Connecting tree‐ring phenotypes, genetic associations and transcriptomics to decipher the genomic architecture of drought adaptation in a widespread conifer

Molecular Ecology, Год журнала: 2021, Номер 30(16), С. 3898 - 3917

Опубликована: Фев. 17, 2021

As boreal forests face significant threats from climate change, understanding evolutionary trajectories of coniferous species has become fundamental to adapting management and conservation a drying climate. We examined the genomic architecture underlying adaptive variation related drought tolerance in 43 populations widespread conifer, white spruce (Picea glauca [Moench] Voss), by combining genotype-environment associations, genotype-phenotype transcriptomics. Adaptive genetic was identified correlating allele frequencies for 6,153 single nucleotide polymorphisms 2,606 candidate genes with temperature, precipitation aridity gradients, testing associations between genotypes 11 dendrometric drought-related traits (i.e., anatomical, growth response climate-sensitivity traits) using polygenic model. set 285 significantly associated climatic factor or phenotypic trait, including 110 that were differentially expressed under greenhouse-controlled conditions. The interlinked phenotype-genotype-environment network revealed eight high-confidence involved adaptation drought, which four drought-responsive expression analysis. Our findings represent step toward characterization basis conifers, is essential enable establishment resilient view new

Язык: Английский

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Drone‐based physiological index reveals long‐term acclimation and drought stress responses in trees

Plant Cell & Environment, Год журнала: 2021, Номер 44(11), С. 3552 - 3570

Опубликована: Авг. 31, 2021

Abstract Monitoring early tree physiological responses to drought is key understanding progressive impacts of on forests and identifying resilient species. We combined drone‐based multispectral remote sensing with measurements physiology environmental parameters over two growing seasons in a 100‐y‐old Pinus sylvestris forest subject 17‐y precipitation manipulation. Our goal was determine if photochemical reflectance index (PRI) captures stress whether are affected by long‐term acclimation. PRI detects changes xanthophyll cycle pigment dynamics, which reflect increases photoprotective non‐photochemical quenching activity resulting from drought‐induced photosynthesis downregulation. Here, never‐irrigated trees up 10 times lower (higher stress) than irrigated trees. Long‐term acclimation experimental treatment, however, influenced the seasonal relationship between soil water availability. also captured diurnal decreases efficiency, driven vapour pressure deficit. Interestingly, 5 years after irrigation stopped for subset trees, positive legacy effect persisted, PRI) compared This study demonstrates ability remotely sensed scale an entire importance determining current responses.

Язык: Английский

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Evaluating fine-scale phenology from PlanetScope satellites with ground observations across temperate forests in eastern North America

Remote Sensing of Environment, Год журнала: 2022, Номер 283, С. 113310 - 113310

Опубликована: Окт. 20, 2022

Язык: Английский

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A Broadband Green-Red Vegetation Index for Monitoring Gross Primary Production Phenology

Journal of Remote Sensing, Год журнала: 2022, Номер 2022

Опубликована: Янв. 1, 2022

The chlorophyll/carotenoid index (CCI) is increasingly used for remotely tracking the phenology of photosynthesis. However, CCI restricted to few satellites incorporating 531 nm band. This study reveals that Moderate Resolution Imaging Spectroradiometer (MODIS) broadband green reflectance (band 4) significantly correlated with this xanthophyll-sensitive narrowband 11) ( R 2 = 0.98 , p < 0.001 ), and consequently, green-red vegetation GRVI—computed MODIS band 1 4—is CCI—computed 11 0.97 ). GRVI performed similarly in extracting phenological metrics dates start end season (EOS) when evaluated gross primary production (GPP) measurements from eddy covariance towers. For EOS extraction evergreen needleleaf forest, even overperformed solar-induced chlorophyll fluorescence which seen as a direct proxy plant opens door GPP photosynthetic monitoring wide set sensors broadbands red spectral regions.

Язык: Английский

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Cotton Stand Counting from Unmanned Aerial System Imagery Using MobileNet and CenterNet Deep Learning Models

Remote Sensing, Год журнала: 2021, Номер 13(14), С. 2822 - 2822

Опубликована: Июль 18, 2021

An accurate stand count is a prerequisite to determining the emergence rate, assessing seedling vigor, and facilitating site-specific management for optimal crop production. Traditional manual counting methods in assessment are labor intensive time consuming large-scale breeding programs or production field operations. This study aimed apply two deep learning models, MobileNet CenterNet, detect cotton plants at stage with unmanned aerial system (UAS) images. These models were trained datasets containing 400 900 images variations plant size soil background brightness. The performance of these was assessed testing different dimensions, dataset 1 300 by pixels 2 250 1200 pixels. model validation results showed that mean average precision (mAP) recall (AR) 79% 73% CenterNet model, 86% 72% training accuracy detection higher both models. had better overall also indicated more required when applying object on dimensions from datasets. absolute percentage error (MAPE), coefficient determination (R2), root squared (RMSE) values 0.07%, 0.98 0.37, respectively, Both have potential accurately timely based high-resolution UAS stage. provides valuable information selecting right tools appropriate number projects agricultural applications.

Язык: Английский

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Characterizing vegetation complexity with unmanned aerial systems (UAS) – A framework and synthesis

Ecological Indicators, Год журнала: 2021, Номер 131, С. 108156 - 108156

Опубликована: Сен. 2, 2021

Ecosystem complexity is among the important drivers of biodiversity and ecosystem functioning, unmanned aerial systems (UASs) are becoming an tool for characterizing vegetation patterns processes. The variety UASs applications immense, so procedures to process data described in literature. Optimizing workflow still a matter discussion. Here, we present comprehensive synthesis aiming identify common rules that shape workflows applied UAS-based studies facing ecosystems. Analysing studies, found similarities irrespective ecosystem, according character property addressed, such as species composition (biodiversity), structure (stand volume/complexity), plant status (phenology stress levels), dynamics (disturbances regeneration). We propose general framework allowing design surveys its purpose component addressed. support by detailed schemes well examples best practices UAS covering each properties (i.e. composition, structure, dynamics) related applications. For efficient survey, following points crucial: knowledge phenomenon, choice platform, sensor, resolution (temporal, spatial spectral), model classification algorithm careful interpretation results. simpler procedure, more robust, repeatable, applicable cost effective it is. Therefore, proper can minimize efforts while maximizing quality

Язык: Английский

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Noninvasive Technologies for Primate Conservation in the 21st Century

International Journal of Primatology, Год журнала: 2021, Номер 43(1), С. 133 - 167

Опубликована: Окт. 22, 2021

Abstract Observing and quantifying primate behavior in the wild is challenging. Human presence affects habituation of new, especially terrestrial, individuals a time-intensive process that carries with it ethical health concerns, during recent pandemic when primates are at even greater risk than usual. As result, wildlife researchers, including primatologists, have increasingly turned to new technologies answer questions provide important data related conservation. Tools methods should be chosen carefully maximize improve will used research questions. We review here role four indirect methods—camera traps, acoustic monitoring, drones, portable field labs—and improvements machine learning offer rapid, reliable means combing through large datasets these generate. describe key applications limitations each tool conservation, where we anticipate conservation technology moving forward coming years.

Язык: Английский

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Interplay among photoreceptors determines the strategy of coping with excess light in tomato

The Plant Journal, Год журнала: 2024, Номер 118(5), С. 1423 - 1438

Опубликована: Фев. 25, 2024

This study investigates photoreceptor's role in the adaption of photosynthetic apparatus to high light (HL) intensity by examining response tomato wild type (WT) (Solanum lycopersicum L. cv. Moneymaker) and mutants (phyA, phyB1, phyB2, cry1) plants HL. Our results showed a photoreceptor-dependent effect HL on maximum quantum yield photosystem II (F

Язык: Английский

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Evaluation of Cotton Emergence Using UAV-Based Narrow-Band Spectral Imagery with Customized Image Alignment and Stitching Algorithms

Remote Sensing, Год журнала: 2020, Номер 12(11), С. 1764 - 1764

Опубликована: Май 30, 2020

Crop stand count and uniformity are important measures for making proper field management decisions to improve crop production. Conventional methods evaluating based on visual observation time consuming labor intensive, it difficult adequately cover a large field. The overall goal of this study was evaluate cotton emergence at two weeks after planting using unmanned aerial vehicle (UAV)-based high-resolution narrow-band spectral indices that were collected pushbroom hyperspectral imager flying 50 m above ground. A customized image alignment stitching algorithm developed process cubes efficiently build panoramas each narrow band. normalized difference vegetation index (NDVI) calculated segment seedlings from soil background. Hough transform used row identification weed removal. Individual identified geometric features calculate count. Results show the had an average error 2.8 pixels, which much smaller than 181 pixels associated commercial software. system able number in seedling clusters with accuracy 84.1%. Mean absolute percentage (MAPE) estimation density meter level 9.0%. For evaluation, MAPE spacing 9.1% standard deviation 6.8%. showed UAV-based images potential emergence.

Язык: Английский

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Breeding for Climate Change Resilience: A Case Study of Loblolly Pine (Pinus taeda L.) in North America

Frontiers in Plant Science, Год журнала: 2021, Номер 12

Опубликована: Апрель 30, 2021

Earth's atmosphere is warming and the effects of climate change are becoming evident. A key observation that both average levels variability temperature precipitation changing. Information data from new technologies developing in parallel to provide multidisciplinary opportunities address overcome consequences these changes forest ecosystems. Changes water availability impose multidimensional environmental constraints trigger molecular stand level. These can represent a threat for normal development tree early seedling recruitment adulthood through direct mortality, by increasing susceptibility pathogens, insect attack, fire damage. This review summarizes strengths shortcomings previous work areas genetic variation related cold drought stress species with particular emphasis on loblolly pine (Pinus taeda L.), most-planted North America. We describe discuss implementation management breeding strategies increase resilience adaptation, how engineering genomics shaping future phenotype-genotype studies. Lessons learned study important intensively-managed ecosystems may also prove be value helping less-intensively managed adapt change, thereby sustainability forestlands future.

Язык: Английский

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