Gas exchange analysers exhibit large measurement error driven by internal thermal gradients

Photosynthetic capacity in middle-aged larch and spruce acclimates independently to experimental warming and elevated CO2

Photosynthetic acclimation to both warming and elevated CO2 of boreal trees remains a key uncertainty in modelling the response of photosynthesis to future climates. We investigated the impact of increased growth temperature and elevated CO2 on photosynthetic capacity (Vcmax and Jmax) in mature trees of two North American boreal conifers, tamarack and black spruce. We show that Vcmax and Jmax at a standard temperature of 25°C did not change with warming, while Vcmax and Jmax at their thermal optima (Topt) and growth temperature (Tg) increased. Moreover, Vcmax and Jmax at either 25°C, Topt or Tg decreased with elevated CO2. The Jmax/Vcmax ratio decreased with warming when assessed at both Topt and Tg but did not significantly vary at 25°C. The Jmax/Vcmax increased with elevated CO2 at either reference temperature. We found no significant interaction between warming and elevated CO2 on all traits. If this lack of interaction between warming and elevated CO2 on the Vcmax, Jmax and Jmax/Vcmax ratio is a general trend, it would have significant implications for improving photosynthesis representation in vegetation models. However, future research is required to investigate the widespread nature of this response in a larger number of species and biomes.

Regional differences in leaf evolution facilitate photosynthesis following severe drought

Characterizing physiological and anatomical changes that underlie rapid evolution following climatic perturbation can broaden our understanding of how climate change is affecting biodiversity. It can also provide evidence of cryptic adaptation despite stasis at higher levels of biological organization. Here, we compared evolutionary changes in populations of Mimulus cardinalis from historically different climates in the north and south of the species' range following an exceptional drought. We grew seeds produced from predrought ancestral plants alongside peak-drought descendants in a common glasshouse and exposed them to wet and dry conditions. Before the drought, northern ancestral populations expressed traits contributing to drought escape, while southern ancestral populations expressed drought avoidance. Following the drought, both regions evolved to reduce water loss and maintain photosynthesis in dry treatments (drought avoidance), but via different anatomical alterations in stomata, trichomes, and palisade mesophyll. Additionally, southern populations lost the ability to take advantage of wet conditions. These results reveal rapid evolution towards drought avoidance at an anatomical level following an exceptional drought, but suggest that differences in the mechanisms between regions incur different trade-offs. This sheds light on the importance of characterizing underlying mechanisms for downstream life-history and macromorphological traits.

Native arbuscular mycorrhizal fungi drive ecophysiology through phenotypic integration and functional plasticity under the Sonoran desert conditions

Knowledge is scarce to what extent environmental drivers and native symbiotic fungi in soil induce abrupt (short-term), systemic (multiple traits), or specific (a subset of traits) shifts in C3 plants' ecophysiological/mycorrhizal responses. We cultivated an emblematic native C3 species (Capsicum annuum var. glabriusculum, "Chiltepín") to look at how the extreme heat of the Sonoran desert, sunlight regimes (low = 2, intermediate = 15, high = 46 mol m2 d-1) and density of native arbuscular mycorrhizal fungi in soil (low AMF = 1% v/v, high AMF = 100% v/v), drive shifts on mycorrhizal responses through multiple functional traits (106 traits). The warming thresholds were relentlessly harsh even under intensive shade (e.g. superheat maximum thresholds reached ranged between 47-63°C), and several pivotal traits were synergistically driven by AMF (e.g. photosynthetic capacity, biomass gain/allometry, and mycorrhizal colonization traits); whereas concurrently, sunlight regimes promoted most (76%) alterations in functional acclimation traits in the short-term and opposite directions (e.g. survival, phenology, photosynthetic, carbon/nitrogen economy). Multidimensional reduction analysis suggests that the AMF promotes a synergistic impact on plants' phenotypic integration and functional plasticity in response to sunlight regimes; however, complex relationships among traits suggest that phenotypic variation determines the robustness degree of ecophysiological/mycorrhizal phenotypes between/within environments. Photosynthetic canopy surface expansion, Rubisco activity, photosynthetic nitrogen allocation, carbon gain, and differential colonization traits could be central to plants' overall ecophysiological/mycorrhizal fitness strengthening. In conclusion, we found evidence that a strong combined effect among environmental factors in which AMF are key effectors could drive important trade-offs on plants' ecophysiological/mycorrhizal fitness in the short term.

Dissecting the Superior Drivers for the Simultaneous Improvement of Fiber Quality and Yield Under Drought Stress Via Genome-Wide Artificial Introgressions of Gossypium barbadense into Gossypium hirsutum

Global water scarcity and extreme weather intensify drought stress, significantly reducing cotton yield and quality worldwide. Drought treatments are conducted using a population of chromosome segment substitution lines generated from E22 (G. hirsutum) and 3-79 (G. barbadense) as parental lines either show superior yields or fiber quality under both control and drought conditions. Fourteen datasets, covering 4 yields and 4 quality traits, are compiled and assessed for drought resistance using the drought resistance coefficient (DRC) and membership function value of drought resistance (MFVD). Genome-wide association studies, linkage analysis, and bulked segregant analysis are combined to analyze the DR-related QTL. A total of 121 significant QTL are identified by DRC and MFVD of the 8 traits. CRISPR/Cas9 and virus-induced gene silencing techniques verified DRR1 and DRT1 as pivotal genes in regulating drought resistant of cotton, with hap3-79 exhibiting greater drought resistance than hapE22 concerning DRR1 and DRT1. Moreover, 14 markers with superior yield and fiber quality are selected for drought treatment. This study offers valuable insights into yield and fiber quality variations between G. hirsutum and G. barbadense amid drought, providing crucial theoretical and technological backing for developing cotton varieties resilient to drought, with high yield and superior fiber quality.

The long and tortuous path towards improving photosynthesis by engineering elevated mesophyll conductance

The growing demand for global food production is likely to be a defining issue facing humanity over the next 50 years. To tackle this challenge, there is a desire to bioengineer crops with higher photosynthetic efficiencies, to increase yields. Recently, there has been a growing interest in engineering leaves with higher mesophyll conductance (gm), which would allow CO2 to move more efficiently from the substomatal cavities to the chloroplast stroma. However, if crop yield gains are to be realised through this approach, it is essential that the methodological limitations associated with estimating gm are fully appreciated. In this review, we summarise these limitations, and outline the uncertainties and assumptions that can affect the final estimation of gm. Furthermore, we critically assess the predicted quantitative effect that elevating gm will have on assimilation rates in crop species. We highlight the need for more theoretical modelling to determine whether altering gm is truly a viable route to improve crop performance. Finally, we offer suggestions to guide future research on gm, which will help mitigate the uncertainty inherently associated with estimating this parameter.

GasanalyzeR: advancing reproducible research using a new R package for photosynthesis data workflows

The analysis of photosynthetic traits has become an integral part of plant (eco-)physiology. Many of these characteristics are not directly measured, but calculated from combinations of several, more direct, measurements. The calculations of such derived variables are based on underlying physical models and may use additional constants or assumed values. Commercially available gas-exchange instruments typically report such derived variables, but the available implementations use different definitions and assumptions. Moreover, no software is currently available to allow a fully scripted and reproducible workflow that includes importing data, pre-processing and recalculating derived quantities. The R package gasanalyzer aims to address these issues by providing methods to import data from different instruments, by translating photosynthetic variables to a standardized nomenclature, and by optionally recalculating derived quantities using standardized equations. In addition, the package facilitates performing sensitivity analyses on variables or assumptions used in the calculations to allow researchers to better assess the robustness of the results. The use of the package and how to perform sensitivity analyses are demonstrated using three different examples.

Quantifying mangrove carbon assimilation rates using UAV imagery

Mangrove forests are recognized as one of the most effective ecosystems for storing carbon. In drylands, mangroves operate at the extremes of environmental gradients and, in many instances, offer one of the few opportunities for vegetation-based sequestering of carbon. Developing accurate and reproducible methods to map carbon assimilation in mangroves not only serves to inform efforts related to natural capital accounting, but can help to motivate their protection and preservation. Remote sensing offers a means to retrieve numerous vegetation traits, many of which can be related to plant biophysical or biochemical responses. The leaf area index (LAI) is routinely employed as a biophysical indicator of health and condition. Here, we apply a linear regression model to UAV-derived multispectral data to retrieve LAI across three mangrove sites located along the coastline of the Red Sea, with estimates producing an R2 of 0.72 when compared against ground-sampled LiCOR LAI-2200C LAI data. To explore the potential of monitoring carbon assimilation within these mangrove stands, the UAV-derived LAI estimates were combined with field-measured net photosynthesis rates from a LiCOR 6400/XT, providing a first estimate of carbon assimilation in dryland mangrove systems of approximately 3000 ton C km-2 yr-1. Overall, these results advance our understanding of carbon assimilation in dryland mangroves and provide a mechanism to quantify the carbon mitigation potential of mangrove reforestation efforts.

Fast Assimilation-Temperature Response: a FAsTeR method for measuring the temperature dependence of leaf-level photosynthesis

We present the Fast Assimilation-Temperature Response (FAsTeR) method, a new method for measuring plant assimilation-temperature (AT) response that reduces measurement time and increases data density compared with conventional methods. The FAsTeR method subjects plant leaves to a linearly increasing temperature ramp while taking rapid, nonequilibrium measurements of gas exchange variables. Two postprocessing steps are employed to correct measured assimilation rates for nonequilibrium effects and sensor calibration drift. Results obtained with the new method are compared with those from two conventional stepwise methods. Our new method accurately reproduces results obtained from conventional methods, reduces measurement time by a factor of c. 3.3 (from c. 90 to 27 min), and increases data density by a factor of c. 55 (from c. 10 to c. 550 observations). Simulation results demonstrate that increased data density substantially improves confidence in parameter estimates and drastically reduces the influence of noise. By improving measurement speed and data density, the FAsTeR method enables users to ask fundamentally new kinds of ecological and physiological questions, expediting data collection in short-field campaigns, and improving the representativeness of data across species in the literature.

Boreal conifers maintain carbon uptake with warming despite failure to track optimal temperatures

Warming shifts the thermal optimum of net photosynthesis (ToptA) to higher temperatures. However, our knowledge of this shift is mainly derived from seedlings grown in greenhouses under ambient atmospheric carbon dioxide (CO2) conditions. It is unclear whether shifts in ToptA of field-grown trees will keep pace with the temperatures predicted for the 21st century under elevated atmospheric CO2 concentrations. Here, using a whole-ecosystem warming controlled experiment under either ambient or elevated CO2 levels, we show that ToptA of mature boreal conifers increased with warming. However, shifts in ToptA did not keep pace with warming as ToptA only increased by 0.26-0.35 °C per 1 °C of warming. Net photosynthetic rates estimated at the mean growth temperature increased with warming in elevated CO2 spruce, while remaining constant in ambient CO2 spruce and in both ambient CO2 and elevated CO2 tamarack with warming. Although shifts in ToptA of these two species are insufficient to keep pace with warming, these boreal conifers can thermally acclimate photosynthesis to maintain carbon uptake in future air temperatures.