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Search: WFRF:(Fernandes C) > Agricultural Sciences

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1.
  • Tavares, Julia, et al. (author)
  • Basin-wide variation in tree hydraulic safety margins predicts the carbon balance of Amazon forests
  • 2023
  • In: Nature. - : Springer Nature. - 0028-0836 .- 1476-4687. ; 617:7959, s. 111-117
  • Journal article (peer-reviewed)abstract
    • Tropical forests face increasing climate risk(1,2), yet our ability to predict their response to climate change is limited by poor understanding of their resistance to water stress. Although xylem embolism resistance thresholds (for example, ?(50)) and hydraulic safety margins (for example, HSM50) are important predictors of drought-induced mortality risk(3-5), little is known about how these vary across Earth's largest tropical forest. Here, we present a pan-Amazon, fully standardized hydraulic traits dataset and use it to assess regional variation in drought sensitivity and hydraulic trait ability to predict species distributions and long-term forest biomass accumulation. Parameters ?(50) and HSM50 vary markedly across the Amazon and are related to average long-term rainfall characteristics. Both ?(50) and HSM50 influence the biogeographical distribution of Amazon tree species. However, HSM50 was the only significant predictor of observed decadal-scale changes in forest biomass. Old-growth forests with wide HSM50 are gaining more biomass than are low HSM(50 )forests. We propose that this may be associated with a growth-mortality trade-off whereby trees in forests consisting of fast-growing species take greater hydraulic risks and face greater mortality risk. Moreover, in regions of more pronounced climatic change, we find evidence that forests are losing biomass, suggesting that species in these regions may be operating beyond their hydraulic limits. Continued climate change is likely to further reduce HSM50 in the Amazon(6,7), with strong implications for the Amazon carbon sink.
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2.
  • Via, Allegra, et al. (author)
  • Best practices in bioinformatics training for life scientists
  • 2013
  • In: Briefings in Bioinformatics. - : Oxford University Press (OUP). - 1467-5463 .- 1477-4054. ; 14:5, s. 528-537
  • Journal article (peer-reviewed)abstract
    • The mountains of data thrusting from the new landscape of modern high-throughput biology are irrevocably changing biomedical research and creating a near-insatiable demand for training in data management and manipulation and data mining and analysis. Among life scientists, from clinicians to environmental researchers, a common theme is the need not just to use, and gain familiarity with, bioinformatics tools and resources but also to understand their underlying fundamental theoretical and practical concepts. Providing bioinformatics training to empower life scientists to handle and analyse their data efficiently, and progress their research, is a challenge across the globe. Delivering good training goes beyond traditional lectures and resource-centric demos, using interactivity, problem-solving exercises and cooperative learning to substantially enhance training quality and learning outcomes. In this context, this article discusses various pragmatic criteria for identifying training needs and learning objectives, for selecting suitable trainees and trainers, for developing and maintaining training skills and evaluating training quality. Adherence to these criteria may help not only to guide course organizers and trainers on the path towards bioinformatics training excellence but, importantly, also to improve the training experience for life scientists.
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journal article (2)
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Malhi, Yadvinder (1)
Baker, Timothy R. (1)
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Meir, Patrick (1)
Lewis, Simon (1)
Ferreira, Leandro (1)
Via, Allegra (1)
Budd, Aidan (1)
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Fernandes, Pedro L. (1)
Menor, Imma Oliveras (1)
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Tavares, Julia (1)
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