crispa (Aiton) Turrill); white spruce (Picea glauca (Moench) Voss); trembling aspen (Populus tremuloides Michaux); and littletree willow (Salix arbusculoides Andersson) with the herbaceous plant species: oat (Avena sativa L.); red fescue (Festuca rubra L.) and white clover (Trifolium repens L.) was evaluated. Mixing plants is a very important principle in restoration practices, given its known role to increase biodiversity and functional diversity in the sustainable ecological system. Although the plant mixing strategy has been rarely explored, we have found no mixture provided advantages for both species in paired combinations. At the same time, the positive effect of the density on plant growth suggested that the microclimate improvement had played a role in the early growth of the plantations. The field trial confirms the positive effect of the microclimate modification on plant productivity in higher planting density. The trade-off on plant competition has shown, however, that the highest density does not necessarily show an optimal condition for plant productivity. The interaction effect of biochar and inoculation treatment shows the benefit of this treatment, although the impact varies according to the density of planting. The plantation density was shown as the most important factor in generating the net positive effect. We suggest that the mechanism was correlated with the microclimate improvement through soil plant water conservation and microbial activity enhancement over soil temperature modification. Hence, putting emphasis on microclimate improvement, along with other combined factors including microbial inoculation and biochar amendment is very important for accelerating the restoration processe

The Effect of Biochar Amendment, Microbiome Inoculation, Crop Mixture and Planting Density on Post-Mining Restoration

Ecological restoration with a multispecies and multifunctional approach can accelerate the re-establishment of numerous ecosystem services. The challenges with land that is degraded, damaged, or destroyed post-mining are the low productivity of soil and the high potential for contaminants. Herein, we evaluated the multispecies and multifunctional approach to restoration strategy through a mixture of woody and herbaceous species, microsymbiont and biochar amendments, and plant spacing. The experiments were conducted using greenhouse and field trials located in Quebec, Canada. We used a mixture of tree species (Alnus viridis (Chaix) DC. ssp. crispa (Aiton) Turrill, Picea glauca (Moench) Voss, Populus tremuloides Michx. and Salix arbusculoides Andersson) and herbaceous species (Avena sativa L., Festuca rubra L. and Trifolium repens L.) on two types of gold-mine waste materials (fine tailing and waste rock). The biochar amendment and microbial inoculation were applied on both greenhouse and field trials. We found both positive and negative effects of plant spacing, biochar amendment and inoculation depending on their interactions. The net positive effect was shown by combining high plantation density, biochar, and inoculation factors on Alnus viridis ssp. crispa. Overall, plantation density was shown to be the most important factor in generating the net positive effect. We suggest that the mechanism was correlated with the improvement in microclimate through soil plant water conservation and microbial activity enhancement over soil temperature modification. Hence, we propose to put emphasis on microclimate improvement for accelerating the restoration processes, along with other combined factors, including microbial inoculation and biochar amendment

Tree establishment on post-mining waste soils: species, density, and mixture effects

Tree establishment to restore degraded boreal post-mining lands is challenged by low soil productivity, a harsh microclimate, and potentially high contaminant levels. The use of mixed vegetation can facilitate the microclimate but increase competition for soil resources. A statistical accounting of plant–plant interactions and adaptation to multispecies conditions is hard to achieve in field experiments; trials under controlled conditions can distinguish effects of planting density and species interactions in the early stages of plant establishment. A greenhouse trial was established in containers (“mesocosms”) with waste rock or fine tailings from gold mines. Pregerminated (1-week-old) seedlings (Alnus viridis subsp. crispa, Picea glauca, Populus tremuloides, Salix arbusculoides) were planted using a Nelder density gradient design, modified for species combinations. A relative competition effect was estimated as a competitiveness index for each species combination, calculated as a ratio of α coefficients in the Holliday growth equation. The specific leaf area (SLA) was measured to indicate plant water stress adaptation. All species grew better in monoculture on fine tailings, while only P. tremuloides grew better in all mixtures on waste rock. Although net positive effects of density on SLA increment during early growth suggested microclimate improvement on fine tailings, no mixture provided advantages for both species in paired combinations

BAAD: a Biomass And Allometry Database for woody plants

CABI:20153174020Understanding how plants are constructed - i.e., how key size dimensions and the amount of mass invested in different tissues varies among individuals - is essential for modeling plant growth, carbon stocks, and energy fluxes in the terrestrial biosphere. Allocation patterns can differ through ontogeny, but also among coexisting species and among species adapted to different environments. While a variety of models dealing with biomass allocation exist, we lack a synthetic understanding of the underlying processes. This is partly due to the lack of suitable data sets for validating and parameterizing models. To that end, we present the Biomass And Allometry Database (BAAD) for woody plants. The BAAD contains 259634 measurements collected in 176 different studies, from 21084 individuals across 678 species. Most of these data come from existing publications. However, raw data were rarely made public at the time of publication. Thus, the BAAD contains data from different studies, transformed into standard units and variable names. The transformations were achieved using a common workflow for all raw data files. Other features that distinguish the BAAD are: (i) measurements were for individual plants rather than stand averages; (ii) individuals spanning a range of sizes were measured; (iii) plants from 0.01-100 m in height were included; and (iv) biomass was estimated directly, i.e., not indirectly via allometric equations (except in very large trees where biomass was estimated from detailed sub-sampling). We included both wild and artificially grown plants. The data set contains the following size metrics: total leaf area; area of stem cross-section including sapwood, heartwood, and bark; height of plant and crown base, crown area, and surface area; and the dry mass of leaf, stem, branches, sapwood, heartwood, bark, coarse roots, and fine root tissues. We also report other properties of individuals (age, leaf size, leaf mass per area, wood density, nitrogen content of leaves and wood), as well as information about the growing environment (location, light, experimental treatment, vegetation type) where available. It is our hope that making these data available will improve our ability to understand plant growth, ecosystem dynamics, and carbon cycling in the world's vegetation