Resource-use efficiency drives overyielding via enhanced complementarity

Mason, Norman W. H.; Orwin, Kate H.; Lambie, Suzanne; Waugh, Deanne; Pronger, Jack; Carmona, Carlos P.; Mudge, Paul L.

doi:10.1007/s00442-020-04732-7

Cited by 22 publications

(27 citation statements)

References 48 publications

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“…Increasing biodiversity effects over time are known to occur in long‐term studies over time scales ranging from multiple years to decades 30,31 . On a shorter time scale, a recent study has shown that relative contributions of SE and CE to the NE changed over the course of a year in a grassland mixture 32 . However, considerably less is known about temporal changes of biodiversity effects over the course of a growing season in annual crop communities.…”

Section: Discussionmentioning

confidence: 99%

“…30,31 On a shorter time scale, a recent study has shown that relative contributions of SE and CE to the NE changed over the course of a year in a grassland mixture. 32 However, considerably less is known about temporal changes of biodiversity effects over the course of a growing season in annual crop communities. This study found an increase of the NE and its two additive components, the CE and SE, over the lifetime of an annual crop.…”

Section: Discussionmentioning

confidence: 99%

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Temporal dynamics of biodiversity effects and light‐use‐related traits in two intercropping systems

Engbersen

Stefan

Brooker

et al. 2021

J of Sust Agri & Env

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Introduction: Intercropping systems can be more productive than their respective monocultures and this positive net biodiversity effect is caused by complementarity and selection effects. While the complementarity effect is caused through resource partitioning or facilitation, the selection effect operates via the greater probability that a more diverse community contains a dominant and high-yielding species which will account for the majority of productivity in that community. Here, we investigated how light-use-related traits contribute to the net biodiversity effect via complementarity or selection effects and how these qrelationships change throughout an annual growing season. Materials and Methods:We conducted weekly destructive harvests to examine temporal dynamics of biodiversity effects in two crop mixtures (oat-lupin and oat-camelina) and their respective monocultures. We linked the biodiversity effects to traits related to light use (i.e., light interception, plant height, photosynthetic efficiency and photosynthetic capacity) and investigated how these relationships changed over time.Results: We found that the net biodiversity and selection effect increased over time in both mixtures, while complementarity effects increased only in the oat-lupin mixture.More intercepted light and taller plants in mixtures compared to monocultures positively contributed to biodiversity effects in both mixtures. Strategies for shade tolerance differed between the mixtures, that is, increased photosynthetic capacity and increased photosynthetic efficiency contributed to a positive net biodiversity effect in the oat-lupin and oat-camelina mixture, respectively. Conclusion:By linking the temporal dynamics of the net biodiversity effect and its two additive components to light-use-related traits in two different crop mixtures, this study demonstrates that complementary light use contributes to overyielding in intercropping systems. Such understanding is important for the design of effective intercropping systems and developing new crop cultivars suited to these environments.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Temporal dynamics of biodiversity effects and light‐use‐related traits in two intercropping systems

Engbersen

Stefan

Brooker

et al. 2021

J of Sust Agri & Env

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“…This encompasses the range of N rates applied across global agricultural systems (Cui et al., 2018; Zhang et al., 2015), and resulted in 126 plots. Each composition treatment was sown in 6 m × 54 m strips at standard rates (Mason et al, 2020), with N rate treatments applied to 6 m × 9 m plots within these. Nitrogen fertiliser was applied as urea after each harvest, with the amount split evenly across applications.…”

Section: Methodsmentioning

confidence: 99%

“…All plots also received lime (1.5 t/ha in October 2014, 0.4 t/ha in April 2015 and 0.5 t/ha in September 2015), and maintenance fertiliser (including potassium, phosphorus, sulphur, sodium, magnesium, boron, molybdenum and selenium) during the experiment. The experiment was managed as a cut-and-carry system (where biomass is regularly cut and removed), with harvest timings for each composition treatment based on biomass in the 200 kg N ha −1 year −1 treatment and best practice criteria (Mason et al, 2020). This resulted in plots being mowed to 5 cm height 14-18 times during the 2-year experiment, and for most plots, more N was removed than added in fertiliser (see Figure S1).…”

Section: Introductionmentioning

confidence: 99%

Relationships of plant traits and soil biota to soil functions change as nitrogen fertiliser rates increase in an intensively managed agricultural system

Orwin

Mason

Aalders

et al. 2020

Journal of Applied Ecology

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Because plant and soil systems are strongly inter‐linked, manipulating plant traits in intensively managed agricultural systems could be used to improve soil functioning and sustainability. However, we have little understanding of whether the impacts of plant traits on soil systems are modified by other management practices, such as fertiliser use. We tested whether relationships among plant traits, soil biota (microbes and nematodes) and soil functions (carbon and nitrogen (N) cycling) change with N fertiliser regime in a field‐based, intensively managed experiment with high biomass removal. The experiment consisted of seven plant species compositions crossed with six N fertiliser rates (0–500 kg N ha−1 year−1). Relationships among plant traits, soil biota and soil functions were often consistent across N fertiliser rates. However, the relationship of percentage N2 fixer to qCO2 shifted from negative to neutral as N rates increased, and the slope of several relationships of plant traits to N cycling indicators declined when >200 kg N ha−1 year−1 was added. The negative relationship of the fungal: bacterial ratio to N cycling indicators also became neutral when > 200 kg N ha−1 year−1 was added, and the relationships of bacterivore abundance and the plant parasitic index to respiration changed direction as N inputs increased. Some relationships of plant traits and soil biota to soil functions were in unexpected directions. This was sometimes associated with species‐specific effects and inconsistent trait trade‐offs within species. In general, conservative plant traits and fungal dominance were associated with low N cycling and cellulose paper decomposition rates, but high respiration rates. Nematode‐based variables were better predictors of some functions than microbial ones; their incorporation into plant trait research could improve predictive power and system understanding. Synthesis and applications. Manipulating plant community traits can modify soil functions in intensively managed systems, but may result in larger changes where fertiliser nitrogen inputs are relatively low. Improved modelling that integrates how plant community traits, species‐specific effects and management practices interact to determine soil functions will be required before managers can confidently predict the consequences of changing plant community traits.

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“…Niinemets et al, 2015), ontogenetically changing traits (Poorter et al, 2015; 4 Puglielli et al, 2021), or seasonally variable traits (e.g. Mason et al, 2020;Puglielli, 2019;Puglielli et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

An updated framework to account for inter-individual variability when quantifying phenotypic variation

Puglielli

Carmona

Varone

et al. 2021

Preprint

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In trait-based ecology, phenotypic variation (PVar) is often quantified with measures that express average differences between populations standardized in the range 0-1. A major problem with these measures is that they disregard the within-population trait variability. In addition, most of these measures cannot be decomposed across scales. This can alter their interpretation, thus limiting their applicability.To overcome these problems, we propose a new measure, the Phenotypic Dissimilarity Index (PhD) that is insensitive to the within-population interindividual trait variability. Likewise, PhD can be used to quantify PVar between individuals in a population while accounting for the PVar within individuals.Using simulated and real data, we showed that PhD index correctly quantifies PVar when the within-population trait variability is not negligible, as in many ecological studies. By accounting for within-population trait variability, the PhD index generally provides a more parsimonious quantification of PVar across an environmental gradient compared to other estimators.Traits sampled within a species have an inherent variability. Accounting for such variability is essential to understand species phenotypic responses to environmental cues. As such, the PhD index will provide ecologists with an asset to reliably quantify and compare PVar within and between species across environmental gradients at different scales. We also provide an R function to calculate the PhD index.

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Resource-use efficiency drives overyielding via enhanced complementarity

Cited by 22 publications

References 48 publications

Temporal dynamics of biodiversity effects and light‐use‐related traits in two intercropping systems

Temporal dynamics of biodiversity effects and light‐use‐related traits in two intercropping systems

Relationships of plant traits and soil biota to soil functions change as nitrogen fertiliser rates increase in an intensively managed agricultural system

An updated framework to account for inter-individual variability when quantifying phenotypic variation

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