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The purpose of this study was to determine the effects of the semicircular canals and otolith organs on respiration in humans. On the basis of animal studies, we hypothesized that vestibular activation would elicit a vestibulorespiratory reflex. To test this hypothesis, respiratory measures, arterial blood pressure, and heart rate were measured during engagement of semicircular canals and/or otolith organs. Dynamic upright pitch and roll (15 cycles/min), which activate the otolith organs and semicircular canals, increased respiratory rate (Delta2 +/- 1 and Delta3 +/- 1 breaths/min, respectively; P < 0.05). Dynamic yaw and lateral pitch (15 cycles/min), which activate the semicircular canals, increased respiration similarly (Delta3 +/- 1 and Delta2 +/- 1, respectively; P < 0.05). Dynamic chair rotation (15 cycles/min), which mimics dynamic yaw but eliminates neck muscle afferent, increased respiration (Delta3 +/- 1; P < 0.05) comparable to dynamic yaw (15 cycles/min). Increases in respiratory rate were graded as greater responses occurred during upright (Delta5 +/- 2 breaths/min) and lateral pitch (Delta4 +/- 1) and roll (Delta5 +/- 1) performed at 30 cycles/min. Increases in breathing frequency resulted in increases in minute ventilation during most interventions. Static head-down rotation, which activates otolith organs, did not alter respiratory rate (Delta1 +/- 1 breaths/min). Collectively, these data indicate that semicircular canals, but not otolith organs or neck muscle afferents, mediate increased ventilation in humans and support the concept that vestibular activation alters respiration in humans.
This dataset supports a broader study examining hyporheic zone respiration rates to improve predictive models at a contiguous United States (CONUS) scale. The CONUS-Scale Model-Sample Study (CM) was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the CONUS. New machine learning models were created every month to guide sampling locations. Data from the resulting samples were used to test and rebuild the machine learning models for the next round of sampling guidance. Sampling began in April 2022 and ended in October 2023. In addition to the widely distributed CONUS sites, a more spatially focused sampling occurred in the Yakima River Basin, WA in summer 2022. Data from this more spatially intensive sampling occurred under the label “Second Spatial Study (SSS)” and were also included in the machine learning models. Other data types collected from SSS that were not part of CM were published in a separate data package (https://data.ess-dive.lbl.gov/view/doi:10.15485/1969566). This data package was originally published in February 2023. It was updated in June 2023 (v2; new and modified files); December 2023 (v3; new and modified files); June 2024 (v4; new and modified files); April 2024 (v5; new and modified files); and September 2025 (v6; modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of two folders of field photos and videos, one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) international generic sample number (IGSN) mapping file; (6) field protocols; (7) a subfolder with sample data; and (8) a subfolder with sensor data. The sample data subfolder contains (1) surface water and sediment dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) surface water and sediment total nitrogen data and averages; (3) surface water major cations and anions and averages; (4) sediment grain size data; (5) sediment iron (II) data and averages; (6) wet sediment mass, dry sediment mass, water mass, and wet sediment volume in incubation and sediment ICR vials; (7) sediment incubation respiration rate data and averages; (8) normalized respiration rate data and averages; (9) methods codes; (10) sediment specific surface area; (11) sediment percent carbon and nitrogen; (12) sediment gravimetric moisture and averages; (15) sediment X-ray diffraction (XRD) data; (16) sediment adenosine triphosphate (ATP) and averages; (17) a subfolder with sediment incubation respiration data, scripts, and plots; (18) surface water and sediment FTICR methods; and (19) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains five subfolders, one containing the sediment .xml data files, one containing the water .xml files, one containing the sediment CoreMS output files, one containing the water CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS).The sensor data subfolder contains (1) a subfolder with miniDOT dissolved oxygen and temperature data and plots; (2) miniDOT dissolved oxygen and temperature summary data; and (3) miniDOT installation methods. All files are .csv, .pdf, .R, .xml, .d, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, .png, .mov, or .mp4. CORRECTION: Carbon and nitrogen content are reported as percentages. The current column headers "01395_C_percent_per_mg" and "01397_N_percent_per_mg" are incorrect. These should read "01395_C_percent" and "01397_N_percent" and will be corrected in the next version of this data package. We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Washington State Parks and Recreation Commission (Scientific Research Permit #210901), and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the samples labeled “SSS” were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview. WHONDRS consortium members were asked to provide any acknowledgments for the collection of samples labeled “CM” and the following is a list of acknowledgments that were submitted with their corresponding Site IDs: (MART) Research activities were conducted in part on the Wind River Experimental Forest within the Gifford Pinchot National Forest; (MP- 100379) Philadelphia is part of Lenapehoking, the ancestral homelands of the Lenape peoples; (MP-102398) Land surveyed is the ancestral homelands of the Nookhose'iinenno (Arapaho), Tsis tsis'tas (Cheyenne), and Nuuchu (Ute); (MP-100749 and MP- 100747) Georgia Coastal Ecosystem LTER, OCE-1832178; (SP-70 and SP-72) Eastern Shoshone, Shoshone-Bannock; (MP- 102944) Funded by Oregon Watershed Enhancement Board. On the traditional lands of the Confederated Tribes of the Siletz, Confederated Tribes of the Grand Rhonde, and the Clatsop-Nehalem Confederated Tribe; (MP- 100607) Holiday Creek is located on the traditional territory of the Monacan Indian Nation; (SP-45) Lafayette Blue Springs State Park; (MP-102420) NSF DEB-2016749; (MP-100019) New Hampshire Agriculture Experiment Station; (SP-35) Rayonier (land owner; https://www.rayonier.com/); (MP- 101276) US Department of Energy, Office of Science, Biological and Environmental Research, Subsurface Biogeochemical Research, Watershed Dynamics and Evolution SFA at ORNL; (MP- 103224) Watershed Dynamics and Evolution SFA at ORNL; (MP- 101584) Traditional lands of the Oceti Sakowin (Dakota, Lakota, Nakoda) and Anishinaabe Peoples.
This study aimed to quantify rates of viral production in aridisol soil under conditions as close to natural field soil as possible given the perturbations necessary to manipulate viral abundances. Viruses were removed from soil, then added back to virus-depleted soil to control the initial viral abundances at either 100% (field_abund) or 10% (reduced_abund) of measured field viral abundance to generate treatments with field-relevant and reduced viral infection pressure, respectively. Replicates of batch incubation jars were harvested every 8 hours for 48 hours to enumerate bacteria and viruses by microscopy (n=5) and profile bacterial community composition by 16S rRNA amplicon sequencing (n=3).
This dataset supports a broader study examining the effects of wetting and drying on hyporheic zone respiration. The dataset provides data generated from a laboratory moisture manipulation experiment. The contents include time series aerobic respiration and moisture; dissolved oxygen; sediment geochemistry data; and field metadata (including qualitative information on instream and river corridor characteristics). Samples were collected as part of the WHONDRS Allison Veach collaboration (AV1). The data package associated with the AV1 study is available at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2529428. AV1 sampling occurred across 7 perennial and 7 intermittent streams in San Antonio, Texas. Each stream/site was visited both in summer during base flow (July-September 2023) and winter during peak flow (January-February 2024). This study uses subsamples from a subset of AV1 samples. The original field samples were labeled as AV1_###. Subsequent subsamples for this study were labeled as EV_###. The labels from the field samples and the EV subsamples can be mapped directly based on the digits following the prefix and underscore (i.e., EV_001 is a subsample from AV1_001). See the critical details section below for more details on sample naming. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) field protocol; and a (6) a subfolder with sediment sample data from the incubation experiment. The sample data subfolder contains (1) effect size; (2) iron (II); (3) gravimetric moisture; (4) respiration rates; (5) raw dissolved oxygen values and plots; (6) specific conductance; (7) pH; (8) temperature; (9) a summary containing mean, median, and standard deviation values of each data type for each treatment (wet and dry); and (10) methods codes. All files are .csv or.pdf.
Nonphosphorylating respiration of mitochondria from brown adipose tissue of rats, providing example of electron transport
Since the first human flights outside of Earth's gravity, crew health and well-being have been major concerns. Exposure to microgravity during spaceflight is known to affect the human immune response, possibly making the crew members more vulnerable to infectious disease. In addition, biological experiments previously flown in space have shown that bacteria grow faster in microgravity than they do on Earth. The ability of certain antibiotics to control bacterial infections may also differ greatly in microgravity. It is therefore critical to understand how spaceflight and microgravity affect bacterial virulence, which is their ability to cause disease. By utilizing spaceflight hardware provided by the European Space Agency (ESA), Dr. Barry Pyle and his team at Montana State University, Bozeman, will be performing an experiment to study the effects of microgravity on the virulence of a common soil and water bacterium, Pseudomonas aeruginosa. Importantly, these bacteria have been detected in the water supplies of previous Space Shuttle flights. The experiment will examine the effects of microgravity exposure on bacterial growth and on the bacterium's ability to form a toxin called Exotoxin A. Another goal is to evaluate the effects of microgravity on the physiology of the bacteria by analyzing their ability to respire (produce energy), by studying the condition of the plasma membrane surrounding the cell, and by determining if specific enzymes remain active. Proteins produced by the bacteria will also be assayed to see if the normal functions of the bacteria are affected. In the context of human life support in spaceflight, the results of this experiment will offer guidance in providing the highest possible water quality for the Shuttle in order to limit the risk of infection to human occupants and to minimize water system and spacecraft deterioration.
This dataset supports a broader study examining the effects of wetting and drying on hyporheic zone respiration across the contiguous United States (CONUS). The dataset provides data generated from a laboratory moisture manipulation experiment. The contents include time series aerobic respiration and moisture; dissolved oxygen; sediment geochemistry data; and field metadata (including qualitative information on instream and river corridor characteristics). Samples were collected as part of the WHONDRS CONUS-Scale Model-Sample Study (CM). This study was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the CONUS. The data package associated with the CM study is available at https://data.ess-dive.lbl.gov/view/doi:10.15485/1923689. CM sampling began in April 2022 and ended in October 2023. This study uses subsamples from a subset of CM samples collected between June 2022 and June 2023. The original field samples were labeled as CM_###. Subsequent subsamples for this study were labeled as EC_###. The labels from the field samples and the EC subsamples can be mapped directly based on the digits following the prefix and underscore (i.e., EC_001 is a subsample from CM_001). See the critical details section below for more details on sample naming. This data package was originally published in August 2024. It was updated in February 2026 (v2; new and modified files). See the change history section in the readme for more details. For details on how to navigate this data package, see this infographic from the River Corridor SFA https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) field protocol; and a (6) a subfolder with sediment sample data from the incubation experiment. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC); (2) total nitrogen (TN); (3) adenosine triphosphate (ATP); (4) percent carbon and nitrogen; (5) effect size; (6) iron (II); (7) gravimetric moisture; (8) respiration rates and raw dissolved oxygen values; (9) specific conductance; (10) pH; (11) temperature; (12) a summary containing median values of each data type for each treatment (wet and dry); (13) methods codes; (14) FTICR-MS methods; and (15) a subfolder of 9.4 Tesla FTICR-MS data. This folder contains three subfolders, one containing the sediment .xml data files, one containing the sediment CoreMS output files, the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .ref, or .xml.
Plant culture in oxygen concentrations below ambient is known to stimulate vegetative growth, but apart from reports on increased leaf number and weight, little is known about development at subambient oxygen concentrations. Arabidopsis thaliana (L.) Heynh. (cv. Columbia) plants were grown full term in pre-mixed atmospheres with oxygen partial pressures of 2.5, 5.1, 10.1, 16.2, and 21.3 kPa O2, 0.035 kPa CO2 and the balance nitrogen under continuous light. Fully expanded leaves were harvested and processed for light and transmission electron microscopy or for starch quantification. Growth in subambient oxygen concentrations caused changes in leaf anatomy (increased thickness, stomatal density and starch content) that have also been described for plants grown under carbon dioxide enrichment. However, at the lowest oxygen treatment (2.5 kPa), developmental changes occurred that could not be explained by changes in carbon budget caused by suppressed photorespiration, resulting in very thick leaves and a dwarf morphology. This study establishes the leaf parameters that change during growth under low O2, and identifies the lower concentration at which O2 limitation on transport and biosynthetic pathways detrimentally affects leaf development. Grant numbers: NAG5-3756, NAG2-1020, NAG2-1375.
We applied cardiovascular system identification (CSI) to characterize closed-loop cardiovascular regulation in patients with diabetic autonomic neuropathy (DAN). The CSI method quantitatively analyzes beat-to-beat fluctuations in noninvasively measured heart rate, arterial blood pressure (ABP), and instantaneous lung volume (ILV) to characterize four physiological coupling mechanisms, two of which are autonomically mediated (the heart rate baroreflex and the coupling of respiration, measured in terms of ILV, to heart rate) and two of which are mechanically mediated (the coupling of ventricular contraction to the generation of the ABP wavelet and the coupling of respiration to ABP). We studied 37 control and 60 diabetic subjects who were classified as having minimal, moderate, or severe DAN on the basis of standard autonomic tests. The autonomically mediated couplings progressively decreased with increasing severity of DAN, whereas the mechanically mediated couplings were essentially unchanged. CSI identified differences between the minimal DAN and control groups, which were indistinguishable based on the standard autonomic tests. CSI may provide a powerful tool for assessing DAN.
Growth of plants in a Controlled Ecological Life Support System (CELSS) may involve the use of hypobaric pressures enabling lower mass requirements for atmospheres and possible enhancement of crop productivity. A controlled environment plant growth chamber with hypobaric capability designed and built at Ames Research Center was used to determine if reduced pressures influence the rates of photosynthesis (Ps) and dark respiration (DR) of hydroponically grown lettuce plants. The chamber, referred to as a plant volatiles chamber (PVC), has a growing area of about 0.2 m2, a total gas volume of about 0.7 m3, and a leak rate at 50 kPa of <0.1%/day. When the pressure in the chamber was reduced from ambient to 51 kPa, the rate of net Ps increased by 25% and the rate of DR decreased by 40%. The rate of Ps increased linearly with decreasing pressure. There was a greater effect of reduced pressure at 41 Pa CO2 than at 81 Pa CO2. This is consistent with reports showing greater inhibition of photorespiration (Pr) in reduced O2 at low CO2 concentrations. When the partial pressure of O2 was held constant but the total pressure was varied between 51 and 101 kPa, the rate of CO2 uptake was nearly constant, suggesting that low pressure enhancement of Ps may be mainly attributable to lowered partial pressure of O2 and the accompanying reduction in Pr. The effects of lowered partial pressure of O2 on Ps and DR could result in substantial increases in the rates of biomass production, enabling rapid throughput of crops or allowing flexibility in the use of mass and energy resources for a CELSS.
Wetland CH 4 emissions are among the most uncertain components of the global CH 4 budget. The complex nature of wetland CH 4 processes makes it challenging to identify causal relationships for improving our understanding and predictability of CH 4 emissions. In this study, we used the flux measurements of CH 4 from eddy covariance towers (30 sites from 4 wetlands types: bog, fen, marsh, and wet tundra) to construct a causality-constrained machine learning (ML) framework to explain the regulative factors and to capture CH 4 emissions at sub-seasonal scale. We found that soil temperature is the dominant factor for CH 4 emissions in all studied wetland types. Ecosystem respiration (CO 2 ) and gross primary productivity exert controls at bog, fen, and marsh sites with lagged responses of days to weeks. Integrating these asynchronous environmental and biological causal relationships in predictive models significantly improved model performance. More importantly, modeled CH 4 emissions differed by up to a factor of 4 under a +1°C warming scenario when causality constraints were considered. These results highlight the significant role of causality in modeling wetland CH 4 emissions especially under future warming conditions, while traditional data-driven ML models may reproduce observations for the wrong reasons. Our proposed causality-guided model could benefit predictive modeling, large-scale upscaling, data gap-filling, and surrogate modeling of wetland CH 4 emissions within earth system land models.
Pulse and respiratory fluctuations of intercranial pressure in hermetic cavity
The previous manned missions to the Moon represent milestones of human ingenuity, perseverance, and intellectual curiosity. However, one of the major ongoing concerns is the array of hazards associated with lunar surface dust. Not only did the dust cause mechanical and structural integrity issues with the suits, the dust 'storm' generated upon reentrance into the crew cabin caused "lunar hay fever" and "almost blindness" (Figure 1). It was further reported that the allergic response to the dust worsened with each exposure. The lack of gravity exacerbated the exposure, requiring the astronauts to wear their helmet within the module in order to avoid breathing the irritating particles. Due to the prevalence of these high exposures, the Human Research Roadmap developed by NASA identifies the Risk of Adverse Health and Performance Effects of Celestial Dust Exposure as an area of concern. Extended human exploration will further increase the probability of inadvertent and repeated exposures to celestial dusts. Going forward, hazard assessments of celestial dusts will be determined through sample return efforts prior to astronaut deployment. Studies on the lunar highland regolith indicate that the dust is not only respirable but also reactive, and previous studies concluded that it is moderately toxic; generating a greater response than titanium oxide but a lower response than quartz. The presence of reactive oxygen species (ROS) on the surface of the dust has been implicated. However, there is actually little data related to physicochemical characteristics of particulates and pulmonary toxicity, especially as it relates to celestial dust exposure. As a direct response to this deficit, the present study evaluates the role of a particulate's innate geochemical features (e.g., bulk chemistry, internal composition, morphology, size, and reactivity) in generating adverse toxicological responses in vitro and in vivo. This highly interdisciplinary study evaluates the relative toxicity of six meteorite samples representing either basalt or regolith breccia on the surfaces of the Moon, Mars, and Asteroid 4Vesta; three potential candidates for future human exploration or colonization. Terrestrial mid-ocean ridge basalt (MORB) is also used for comparison as a control sample.
In this study, we developed a three-way carbon dioxide (CO 2 ) flux-partitioning algorithm that separates net ecosystem exchange (NEE) into aboveground plant respiration (R above ), belowground root and soil respiration (R below ), and gross primary production (GPP). We applied this algorithm to a coupled dataset of continuous chamber-measured soil respiration and eddy covariance (EC)-measured NEE of CO 2 in an oak-hickory (Quercus-Carya) deciduous broadleaf forest from 2006 to 2015. We found that on annual time scale, R below dominated over R above with the former accounting for 66.9–86.4% and the latter 13.6–33.1%, of the total ecosystem respiration (R eco ). The ratio of R below to R above varied seasonally, ranging from 1.77 to 7.25 in growing season, and 1.02 to 4.57 in non-growing season. The temperature sensitivity (E 0 ) of R below was significantly higher than that of R above , and E 0 of R eco responded differently to air and soil temperature. Over the whole study period, annual mean R above , R below , and GPP were 243, 806, and 1170 g C m –2 , respectively, with annual R eco accounting for 89.6% of GPP, of which 68.8% was lost as R below and 20.8% lost as R above , and leaving only 10% of the carbon fixation in ecosystems. Furthermore, these estimates, however, did not consider potential light inhibition of leaf respiration. If we accept the presence of light inhibition, then the daytime three-way partitioning method would underestimate annual R above by 20.4% whereas the nighttime method would overestimate R above by 23.9% and GPP by 4.7%, compared with estimates accounting for light inhibition in leaves.
Whether and how CO 2 and nitrogen (N) availability interact to influence carbon (C) cycling processes such as soil respiration remains a question of considerable uncertainty in projecting future C–climate feedbacks, which are strongly influenced by multiple global change drivers, including elevated atmospheric CO 2 concentrations (eCO 2 ) and increased N deposition. However, because decades of research on the responses of ecosystems to eCO 2 and N enrichment have been done largely independently, their interactive effects on soil respiratory CO 2 efflux remain unresolved. Here, we show that in a multifactor free-air CO 2 enrichment experiment, BioCON (Biodiversity, CO 2 , and N deposition) in Minnesota, the positive response of soil respiration to eCO 2 gradually strengthened at ambient (low) N supply but not enriched (high) N supply for the 12-y experimental period from 1998 to 2009. In contrast to earlier years, eCO 2 stimulated soil respiration twice as much at low than at high N supply from 2006 to 2009. In parallel, microbial C degradation genes were significantly boosted by eCO 2 at low but not high N supply. Further, incorporating those functional genes into a coupled C–N ecosystem model reduced model parameter uncertainty and improved the projections of the effects of different CO 2 and N levels on soil respiration. If our observed results generalize to other ecosystems, they imply widely positive effects of eCO 2 on soil respiration even in infertile systems.
This study was designed to investigate the role of tissue oxygenation in some of the factors that are thought to regulate muscle respiration and metabolism. Tissue oxygenation was altered by reductions in O2 delivery (muscle blood flow x arterial O2 content), induced by decreases in arterial PO2 (PaO2). O2 uptake (VO2) was measured in isolated in situ canine gastrocnemius at rest and while working at two stimulation intensities (isometric tetanic contractions at 0.5 and 1 contractions/s) on three separate occasions, with only the level of PaO2 (78, 30, and 21 Torr) being different for each occasion. Muscle blood flow was held constant (pump perfusion) at each work intensity for the three different levels of PaO2. Muscle biopsies were obtained at the end of each rest and work period. Muscle VO2 was significantly less (P less than 0.05) at both stimulation intensities for the hypoxemic conditions, whereas [ATP] was reduced only during the highest work intensity during both hypoxemic conditions (31% reduction at 21 Torr PaO2 and 17% at 30 Torr). For each level of PaO2, the relationships between the changes that occurred in VO2 and levels of phosphocreatine, ADP, and ATP/ADP.P(i) as the stimulation intensity was increased were significantly correlated; however, the slopes and intercepts of these lines were significantly different for each PaO2. Thus a greater change in any of the proposed regulators of tissue respiration (e.g., phosphocreatine, ADP) was required to achieve a given VO2 as PaO2 was decreased.(ABSTRACT TRUNCATED AT 250 WORDS).
A recent burst of technological innovation and adaptation has greatly improved our ability to capture respiration rate data from plant sources. At the tissue level, several independent respiration measurement options are now available, each with distinct advantages and suitability, including high-throughput sampling capacity. These advancements facilitate the inclusion of respiration rate data into large-scale biological studies such as genetic screens, ecological surveys, crop breeding trials, and multi-omics molecular studies. As a result, our understanding of the correlations of respiration with other biological and biochemical measurements is rapidly increasing. Difficult questions persist concerning the interpretation and utilization of respiration data; concepts such as allocation of respiration to growth versus maintenance, the unnecessary or inefficient use of carbon and energy by respiration, and predictions of future respiration rates in response to environmental change are all insufficiently grounded in empirical data. However, we emphasize that new experimental designs involving novel combinations of respiration rate data with other measurements will flesh-out our current theories of respiration. Furthermore, dynamic recordings of respiration rate, which have long been used at the scale of mitochondria, are increasingly being used at larger scales of size and time to reflect processes of cellular signal transduction and physiological response to the environment. Herein, we also highlight how respiratory methods are being better adapted to different plant tissues including roots and seeds, which have been somewhat neglected historically.