Trait-based characterisation of cover plants’ light competition strategies for weed control in banana cropping systems in the French West Indies

Abstract Cover plants can be used as an ecological tool to manage weeds through competition for shared resources. Assessing the abilities of a large number of different plant species to compete for light remains difficult. Our aim was to characterise the light competition strategies of a range of species on the basis of a small number of traits related to both acquisition of light and interference abilities, to help farmers choose the most suitable cover plant species for banana cropping systems. Using a trait-based approach, we identified and measured the most representative plant morphological and functional traits to characterize the light acquisition strategies of 21 plant species including banana, cover plants, and weed species. We identified trade-offs between plant traits and light acquisition strategies. We identified light competition strategies by taking into account the aboveground interference abilities of plants as defined by their growth habit. There was a wide range of variations between species for all the traits. Two main trade-offs were identified: resource acquisition vs. conservation and carbohydrates investment in height vs. leaf area. Five traits selected in a multivariate analysis explained 80% of the variability of light acquisition strategies in our panel of species. These were related to plant morphology (height and plant crown width), light conversion efficiency (specific leaf area), carbohydrate allocation (aboveground leaf area ratio), and carbohydrates demand (aboveground biomass). The growth habit and the light acquisition strategies were related. The characterisation of plant species using functional traits enabled us to hypothesise three light acquisition strategies shaped by interference abilities in four light competing strategies. We propose a new method to characterise and distinguish species through their ability to acquire light and to interfere aboveground with their neighbours.

[1]  P. Reich,et al.  Biomass allocation to leaves, stems and roots: meta-analyses of interspecific variation and environmental control. , 2012, The New phytologist.

[2]  É. Malézieux,et al.  Mixing plant species in cropping systems: concepts, tools and models. A review , 2011, Agronomy for Sustainable Development.

[3]  Eric Garnier,et al.  A trait-based approach to comparative functional plant ecology: concepts, methods and applications for agroecology. A review , 2012, Agronomy for Sustainable Development.

[4]  E. Laca,et al.  Relating rice traits to weed competitiveness and yield: a path analysis , 2006, Weed Science.

[5]  M. Kropff,et al.  Clover as a cover crop for weed suppression in an intercropping design: I. Characteristics of several clover species , 2007 .

[6]  John R. Evans,et al.  Photosynthetic nitrogen-use efficiency of species that differ inherently in specific leaf area , 1998, Oecologia.

[7]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[8]  L. Aarssen,et al.  Conundrums of competitive ability in plants: what to measure? , 2002 .

[9]  Sean C. Thomas,et al.  The worldwide leaf economics spectrum , 2004, Nature.

[10]  Marc Dorel,et al.  Leaf area development strategies of cover plants used in banana plantations identified from a set of plant traits , 2016 .

[11]  M. Werger,et al.  Above-ground biomass investments and light interception of tropical forest trees and lianas early in succession. , 2007, Annals of botany.

[12]  E. Garnier,et al.  A standardized protocol for the determination of specific leaf area and leaf dry matter content , 2001 .

[13]  M. Werger,et al.  Canopy Structure and Photon Flux Partitioning Among Species in a Herbaceous Plant Community , 1995 .

[14]  Miguel A. Altieri,et al.  Green Agriculture: foundations for biodiverse, resilient and productive agricultural systems , 2012 .

[15]  S. Schnitzer,et al.  Lianas Have a Greater Competitive Effect Than Trees of Similar Biomass on Tropical Canopy Trees , 2012 .

[16]  S. Higgins,et al.  TRY – a global database of plant traits , 2011, Global Change Biology.

[17]  J. Oleksyn,et al.  Phenotypic correlates of the lianescent growth form: a review , 2013, Annals of botany.

[18]  J. Cornelissen,et al.  Evidence of the ‘plant economics spectrum’ in a subarctic flora , 2010 .

[19]  Mark Westoby,et al.  A leaf-height-seed (LHS) plant ecology strategy scheme , 1998, Plant and Soil.

[20]  Robert L. Zimdahl,et al.  Weed-Crop Competition: A Review , 2004 .

[21]  C. Violle,et al.  Let the concept of trait be functional , 2007 .

[22]  M. Westoby,et al.  Plant height and evolutionary games , 2003 .

[23]  Y. Iwasa,et al.  Tree height and crown shape, as results of competitive games , 1985 .

[24]  M. Westoby,et al.  Alternative height strategies among 45 dicot rain forest species from tropical Queensland, Australia , 2005 .

[25]  Marc Dorel,et al.  A trait-based characterization of cover plants to assess their potential to provide a set of ecological services in banana cropping systems , 2014 .

[26]  C. Violle,et al.  Allocation strategies and seed traits are hardly affected by nitrogen supply in 18 species differing in successional status , 2009 .

[27]  D. F. Cox,et al.  Statistical Procedures for Agricultural Research. , 1984 .

[28]  M. Altieri.  The ecological role of biodiversity in agroecosystems , 1999 .

[29]  Sabrina Gaba,et al.  Agroecological weed control using a functional approach: a review of cropping systems diversity , 2013, Agronomy for Sustainable Development.

[30]  K. Bradley Watkins,et al.  COVER CROPS IN SUSTAINABLE FOOD PRODUCTION , 2000 .

[31]  P. Reich,et al.  New handbook for standardised measurement of plant functional traits worldwide , 2013 .

[32]  Sabrina Gaba,et al.  Trajectories of weed communities explained by traits associated with species’ response to management practices , 2012 .

[33]  K. Thompson,et al.  Specific leaf area and leaf dry matter content as alternative predictors of plant strategies , 1999 .

[34]  N. Anten.  Optimal photosynthetic characteristics of individual plants in vegetation stands and implications for species coexistence. , 2004, Annals of botany.

[35]  M. Duru,et al.  Standing herbage mass: An integrated indicator of management practices for examining how fertility and defoliation regime shape the functional structure of species-rich grasslands , 2014 .

[36]  S. Snapp,et al.  Winter cover crops for local ecosystems: linking plant traits and ecosystem function , 2008 .

[37]  A. Ishida,et al.  Correlation between relative growth rate and specific leaf area requires associations of specific leaf area with nitrogen absorption rate of roots , 2008, The New phytologist.

[38]  Philippe Tixier,et al.  Model evaluation of cover crops, application to eleven species for banana cropping systems , 2011 .

[39]  Marie-Laure Navas,et al.  Can traits predict the competitive response of herbaceous Mediterranean species , 2005 .

[40]  Peter B. Reich,et al.  Leaf structure (specific leaf area) modulates photosynthesis–nitrogen relations: evidence from within and across species and functional groups , 1998 .

[41]  Nicolas Gross,et al.  Trade-off between root nitrogen acquisition and shoot nitrogen utilization across 13 co-occurring pasture grass species , 2009 .

[42]  John Vandermeer,et al.  The Ecology of Intercropping by John H. Vandermeer , 1989 .

[43]  Eric Garnier,et al.  PLANT FUNCTIONAL MARKERS CAPTURE ECOSYSTEM PROPERTIES DURING SECONDARY SUCCESSION , 2004 .

[44]  K. Cao,et al.  Contrasting cost–benefit strategy between lianas and trees in a tropical seasonal rain forest in southwestern China , 2010, Oecologia.