Herbivory can impact gas exchange, but the causes of interspecific variation in response remain poorly understood. We aimed to determine (1) what effects does experimental herbivory damage to leaf midveins have on leaf gas exchange and, (2) whether changes in leaf gas exchange after damage was predicted by leaf mechanical or venation traits. We hypothesized that herbivory-driven impacts on leaf gas exchange would be mediated by (1a/1b) venation networks, either by more vein resistance, or possibly trading off with other structural defenses; (2a/2b) or more reticulation (resilience, providing more alternate flow pathways after damage) or less reticulation (sectoriality, preventing spread of reduced functionality after damage). We simulated herbivory by damaging the midveins of four leaves from each of nine Sonoran Desert species. We then measured the percent change in photosynthesis (ΔAn%), transpiration (ΔEt%) and stomatal conductance (Δgsw%) between treated and control leaves. We assessed the relationship of each with leaf venation traits and other mechanical traits. ΔAn% varied between +10 % and −55%, similar to ΔEt% (+27%, −54%) and Δgsw% (+36%, −53%). There was no tradeoff between venation and other structural defenses. Increased damage resilience (reduced ΔAn%, ΔEt%, Δgsw%) was marginally associated with lower force-to-tear (P < 0.05), and higher minor vein density (P < 0.10) but not major vein density or reticulation. Leaf venation networks may thus partially mitigate the response of gas exchange to herbivory and other types of vein damage through either resistance or resilience.
Beyond facilitating transport and providing mechanical support to the leaf, veins have important roles in the performance and productivity of plants and the ecosystem. In recent decades, computational image analysis has accelerated the extraction and quantification of vein traits, benefiting fields of research from agriculture to climatology. However, most of the existing leaf vein image analysis programs have been developed for the reticulate venation found in dicots. Despite the agroeconomic importance of cereal grass crops, like
- PAR ID:
- 10367190
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- The Plant Journal
- Volume:
- 107
- Issue:
- 2
- ISSN:
- 0960-7412
- Page Range / eLocation ID:
- p. 629-648
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Climate means and variability are shifting rapidly, leading to mismatches between climate and locally adapted plant traits. Phenotypic plasticity, the ability of a plant to respond to environmental conditions within a lifetime, may provide a buffer for plants to persist under increasing temperature and water stress. We used two reciprocal common gardens across a steep temperature gradient to investigate plasticity in six populations of Fremont cottonwood, an important foundation tree species in arid riparian ecosystems. We investigated two components of leaf hydraulic architecture: leaf venation and stomatal morphology, both of which regulate leaf water potential and photosynthesis. These traits will likely affect plant performance under climate stressors, but it is unclear whether they are controlled by genetic or environmental factors, and whether they respond to the environment in parallel or independent directions. We found that: 1) Populations had divergent responses to a hotter growing environment, increasing or decreasing vein density. 2) Populations showed surprisingly independent responses of venation vs. stomatal traits. 3) As a result of these different responses, plasticity in hydraulic architecture traits was not predictable from historic climate conditions at population source locations, and often varied substantially within populations. 4) Hydraulic architecture was clearly linked to growth, with higher vein and stomatal density predicting greater tree growth in the hottest growing environment. However, higher plasticity in these traits did not increase average growth across multiple environments. Thus, P. fremontii populations and genotypes vary in their capacity to adjust their leaf hydraulic architecture and support growth in contrasting environments, but that this plasticity is not clearly predictable or beneficial. Identifying genotypes suitable for future conditions will depend on the relative importance of multiple traits, and on both evolutionary and ecological responses to changing temperature and water availability.more » « less
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Summary Leaf vein network geometry can predict levels of resource transport, defence and mechanical support that operate at different spatial scales. However, it is challenging to quantify network architecture across scales due to the difficulties both in segmenting networks from images and in extracting multiscale statistics from subsequent network graph representations.
Here we developed deep learning algorithms using convolutional neural networks (CNNs) to automatically segment leaf vein networks. Thirty‐eight CNNs were trained on subsets of manually defined ground‐truth regions from >700 leaves representing 50 southeast Asian plant families. Ensembles of six independently trained CNNs were used to segment networks from larger leaf regions (
c . 100 mm2). Segmented networks were analysed using hierarchical loop decomposition to extract a range of statistics describing scale transitions in vein and areole geometry.The CNN approach gave a precision‐recall harmonic mean of 94.5% ± 6%, outperforming other current network extraction methods, and accurately described the widths, angles and connectivity of veins. Multiscale statistics then enabled the identification of previously undescribed variation in network architecture across species.
We provide a
LeafVeinCNN software package to enable multiscale quantification of leaf vein networks, facilitating the comparison across species and the exploration of the functional significance of different leaf vein architectures. -
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Premise Physiological processes may vary within leaf laminae; however, the accompanying heterogeneity in leaf venation is rarely investigated because its quantification can be time consuming. Here we introduce accelerated protocols using existing software to increase sample throughput and ask whether laminae venation varies among three crop types and four subspecies of
Brassica rapa .Methods FAA (formaldehyde, glacial acetic acid, and ethanol)‐fixed samples were stored in ethanol. Without performing any additional clearing or staining, we tested two methods of image acquisition at three locations along the proximal‐distal axis of the laminae and estimated the patterns of venation using the program phenoVein. We developed and made available an R script to handle the phenoVein output and then analyzed our data using linear mixed‐effects models.Results Beyond fixation and storage, staining and clearing are not necessary to estimate leaf venation using phenoVein if the images are acquired using a stereomicroscope. All estimates of venation required some manual adjustment. We found a significant effect of location within the laminae for all aspects of venation.
Discussion By removing the clearing and staining steps and utilizing the semi‐automated program phenoVein, we quickly and cheaply acquired leaf venation data. Venation may be an important target for crop breeding efforts, particularly if intralaminar variation correlates with variation in physiological processes, which remains an open question.
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