Future global productivity will be affected by plant trait response to climate

Madani, Nima; Kimball, J. S.; Ballantyne, Ashley P.; Affleck, David L. R.; Bodegom, Peter M. van; Reich, Peter B.; Kattge, Jens; Sala, Anna; Nazeri, Mona; Jones, Matthew O.; Zhao, Maosheng; Running, Steven W.

doi:10.1038/s41598-018-21172-9

Cited by 127 publications

(116 citation statements)

References 73 publications

Supporting

Mentioning

106

Contrasting

Order By: Relevance

“…Changes in the community functional trait composition may also imply changes in key aspects of ecosystem functioning such as nutrient, carbon and water cycling. Therefore, understanding past and current responses of community-level traits has the potential to provide valuable insights into tropical forest resilience against environmental changes and offer a promising avenue for a better understanding of ecosystem functioning (Madani et al 2018). While analysing biodiversity responses to environmental changes at the community level is clearly desirable, it is a challenging task for tropical forests in particular given their high diversity, relative paucity of trait data (e.g.…”

Section: Introductionmentioning

confidence: 99%

Drier tropical forests are susceptible to functional changes in response to a long‐term drought

et al. 2019

View full text Add to dashboard Cite

Climatic changes have profound effects on the distribution of biodiversity, but untangling the links between climatic change and ecosystem functioning is challenging, particularly in high diversity systems such as tropical forests. Tropical forests may also show different responses to a changing climate, with baseline climatic conditions potentially inducing differences in the strength and timing of responses to droughts. Trait‐based approaches provide an opportunity to link functional composition, ecosystem function and environmental changes. We demonstrate the power of such approaches by presenting a novel analysis of long‐term responses of different tropical forest to climatic changes along a rainfall gradient. We explore how key ecosystem's biogeochemical properties have shifted over time as a consequence of multi‐decadal drying. Notably, we find that drier tropical forests have increased their deciduous species abundance and generally changed more functionally than forests growing in wetter conditions, suggesting an enhanced ability to adapt ecologically to a drying environment.

show abstract

Section: Introductionmentioning

confidence: 99%

Drier tropical forests are susceptible to functional changes in response to a long‐term drought

et al. 2019

View full text Add to dashboard Cite

show abstract

“…try-db.org/). The applications of the database range from functional and community ecology, plant geography, species distribution, and vegetation models parameterizations [37][38][39][40].…”

Section: Global Plant Traitsmentioning

confidence: 99%

Global Estimation of Biophysical Variables from Google Earth Engine Platform

et al. 2018

Self Cite

View full text Add to dashboard Cite

This paper proposes a processing chain for the derivation of global Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fraction Vegetation Cover (FVC), and Canopy water content (CWC) maps from 15-years of MODIS data exploiting the capabilities of the Google Earth Engine (GEE) cloud platform. The retrieval chain is based on a hybrid method inverting the PROSAIL radiative transfer model (RTM) with Random forests (RF) regression. A major feature of this work is the implementation of a retrieval chain exploiting the GEE capabilities using global and climate data records (CDR) of both MODIS surface reflectance and LAI/FAPAR datasets allowing the global estimation of biophysical variables at unprecedented timeliness. We combine a massive global compilation of leaf trait measurements (TRY), which is the baseline for more realistic leaf parametrization for the considered RTM, with large amounts of remote sensing data ingested by GEE. Moreover, the proposed retrieval chain includes the estimation of both FVC and CWC, which are not operationally produced for the MODIS sensor. The derived global estimates are validated over the BELMANIP2.1 sites network by means of an inter-comparison with the MODIS LAI/FAPAR product available in GEE. Overall, the retrieval chain exhibits great consistency with the reference MODIS product (R 2 = 0.87, RMSE = 0.54 m 2 /m 2 and ME = 0.03 m 2 /m 2 in the case of LAI, and R 2 = 0.92, RMSE = 0.09 and ME = 0.05 in the case of FAPAR). The analysis of the results by land cover type shows the lowest correlations between our retrievals and the MODIS reference estimates (R 2 = 0.42 and R 2 = 0.41 for LAI and FAPAR, respectively) for evergreen broadleaf forests. These discrepancies could be attributed mainly to different product definitions according to the literature. The provided results proof that GEE is a suitable high performance processing tool for global biophysical variable retrieval for a wide range of applications.

show abstract

“…To date, there has been a focus on species mean trait values; however, for species to be able to adapt to climate change they require, heritable, intraspecific trait variation. Yet, a few studies focus on intraspecific trait variation and if these traits are genetically determined (e.g., Aranda et al, ; Schreiber, Hacke, & Hamann, ; Hajek, Kurjak, von Wühlisch, Delzon, & Schuldt,; Madani et al, ). There is growing appreciation of the importance of intraspecific variation in functional and complex traits in providing the capacity to adapt to climate change.…”

Section: Introductionmentioning

confidence: 99%

“…Yet, a few studies focus on intraspecific trait variation and if these traits are genetically determined (e.g., Aranda et al, 2014;Schreiber, Hacke, & Hamann, 2015;Hajek, Kurjak, von Wühlisch, Delzon, & Schuldt,2016;Madani et al, 2018). There is growing appreciation of the importance of intraspecific variation in functional and complex traits in providing the capacity to adapt to climate change.…”

Section: Introductionmentioning

confidence: 99%

“…Functional traits, by definition, are indicative of their relationship to the environment (Shipley et al, 2016), and population differentiation along climate gradients can be used to quantify the relative contribution of climate variables to patterns of trait differentiation (Madani et al, 2018). But these outputs would be unable to estimate the relative trait responsiveness to selection pressures.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Plant functional traits differ in adaptability and are predicted to be differentially affected by climate change

Ahrens

Andrew

Mazanec³

et al. 2019

Ecology and Evolution

View full text Add to dashboard Cite

1. Climate change is testing the resilience of forests worldwide pushing physiological tolerance to climatic extremes. Plant functional traits have been shown to be adapted to climate and have evolved patterns of trait correlations (similar patterns of distribution) and coordinations (mechanistic trade-off). We predicted that traits would differentiate between populations associated with climatic gradients, suggestive of adaptive variation, and correlated traits would adapt to future climate scenarios in similar ways. 2. We measured genetically determined trait variation and described patterns of correlation for seven traits: photochemical reflectance index (PRI), normalized difference vegetation index (NDVI), leaf size (LS), specific leaf area (SLA), δ 13 C (integrated water-use efficiency, WUE), nitrogen concentration (N CONC ), and wood density (WD). All measures were conducted in an experimental plantation on 960 trees sourced from 12 populations of a key forest canopy species in southwestern Australia.3. Significant differences were found between populations for all traits. Narrowsense heritability was significant for five traits (0.15-0.21), indicating that natural selection can drive differentiation; however, SLA (0.08) and PRI (0.11) were not significantly heritable. Generalized additive models predicted trait values across the landscape for current and future climatic conditions (>90% variance). The percent change differed markedly among traits between current and future predictions (differing as little as 1.5% (δ 13 C) or as much as 30% (PRI)). Some trait correlations were predicted to break down in the future (SLA:N CONC , δ 13 C:PRI, and N CONC :WD). 4. Synthesis: Our results suggest that traits have contrasting genotypic patterns and will be subjected to different climate selection pressures, which may lower the working optimum for functional traits. Further, traits are independently associated with different climate factors, indicating that some trait correlations may be | 233 AHRENS Et Al.

show abstract

Future global productivity will be affected by plant trait response to climate

Cited by 127 publications

References 73 publications

Drier tropical forests are susceptible to functional changes in response to a long‐term drought

Drier tropical forests are susceptible to functional changes in response to a long‐term drought

Global Estimation of Biophysical Variables from Google Earth Engine Platform

Plant functional traits differ in adaptability and are predicted to be differentially affected by climate change

Contact Info

Product

Resources

About