Engineering topics

Wright, Ian J.

Publications and source records attributed to Wright, Ian J..

5 records

DOE OSTI2022

The global spectrum of plant form and function: enhanced species-level trait dataset

Here we provide the ‘Global Spectrum of Plant Form and Function Dataset’, containing species mean values for six vascular plant traits. Together, these traits –plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass – define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Convergence in phosphorus constraints to photosynthesis in forests around the world

Tropical forests take up more carbon (C) from the atmosphere per annum by photosynthesis than any other type of vegetation. Phosphorus (P) limitations to C uptake are paramount for tropical and subtropical forests around the globe. Yet the generality of photosynthesis-P relationships underlying these limitations are in question, and hence are not represented well in terrestrial biosphere models. Here we demonstrate the dependence of photosynthesis and underlying processes on both leaf N and P concentrations. The regulation of photosynthetic capacity by P was similar across four continents. Implementing P constraints in the ORCHIDEE-CNP model, gross photosynthesis was reduced by 36% across the tropics and subtropics relative to traditional N constraints and unlimiting leaf P. Our results provide a quantitative relationship for the P dependence for photosynthesis for the front-end of global terrestrial C models that is consistent with canopy leaf measurements.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Rising CO 2 and warming reduce global canopy demand for nitrogen

Nitrogen (N) limitation has been considered as a constraint on terrestrial carbon uptake in response to rising CO 2 and climate change. By extension, it has been suggested that declining carboxylation capacity (V cmax ) and leaf N content in enhanced-CO 2 experiments and satellite records signify increasing N limitation of primary production. We predicted Vcmax using the coordination hypothesis and estimated changes in leaf-level photosynthetic N for 1982–2016 assuming proportionality with leaf-level V cmax at 25°C. The whole-canopy photosynthetic N was derived using satellite-based leaf area index (LAI) data and an empirical extinction coefficient for V cmax , and converted to annual N demand using estimated leaf turnover times. The predicted spatial pattern of V cmax shares key features with an independent reconstruction from remotely sensed leaf chlorophyll content. Predicted leaf photosynthetic N declined by 0.27% yr -1 , while observed leaf (total) N declined by 0.2–0.25% yr -1 . Predicted global canopy N (and N demand) declined from 1996 onwards, despite increasing LAI. Leaf-level responses to rising CO 2 , and to a lesser extent temperature, may have reduced the canopy requirement for N by more than rising LAI has increased it. This finding provides an alternative explanation for declining leaf N that does not depend on increasing N limitation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Eco-evolutionary optimality as a means to improve vegetation and land-surface models

Global vegetation and land-surface models embody interdisciplinary scientific understanding of the behaviour of plants and ecosystems, and are indispensable to project the impacts of environmental change on vegetation and the interactions between vegetation and climate. Furthermore, systematic errors and persistently large differences among carbon and water cycle projections by different models highlight the limitations of current process formulations. In this review, focusing on core plant functions in the terrestrial carbon and water cycles, we show how unifying hypotheses derived from eco-evolutionary optimality (EEO) principles can provide novel, parameter-sparse representations of plant and vegetation processes. We present case studies that demonstrate how EEO generates parsimonious representations of core, leaf-level processes that are individually testable and supported by evidence. EEO approaches to photosynthesis and primary production, dark respiration and stomatal behaviour are ripe for implementation in global models. EEO approaches to other important traits, including the leaf economics spectrum and applications of EEO at the community level are active research areas. Independently tested modules emerging from EEO studies could profitably be integrated into modelling frameworks that account for the multiple time scales on which plants and plant communities adjust to environmental change.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Organizing principles for vegetation dynamics

Understanding vegetation dynamics is very challenging because of the multitude of contributing processes at 64widely different spatial and temporal scales. In this Perspective we propose that understanding of vegetation dynamics can be improved, permitting better predictions, based on organizing principles that constrain plant and ecosystem be haviour: natural selection, self-organization, and entropy maximization. Although these ideas are increasingly used,a limited common understanding of their theoretical basis has prevented their full potential to be realized. We explain the power of natural selection-based optimality to predict photosynthesis and carbon allocation responses to multiple environmental drivers, and how individual plasticity leads to the predictable self-organization of forest canopies. We show how models of natural selection acting on a few key traits can generate realistic plant communities, and how entropy maximization can distinguish between stochastic and deterministic drivers of vegetation patterns. In combination with empirical exploration of patterns in plant functional variation, these principles can accelerate the development of dynamic vegetation models as well as trait-based ecology resting on strengthened theoretical and empirical foundations.

Geosciences↗