Seasonal Relationships Research Articles

Determining the seasonal relationships between upstream flows and channel transmission losses along a dryland river reach

River transmission loss is the reduced amount of flow at downstream locations along a channel due to infiltration into the riverbed and riverbank, evaporation from water surface, transpiration by riparian vegetation and, temporary storage in the river and flood plains. Transmission losses reduce flood stage, recharge local and regional aquifers and, are main sources of groundwater recharge in dryland areas. This study determines the seasonal relationships between upstream flows and channel transmission losses along a river reach in Runde River catchment in Zimbabwe. Using regression equations, channel transmission loss volumes were modelled as the response variables while upstream flow volumes were the predictor variables. The study shows significant (p = 0.000) positive linear relationships between reach upstream flow and transmission loss during the cool, hot and rainy seasons. Also, during the post rainy season, a significant (p = 0.000) power relationship exist between reach upstream flow and transmission loss. This simple approach helps to understand water balances and transmission losses in data scarce dryland river systems.

Seasonality of Coastal Picophytoplankton Growth, Nutrient Limitation, and Biomass Contribution.

Picophytoplankton in the Baltic Sea includes the simplest unicellular cyanoprokaryotes (Synechococcus/Cyanobium) and photosynthetic picoeukaryotes (PPE). Picophytoplankton are thought to be a key component of the phytoplankton community, but their seasonal dynamics and relationships with nutrients and temperature are largely unknown. We monitored pico- and larger phytoplankton at a coastal site in Kalmar Sound (K-Station) weekly during 2018. Among the cyanoprokaryotes, phycoerythrin-rich picocyanobacteria (PE-rich) dominated in spring and summer while phycocyanin-rich picocyanobacteria (PC-rich) dominated during autumn. PE-rich and PC-rich abundances peaked during summer (1.1 × 105 and 2.0 × 105 cells mL–1) while PPE reached highest abundances in spring (1.1 × 105 cells mL–1). PPE was the main contributor to the total phytoplankton biomass (up to 73%). To assess nutrient limitation, bioassays with combinations of nitrogen (NO3 or NH4) and phosphorus additions were performed. PE-rich and PC-rich growth was mainly limited by nitrogen, with a preference for NH4 at >15°C. The three groups had distinct seasonal dynamics and different temperature ranges: 10°C and 17–19°C for PE-rich, 13–16°C for PC-rich and 11–15°C for PPE. We conclude that picophytoplankton contribute significantly to the carbon cycle in the coastal Baltic Sea and underscore the importance of investigating populations to assess the consequences of the combination of high temperature and NH4 in a future climate.

Assessing Net Growth of Phytoplankton Biomass on Hourly to Annual Time Scales Using the Geostationary Ocean Color Instrument

AbstractQuestions of whether diurnal changes in carbon fixation affect the global carbon budget cannot be answered using the present generation of polar orbiting ocean color sensors that can only retrieve one image daily. Here, we present novel satellite‐derived indices of chlorophyll‐based production based on the Geostationary Ocean Color Imager (GOCI), whose hourly imaging capability offer the potential for direct estimates of net phytoplankton growth over hourly to seasonal time scales. Our results reveal large variations in net chlorophyll growth in the GOCI study region, both over the day and between seasons. Hourly changes in chlorophyll concentration are highest during spring while growth rates show maxima during the winter. We show seasonal relationships between growth and photon flux. Our study suggests that Geostationary Ocean Color data can be used to constrain phytoplankton productivity on diurnal time scales and be an essential tool to better understand diurnal growth patterns over large spatial regions.

In the heat of the moment: Economic and non-economic drivers of the weather-crime relationship

Using daily data on the universe of crimes from 600 police stations in Karnataka, India between 2011 and 2016, and daily weather data from a dense network of monitoring stations, we study the daily and seasonal weather-crime relationship. We analyze a wide variety of crime types, and find that violent crimes respond to both daily and seasonal variation in temperatures and rainfall, whereas property crimes only respond to seasonal variation. The results provide novel evidence for the economic theory of crime, but also for the importance of non-economic drivers of violent crime, including violence against women and ethnically marginalized groups, and inter-group conflict.

The AFLW draft combine: Seasonal changes and relationships to draft success

ABSTRACT This study aimed to identify seasonal changes in AFLW Draft Combine assessments, examine the physical and anthropometric assessments associated with draft outcome and investigate the presence of a relative age effect. Three seasons (2017–2019) of the AFLW Draft Combine assessment data were obtained (n = 131). Testing data between seasons were examined using a MANOVA. A factor analysis using principal components (identifying speed, lower body power, aerobic capacity, and anthropometry) was conducted prior to the construction of a binary logistic regression model. Speed (including 5, 10 and 20 m sprint times) significantly contributed to the binary logistic regression model discriminating drafted and non-drafted players (p = 0.040). A significant main effect of season was reported (p ≤ 0.01) with post-hoc tests confirming 5, 10 and 20 m sprint times were faster in the 2018 AFLW Draft Combine compared with the 2017 AFLW Draft Combine. No relative age effect was observed in this dataset. Overall, the 20 m sprint test showed the greatest difference between drafted and non-drafted players, while speed (collectively) was the greatest predictor of draft outcome. This data provides insight into the physical qualities of prospective players that were associated with selection to the AFLW competition in its first 3 years.

Seasonal variability in phytoplankton light absorption properties: Implications for the regional parameterization of the chlorophyll a specific absorption coefficients

Data of in vivo absorption of particulate material in water column obtained from multiple research cruises performed in the Alboran Sea (Western Mediterranean Sea) were used to investigate seasonal variability of the phytoplankton light absorption properties. Specific absorption coefficients of phytoplankton, aph∗ (λ) were calculated and used to determine the performance of aph∗ (λ) parameterizations based on chlorophyll a concentration for each season. aph∗ (λ) in the blue spectral bands for the euphotic layer decreased by 20% in spring and summer compared with autumn and winter. These changes might reflect stronger dominance of diatoms during these periods, since these cells are characterized by a high degree of pigment packaging that leads to flattening of the absorption spectrum. Surface temperature and salinity, which are proxies for modifications of the surface layer by vertical mixing, explained more than 50% of the variability in the absorption properties, suggesting that the communities also presented high photo-acclimation capacity in response to short-term hydrological variability. The biases between measured and parameterized aph∗ (λ) decreased when the seasonal relationships between chlorophyll a concentration and aph∗ (λ) were used for estimating the parameterization coefficients instead of using the whole dataset. The regional parameterization using seasonal data performed better that parameterizations using global data. These seasonal and regional parameterizations can be useful for developing more refined bio-optical models of primary production for the study area, although it has to be taken into account that a significant percentage of variability in aph∗ (λ) related to short-term hydrological changes remained still unexplained by the seasonal parameterization.

Changes in Air Pollution-Related Behaviour Measured by Google Trends Search Volume Index in Response to Reported Air Quality in Poland.

Decreased air quality is connected to an increase in daily mortality rates. Thus, people’s behavioural response to sometimes elevated air pollution levels is vital. We aimed to analyse spatial and seasonal changes in air pollution-related information-seeking behaviour in response to nationwide reported air quality in Poland. Google Trends Search Volume Index data was used to investigate Poles’ interest in air pollution-related keywords. PM10 and PM2.5 concentrations measured across Poland between 2016 and 2019 as well as locations of monitoring stations were collected from the Chief Inspectorate of Environmental Protection databases. Pearson Product-Moment Correlation Coefficients were used to measure the strength of spatial and seasonal relationships between reported air pollution levels and the popularity of search queries. The highest PM10 and PM2.5 concentrations were observed in southern voivodeships and during the winter season. Similar trends were observed for Poles’ interest in air pollution-related keywords. Greater interest in air quality data in Poland strongly correlates with both higher regional and higher seasonal air pollution levels. It appears that Poles are socially aware of this issue and that their intensification of the information-seeking behaviour seems to indicate a relevant ad hoc response to variable threat severity levels.

Retrospective analysis of marine growth and relationships to return rates of Penobscot River Atlantic salmon

Beginning in the 1980s, return rates of Atlantic salmon (Salmo salar) to the Penobscot River, Maine, USA, declined and have persisted at low levels. This downturn coincided with similar declines in North American and European Atlantic salmon stocks and with changes in the Northwest Atlantic ecosystem. Previous studies investigated whether early marine growth explained the declines, but results varied, with decreased growth associated with declines in European stocks but not North American stocks. In this study, we evaluate whether growth over the entire marine stage is related to Atlantic salmon marine survival. We constructed a growth time series from scales of returned Penobscot River Atlantic salmon spanning periods of varying marine survival. We used analysis of variance (ANOVA) and post hoc tests to quantify seasonal growth increment differences and principal component analysis to characterize variability among the suite of growth increments. We observed reduced growth during the second winter and second marine year starting in the 1990s, with compensatory seasonal growth relationships. These results indicate that diminished growth during late marine stages is associated with low return rates in this population.

Seasonality of Tropical Photosynthesis: A Pantropical Map of Correlations With Precipitation and Radiation and Comparison to Model Outputs

AbstractTropical ecosystems strongly influence Earth's climate and weather patterns. Most tropical ecosystems remain warm year‐round; nonetheless, their plants undergo seasonal cycles of carbon and water exchange. Previous research has shown the importance of precipitation and radiation as drivers of the seasonality of photosynthetic activity in the tropics. Although data are scarce, field‐based studies have found that seasonal cycles at a handful of tropical sites do not match those in the land surface model (LSM) simulations. A comprehensive understanding and model comparison of how seasonal variations in tropical photosynthetic activity relate to climate is lacking. Here, we identify the relationships of precipitation and radiation with satellite‐based proxies for photosynthetic activity (e.g., GOME‐2 SIF, MAIAC EVI) for the pantropical region. Three dominant and spatially distinct seasonal relationships emerge: photosynthetic activity that is positively correlated with both drivers (36% of tropical pixels), activity that increases following rain but decreases with radiation (28%), and activity that increases following bright seasons but decreases with rain (14%). We compare distributions of these observed relationships with those from LSMs. In general, compared to satellite‐based proxies of photosynthetic activity, model simulations of gross primary productivity (GPP) overestimate the extent of positive correlations of photosynthetic activity with water and underestimate positive correlations with radiation. The largest discrepancies between simulations and observations are in the representation of regions where photosynthetic activity increases with radiation and decreases with rain. Our clear scheme for representing the relationship between climate and photosynthetic activity can be used to benchmark tropical seasonality of GPP in LSMs.

Relationship between land surface temperature and normalized difference water index on various land surfaces: A seasonal analysis

The present study examines the seasonal relationship between land surface temperature (LST) and normalized difference water index (NDWI) on various land surfaces in Raipur City of India by using a series of Landsat images for four specific seasons since 1991-92. The LST is retrieved using the mono-window algorithm technique. The results show that the LST of the study area is noticeably affected by surface composition. The best correlation (correlation coefficient r = 0.42) between the LST and NDWI is achieved in the post-monsoon season, followed by the monsoon season (r = 0.33), pre-monsoon season (r = 0.25), and winter season (r = 0.04). There is a moderate negative correlation (r = -0.49, -0.33, -0.31, and -0.25 in the pre-monsoon, monsoon, post-monsoon, and winter season, respectively) generated between the LST and NDWI on water bodies. On green vegetation, this LST-NDWI correlation is moderate positive (r = 0.67, 0.43, 0.50, and 0.25 in the pre-monsoon, monsoon, post-monsoon, and winter season, respectively). On human settlement and barren land surface, the correlation is weak positive (r = 0.24, 0.21, 0.27, and 0.15 in the pre-monsoon, monsoon, post-monsoon, and winter season, respectively). The output of the research work can be used in the town planning section of any urban agglomeration.

Investigation of the Influence of Water Vapor on Heavy Pollution and Its Relationship With AOD Using MAX‐DOAS on the Coast of the Yellow Sea

AbstractMulti‐AXis Differential Optical Absorption Spectroscopy (MAX‐DOAS) observations were carried out from March 1, 2019 to February 29, 2020 in Qingdao, China, on the coast of the Yellow Sea (120.67°E, 36.35°N). Atmospheric parameters retrieved from the MAX‐DOAS instrument included vertical profiles of aerosol extinction, gaseous aerosol precursors (NO2, SO2), and H2O. First, the seasonal relationship between aerosol optical depth (AOD) and the H2O vertical column density (VCD) was analyzed. The correlation coefficients (r) between AOD and H2O VCD were largest in the winter, followed by spring, autumn, and summer. In addition, the correlation during heavily polluted weather was much higher than that during clean weather or slightly polluted weather. Then, an analysis of the wind speed and direction, and trace gas VCDs during the months with frequent pollution (December 2019 and January 2020) found that heavy pollution episodes easily occurred in Qingdao due to a combination of high H2O concentrations and low wind speeds. Out of four pollution events (P1, P2, P3, P4), both the H2O concentration and pollution were highest during the first event (P1). The H2O VCD, AOD, sulfate AOD, and total column HNO3 simultaneously increased during P1, while the NO2 and SO2 VCDs decreased. These trends are consistent with liquid phase reactions. Finally, the 1,000 m backward trajectory for the wind and the gas profiles during P1 revealed that the pollutants increased in Qingdao due to the influence of a polluted air mass from the western inland regions.

Seasonal Changes and Relationships in Training Loads, Neuromuscular Performance, and Recovery and Stress State in Competitive Female Soccer Players.

Background: The purpose of this study was to examine seasonal changes in training load (TL), neuromuscular performance, subjective recovery, and stress state, and to investigate the relationships between acute and chronic TL and neuromuscular performance in competitive female soccer players.Methods: Nine competitive female soccer players (20.0 ± 1.7 years; 60.3 ± 6.3 kg; 164.0 ± 5.8 cm) completed the Short Recovery and Stress Scale and the countermovement jump (CMJ) with polyvinyl chloride pipe (CMJ0) and 20 kg barbell (CMJ20) at 2–3 h before 1st match (NC1), 6th match (NC2), 9th match (C1), and 15th match (C2) of the competitive season. TL included total distance, high-speed running, and PlayerLoad. Acute and chronic TL was calculated by using the average of 2 days (D2), 7 days (D7), and 21 days (D21) prior to four different match play.Results: Significant decreases were found from NC1 to C1 in D7 total distance [p = 0.03, Cohen's effect size (dz) = 1.40]. D7 total distance and PlayerLoad significantly decreased from NC to C1 and C2 (p = 0.001–0.01, dz = 1.40–1.72). Significant increases were observed from NC1 to C1 in CMJ0 jump height (p = 0.03, dz = 1.40), (p = 0.021, dz = 1.44), and peak power (p = 0.03, dz = 1.32). Significant negative correlations were observed for D7 total distance and CMJ0 jump height (p = 0.02, r = 0.79) and peak power (p = 0.03, r = 0.71) at C2, while significant positive correlations were observed at C1 for D7 PlayerLoad and CMJ0 jump height (p = 0.02, r = 0.80).Conclusion: Polyvinyl chloride pipe (CMJ0) jump height and peak power may increase from preseason to the midcompetitive season. Seasonal variations may affect the relationships between D7 TL and CMJ0 performance.

Seasonal variations in the synoptic climatology of air pollution in Birmingham, UK

A synoptic typing approach was undertaken to examine the seasonal relationship (winter versus summer) between air mass types and pollutant concentrations of O3, PM10, NOx, NO2 and CO in Birmingham, UK, from 2000 to 2015. Daily means of seven surface meteorological variables were entered into a P-mode principal component analysis. Three principal components explained 72.2% (72.9%) of the variance in winter (summer). Cluster analysis was used to group together days with similar PC scores and thus similar meteorological conditions. Six clusters provided the best air mass classification in both seasons. High pollutant concentrations were associated with anticyclonic types. In particular, tropical (polar) continental air mass type was most likely to produce extremely high concentrations in summer (winter). In winter, a sequence of Polar Continental (cool and humid) and Binary Mid-latitude Anticyclonic Maritime—Sub-Polar Cyclonic Maritime (cold and dry) induced severe pollution episodes in all pollutants. Whilst the mean duration of severe pollution episodes varied little between winter and summer (O3 was an exception, with severe episodes lasting 20% longer in summer), high pollutant extremes were more common in winter. This was due to more favourable meteorological conditions (e.g. temperature inversions) and increased anthropogenic emissions during the cold season.

Assessment of seasonal relationship between polycyclic aromatic hydrocarbon accumulation and expression patterns of oxidative stress-related genes in muscle tissues of red mullet (M. barbatus) from the Northern Adriatic Sea

In this study, we examined the seasonal association between Polycyclic Aromatic Hydrocarbon (PAH) concentrations and mRNA expression profiles of some antioxidant genes (i.e. CAT, GST and SOD), as well as lipid peroxidation (LPO), in muscle of sexually inactive females of red mullet (Mullus barbatus). Fish were captured in a fishery area of the Northern Adriatic Sea during both winter and summer. We found significantly (p < 0.05) higher ∑HMW-PAHs concentrations in muscle of specimens caught during winter than summer. On the basis of sampling season, red mullets exhibited different gene expression profiles of antioxidant enzymes showing lower levels of both CAT and GST in winter than in summer. Accordingly, CAT was found to be negatively associated with ∑PAH concentrations, especially ∑LMW-PAH, in individuals collected during winter. Seasonal-related downregulation of some oxidative stress biomarker expression is suggestive of greater susceptibility of red mullets to PAHs during winter.

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

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

Harmful Algae and Oceanographic Conditions in the Strait of Georgia, Canada Based on Citizen Science Monitoring

In British Columbia (BC), harmful algal blooms (HABs) regularly cause severe economic losses through finfish mortalities and shellfish harvest closures due to toxin accumulation, gill damage, or hypoxia. As there is no routine governmental monitoring of HAB phenomena in BC, HAB variability, and its potential links to environmental drivers are not well understood. Here we present results from a well-managed citizen science program which collected an unprecedented 4 year, high-resolution (∼bi-monthly, ∼80 stations) dataset of harmful algae (HA) concentrations and corresponding physical and chemical properties of seawater throughout the Strait of Georgia (SoG), BC. Analysis of this dataset revealed statistically significant interannual and seasonal relationships between environmental drivers and the most common HA taxa: Rhizosolenia setigera, Dictyocha spp., Alexandrium spp., Heterosigma akashiwo, Chaetoceros convolutus, and C. concavicornis. HABs exhibited significant interannual variations; specifically, no HABs were found during the summer of 2015, blooms of Dictyocha occurred in 2016 and 2017, and dense blooms of Heterosigma and Noctiluca occurred in 2018. In addition, HA prevalence corresponded with negative effects observed in local aquaculture facilities where higher toxins concentrations (causing Paralytic and Diarrhetic Shellfish Poisonings) in shellfish flesh were detected during years with greater abundance of Alexandrium and Dinophysis. Furthermore, salmon mass mortality at fish farms corresponded to years with high concentrations of Heterosigma and Dictyocha. As such, these results highlight the need for long-term data to evaluate the potential role of HA as a stressor on the SoG ecosystem.

Seasonal Relationship Between Net Primary and Net Community Production in the Subtropical Gyres: Insights From Satellite and Argo Profiling Float Measurements

AbstractThe ratio between net community production (NCP) and net primary production (NPP) is a useful index of carbon export efficiency (e‐ratio). Seasonal variations of e‐ratio are poorly documented due to the lack of field measurements. In this study, the satellite‐based NPP and Argo‐Oxygen (O2) based NCP were used to determine e‐ratio in the subtropical gyres. Comparisons with long‐term field measurements at the Hawaii Ocean Time‐Series showed good agreement in annual mean and spring‐summer (April–July) e‐ratio. With the short‐term tracer (O2) the satellite‐Argo approach revealed significant seasonal variations in NCP and e‐ratio in the subtropical gyres of the North Pacific, North Atlantic, and South Pacific. The satellite‐Argo‐derived annual mean e‐ratio in all three Northern Hemisphere sites were close to those from the temperature‐based empirical model, but significantly lower in the South Pacific subtropical gyre where the sub‐annual NCP variations were stronger.

Vulture Abundance and Habitat Association Following Major Hurricane Disturbance in the Tropical Dry Forest of Western Mexico

Scavenger birds are common species frequently associated with open habitats, but sympatric vulture species have differing natural history traits that may influence seasonal habitat relationships and responses to natural disturbances, such as hurricanes. We evaluated seasonality and habitat relationships of Black Vultures (Coragyps atratus) and Turkey Vultures (Cathartes aura) at sites within and outside the path of maximum winds of Hurricane Patricia in western Mexico. We used 1.5-km line transects to survey vultures during dry and rainy seasons in four habitats of the tropical dry forest biome over a 2-yr period after hurricane landfall. We measured habitat structure along each transect using the point-centered quarter method, and determined landscape composition within a 3000-ha circular plot centered around the midpoint of each transect. Vulture abundance was influenced by habitat structure variables of open areas, but at sites affected by hurricane disturbance vulture abundance was positively associated with increased cover of wetlands and agricultural land. Both species of vultures had low abundance in forests, and Black Vultures had significantly higher abundance in agricultural land and wetlands. Season significantly influenced vulture abundance by habitat: agricultural land and wetlands had higher vulture abundance in the rainy season, but forests had higher abundance in the dry season. Disturbance by a major hurricane induced species-specific changes in spatial-temporal abundance of vultures: the Black Vulture in particular had higher abundance in all habitats except wetlands during the dry season, and greater abundance in the first months after hurricane landfall. Hence, although vultures occur predominantly in open areas, they show species-specific habitat associations and responses to hurricane disturbance.

Positive relationship between seasonal Indo-Pacific Ocean wave power and SST

The influence of increasing sea surface temperatures (SSTs), in response to greenhouse warming, on wave power (WP) remains uncertain. Here, seasonal relationships between SST anomalies and mean and extreme WP over the Indo-Pacific Ocean are examined. Overall, seasonal WP has significantly increased over much of the Pacific, Indian, and Southern Ocean by 1.21–3.10 kW/m dec−1 over 1979–2019. Contributions from wave characteristics, namely significant wave height (SWH) and peak wave period (PWP), to changes in WP show that SWH contributes most in extra-tropical regions, and PWP most in tropical regions. Further, seasonal relationships between SST anomalies and WP indicate that increases in WP are also seen during strong El Niño years in December–February, and in-phase combinations of El Niño and positive Indian Ocean Dipole (IOD) events during June–August and September–November. Results highlight both long-term increasing SSTs and climate variability roles for inducing large-scale seasonal WP changes throughout the Indo-Pacific.

Time-of-Year Variation in Intraocular Pressure.

In this study conducted in Chicago, IL, intraocular pressure (IOP) level was found to have a subtle, but measurable, annual pattern. Reasonable evidence is presented for a time-of-year variation in IOP. Adequate numbers of subjects must be studied to detect this small variation. The aim was to investigate the relationship between IOP and time of year. During a separate investigation, patients from 2011 to 2018 (dataset A, N=3041) in an urban, academic facility in Chicago, IL received an examination that included Goldmann applanation tonometry. Regression analyses assessed the relationship between time of year and IOP. Two additional datasets, 1 collected in a similar manner during 1999 and 2002 (dataset B, N=3261) and another consisting of all first visits during 2012 and 2017 (dataset C, N=69,858), were used to confirm and further investigate trends. For dataset A, peak mean IOP occurred in December/January (15.7±3.7/15.7±3.8 mm Hg) and lowest in September (14.5±3.1 mm Hg). The analysis suggested conventional quarterly analysis (January to March, etc.) can conceal time-of-year relationships because of inadequate statistical power and timing of IOP variation. Multiple linear regression analysis, with a November-to-October reordering, detected an annual, downward IOP trend (P<0.0001). Analysis of dataset B confirmed this trend (P<0.001). Fourier analysis on datasets A and B combined supported a 12-month IOP cycle for right/left eyes (P=0.01/P=0.005) and dataset C provided stronger evidence for an annual periodicity (P<0.0001). Harmonics analysis of dataset C showed a repeating pattern where IOP trended downward around April, and then back upward around October. This analysis strongly supports a demonstrable annual, cyclical IOP pattern with a trough to peak variation of ≈1 mm Hg, which has a seasonal relationship.