Dataset Information

Are trait-growth models transferable? Predicting multi-species growth trajectories between ecosystems using plant functional traits.

ABSTRACT: Plant functional traits are increasingly used to generalize across species, however few examples exist of predictions from trait-based models being evaluated in new species or new places. Can we use functional traits to predict growth of unknown species in different areas? We used three independently collected datasets, each containing data on heights of individuals from non-resprouting species over a chronosquence of time-since-fire sites from three ecosystems in south-eastern Australia. We examined the influence of specific leaf area, woody density, seed size and leaf nitrogen content on three aspects of plant growth; maximum relative growth rate, age at maximum growth and asymptotic height. We tested our capacity to perform out-of-sample prediction of growth trajectories between ecosystems using species functional traits. We found strong trait-growth relationships in one of the datasets; whereby species with low SLA achieved the greatest asymptotic heights, species with high leaf-nitrogen content achieved relatively fast growth rates, and species with low seed mass reached their time of maximum growth early. However these same growth-trait relationships did not hold across the two other datasets, making accurate prediction from one dataset to another unachievable. We believe there is evidence to suggest that growth trajectories themselves may be fundamentally different between ecosystems and that trait-height-growth relationships may change over environmental gradients.

SUBMITTER: Thomas FM

PROVIDER: S-EPMC5423618 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Are trait-growth models transferable? Predicting multi-species growth trajectories between ecosystems using plant functional traits.

Thomas Freya M FM Vesk Peter A PA

PloS one 20170509 5

Plant functional traits are increasingly used to generalize across species, however few examples exist of predictions from trait-based models being evaluated in new species or new places. Can we use functional traits to predict growth of unknown species in different areas? We used three independently collected datasets, each containing data on heights of individuals from non-resprouting species over a chronosquence of time-since-fire sites from three ecosystems in south-eastern Australia. We exa ...[more]

PMID: 28486535

Similar Datasets

Project description:A genome-wide association study (GWAS) for 10 yield and yield component traits was conducted using an association panel comprising 225 diverse spring wheat genotypes. The panel was genotyped using 10,904 SNPs and evaluated for three years (2016-2019), which constituted three environments (E1, E2 and E3). Heritability for different traits ranged from 29.21 to 97.69%. Marker-trait associations (MTAs) were identified for each trait using data from each environment separately and also using BLUP values. Four different models were used, which included three single trait models (CMLM, FarmCPU, SUPER) and one multi-trait model (mvLMM). Hundreds of MTAs were obtained using each model, but after Bonferroni correction, only 6 MTAs for 3 traits were available using CMLM, and 21 MTAs for 4 traits were available using FarmCPU; none of the 525 MTAs obtained using SUPER could qualify after Bonferroni correction. Using BLUP, 20 MTAs were available, five of which also figured among MTAs identified for individual environments. Using mvLMM model, after Bonferroni correction, 38 multi-trait MTAs, for 15 different trait combinations were available. Epistatic interactions involving 28 pairs of MTAs were also available for seven of the 10 traits; no epistatic interactions were available for GNPS, PH, and BYPP. As many as 164 putative candidate genes (CGs) were identified using all the 50 MTAs (CMLM, 3; FarmCPU, 9; mvLMM, 6, epistasis, 21 and BLUP, 11 MTAs), which ranged from 20 (CMLM) to 66 (epistasis) CGs. In-silico expression analysis of CGs was also conducted in different tissues at different developmental stages. The information generated through the present study proved useful for developing a better understanding of the genetics of each of the 10 traits; the study also provided novel markers for marker-assisted selection (MAS) to be utilized for the development of wheat cultivars with improved agronomic traits.Supplementary informationThe online version contains supplementary material available at 10.1007/s11032-021-01240-1.

Project description:The concept of ‘ecosystem service’ has gained momentum in the twenty-first century to bridge the gap between human–nature interactions. However, the challenge remains to map the flow of ecosystem services (ES) for their efficient management. Among the multiple existing methods, biophysical assessments provide better knowledge of the state of the ecosystem and its mapping for complimentary services. Trait–service linkage is one of the tools to reliably link biodiversity with ES if we better understand the role functional traits play in the underlying ecosystem processes. In this paper, we have performed a bibliometric analysis of published literature on ES and plant functional traits to identify the current state of knowledge on trait–service linkage, biases, research gaps, and challenges. There was a skewed geographical basis for trait–service linkage studies; most studies were conducted in Europe and North America. The majority of the research focused on supporting and regulating ES, mainly carbon sequestration, biomass production, and climate regulation, using a particular set of vegetative traits, such as leaf, root, and plant height, and ignored most regeneration traits, except for a few flower traits. A matrix to quantify the association between ES and selected plant traits (specific leaf area, leaf dry matter content, leaf area, leaf nitrogen content, vegetation height, wood density, canopy density, root length, root density, flowering time, flower color and flower size) revealed that the two leaf traits (specific leaf area and leaf dry matter content) in the linkage have contrasting associations with multiple ES. The study illustrated that there is still a considerable research gap in linking plant traits with essential ES (biomass production, climate and water regulation). Thus, suggest future studies on ES should focus more on trait–service linkage across major ecosystems to underpin key ecosystem processes for better sustenance of ES and human well-being. Supplementary Information The online version contains supplementary material available at 10.1007/s44177-023-00048-2.

Dataset Information

Are trait-growth models transferable? Predicting multi-species growth trajectories between ecosystems using plant functional traits.

Publications

Are trait-growth models transferable? Predicting multi-species growth trajectories between ecosystems using plant functional traits.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets