Properties of conventional playing surfaces have been investigated for many years and the stiffness of the surface has potential to influence athletic performance. However, despite the proliferation of different infilled artificial turfs with varying properties, the effect of surface stiffness of these types of surfaces on athlete performance remains unknown. Therefore, the purpose of this project was to determine the influence of surface stiffness of artificial turf systems on athlete performance. Seventeen male athletes performed four movements  on five surfaces of varying stiffness: Softest (−50%), Softer (−34%), Soft (−16%), Control, Stiff (+17%). Performance metrics  and kinematic data were recorded during each movement and participants performed a subjective evaluation of the surface. When compared to the Control surface, performance was significantly improved during running , the agility drill (Softest) and vertical jumping (Soft). Subjectively, participants could not discern between any of the softer surfaces in terms of surface cushioning, however, the stiffer surface was rated as harder and less comfortable. Overall, changes in surface stiffness altered athletic performance and, to a lesser extent, subjective assessments of performance, with changes in performance being surface and movement specific. Artificial turf surfaces have risen in popularity in recent years, with estimates of over 6000 artificial surfaces installed in North America, and 1000 to 1500 new installations each year [Manipulating stiffness of athletic surfaces has shown potential in terms of increasing athletic performance ,3,4,5 anEnergy loss is influenced by the properties and components of the sport surface. Mechanical drop tests on conventional running surfaces have shown energy loss ranging from 50% to 78% depending on the specific surface ,10, and Aside from direct storage and return of energy by the surface, the stiffness of the surface can also have a direct influence on the movement patterns and energy expenditure of the athlete. Athletes will alter their biomechanics when interacting with different surfaces ,10. InteIt appears that both short duration  and long duration (running) performance can be influenced by changes in surface stiffness. While these results are positive, it should be noted that many of these studies utilized extreme changes of stiffness or had athletes performing very controlled non-sport specific movements. When considering the stiffness of artificial turf systems, studies have shown that varying stiffness can influence peak vertical accelerations during running  as well Therefore, the purpose of this project was: (i) to determine the influence of surface stiffness of artificial turf surfaces on athlete performance; (ii) to investigate changes in kinematics on surfaces that have altered performance to gain insight into the mechanisms involved in any performance changes.Seventeen male competitive football and soccer athletes were recruited for the experiment . Informed written consent was obtained from all participants prior to data collection, with the study being conducted in accordance with the Declaration of Helsinki, and the protocol approved by the University of Calgary’s Ethics Board (REB18-0941). All participants were provided with an adidas X19.3 cleat  in either a US men’s size 9, 10, 11 or 12.The five different artificial turf surface conditions that were used in the investigation were constructed and installed outdoors over an asphalt surface, with the stiffness of the surfaces altered through changes in shock pad material (surfaces 1–3) or changes in carpet and infill material (surfaces 4–5).2. Surfaces #1–4 had identical carpet and infill compositions, with the only differences between them being their shock pad material (or lack of shock pad for surface 4). Surface #5 did not contain an underlying shock pad, with changes in stiffness being attained through differences in both the infill composition and density of the carpet fibers (lower density of fibers −1220 g/m2). Surface 4 was termed as Control, due to it being the common surface installed by the manufacturer for high performance sporting activities.All surfaces contained the FieldTurf  Classic HD 2.5” base carpet with carpet for surfaces #1–4 having a fiber density of 1220 g/mFollowing construction of all turf surfaces, mechanical drop test measurements were performed following modified American Society for Testing and Materials (ASTM) standards F355  and F193Data collection consisted of two testing sessions; during session one running economy was measured, while during session two sprint, agility and jump performance was measured on the different surfaces.2 and CO2 sensors were calibrated with a gas containing known concentrations of O2 and CO2 following the Matheson Certified Calibration Standard. The final calibration step involved calibrating the sampling turbine with a 3.0 L syringe  to ensure accurate volumetric measurements. When the participant was ready to begin their warmup, they were outfitted with a heart rate monitor and a breathing mask  connected to the Cosmed . As data was collected outdoors, a recent study has shown the Cosmed K5 to be valid for measuring submaximal gas-exchange variables in an outdoor environment . Immediae Cosmed . The Cos2 production [2 production consistently exceeded O2 consumption, this indicated that the exercise intensity associated with AnT had been reached. This incremental test served two purposes: (1) it identified the speed at which each participant would run during data collection, which was identified as 1.0 mph below the speed at which AnT was reached and (2) it allowed the participants to warm-up prior to data collection.The test session began with an incremental running test to a submaximal intensity. The participant began running at 2.5 m/s and increased their speed by 0.22 m/s every 2 min. Running speed was controlled by a computer program that output loud audible beeps set to coincide with when the participant should be reaching the end markers (20 m apart) labelled on each turf surface. The participant continued running at faster speeds until they reached anaerobic threshold (AnT). The identification of AnT uses multiple variables to provide an understanding of exercise intensity but the most commonly used variables during testing were (1) a non-linear increase in pulmonary ventilation and (2) the point of excessive COoduction . Once CO2 consumption over the last two minutes of the trial was calculated for analysis.After completing this incremental test, the participant was allowed to rest for ten minutes. Then a series of five five-minute constant speed running trials were performed, one on each surface, with five minutes of rest between each trial. The order of surfaces that the trials were performed on was randomized. For each running trial, the average ODuring the second testing session, participants performed three performance drills on each of the different surfaces: 5-10-5 agility drill, 10 m sprint acceleration and running vertical jump.The 5-10-5 agility drill had the athlete starting by straddling a photocell timing light. When instructed to begin, the athletes turned 90° and burst forward 5 yards, then turned 180° and moved in the opposite direction for 10 yards before again turning 180° and reversing direction and sprinting 5 yards back to the starting position . Brower The maximal effort vertical jump was performed with a Vertec jump meter, with the athletes being instructed to jump as high as possible. Participants were allowed to perform any approach they desired with the goal of reaching as high a level as possible on the jump meter. Participants were provided with enough practice trials in order to attain their preferred jumping technique and were required to maintain this technique throughout the duration of the testing session .Lastly, participants performed a maximum effort 10 m sprint acceleration. Athletes started in a stationary, self-selected stance at the starting line, accelerated forward while breaking the starting line timing gates and sprinted 10 m through the finish line timing gates . Sprint Three trials were collected during each drill on each of the five surfaces, with the athletes also performing practice trials of each movement prior to testing to mitigate learning effects. As with the running session, the surfaces were used in a randomized order and the mean of the three trials on each surface was used for comparisons.Biomechanical data were also recorded at 240 Hz during the second testing session (sprint/agility/jump) using a full body inertial motion capture system . The motion capture system consisted of 17 motion trackers placed at anatomical locations on the body with each tracker containing a 3D linear accelerometer, 3D rate gyroscopes, 3D magnetometers and a barometer. Following placement of the trackers, a neutral pose of the athlete was taken that defined the anatomical axis while also determining the relative orientation/location of each tracker. Following completion of the calibration pose, a joint coordinate system was established allowing for 3D kinematics to be measured during each movement. Following data collection, joint angles and foot contact phases were calculated within MVN Analyze 2020.0.2 using proprietary algorithms  and then output and imported into Matlab R2019a  where the step of interest was extracted, and peak values were calculated for each trial using custom code. Kinematics during the different movements were only investigated if a performance difference was observed during the sprint, agility or vertical jump test (kinematics were not measured during the running testing session). Due to space constraints, kinematics during a single stance phase for each movement were compared—the closest stance phase at the 5 m mark during the sprint, the initial plant leg during the first change in direction during the agility drill and the initial touchdown leg during the jumping movement of the vertical jump and reach test. Peak sagittal plane angles and angular velocities of the ankle, knee, and hip joint, as well as the trunk and center of mass, were compared to the Control condition.Prior to the experiment participants filled out an initial questionnaire rating their ideal surface properties of cushioning, on a 5-point Likert scale with text anchors of very soft to very hard. Subjective assessments were then collected using a questionnaire that had athletes rank the surfaces on a five-point Likert scale for the following qualities: cushioning (very soft to very hard), cushioning comfort (very uncomfortable to comfortable), perceived athlete performance (very poorly to very well) and overall surface rating (worst surface ever to best surface ever). These assessments were taken during both testing sessions and were recorded immediately following performance on a specific surface.t-test at a significance level of α = 0.10 with 95% confidence intervals of the differences (95% CIDiff) being reported. Data was formally tested for violation of normality using a Shapiro-Wilk test of normality. The level of significance was chosen as p < 0.10 because the consequences of incorrectly accepting a false result (possibly slightly increased expenses for turf owners and manufacturers) are minor in comparison to the benefits of a positive effect (improved athlete performance). The main outcome variables were the specific performance measurements . If differences in performance occurred, kinematics were investigated and were only compared between surfaces that had significant differences in performance using a paired t-test at a level of α = 0.10. Secondary outcome variables included the subjective assessment measurements on each surface, which were also analyzed using a paired t-test at a level of α = 0.10 [All data was compared to the Control surface using a paired α = 0.10 ,20.Reliability of the timed movements was measured using calculation of the intraclass correlation coefficient and their 95% confidence intervals based on an intra-rater reliability absolute agreement, two-way mixed model. Effect size (Cohen’s d) calculations were made following the method of Cohen (1992)  and DunlAll statistical analyses were performed using SPSS software v12.0 .Reliability data of the different timed movements is shown in p = 0.069, 90% CIDiff = −0.103 to −1.912) and Softer  surfaces resulted in significant reductions in oxygen consumption, both with small effect sizes  when compared to the Control surface. No differences were present during the 10 m sprint movement, regardless of surface stiffness. During the agility drill movement, the Softest surface  resulted in improved performance compared to the Control surface, with a medium effect size (0.57). Increased vertical jump and reach performance was present when jumping on the Soft surface compared to the Control  with a medium effect size (0.60); however, no other surfaces yielded any jumping performance differences.No data violated the assumption of normality , performance data are shown in p = 0.069, 90% CIDiff = 0.023 to 0.398), with a medium effect size (0.58), an increased peak ankle plantarflexion angle during the change of direction  with a medium effect size (0.54) and a greater trunk lean angle when completing the change of direction , with a medium effect size (0.55) on the Softest surface compared to the Control  with a medium effect size (0.57), and the peak knee extension angular velocity  with a medium effect size (0.54) were both increased, as well as the vertical center of mass velocity at takeoff , with a medium effect size (0.62) when jumping on the Soft surface compared to the Control.During the vertical jump, differences in kinematics were observed in both the ankle and knee joint as well as for the center of mass . Specifip = 0.083, 90% CIDiff = 0.032 to 1.093) with a medium effect size (0.66) and gave it a lower comfort rating  with a medium effect size (0.76).The subjective assessment of cushioning and cushioning comfort is shown in p = 0.070, 90% CIDiff = −0.057 to −1.068) with a large effect size (0.86)  .p = 0.068, 90% CIDiff = 0.02 to 0.686) with a medium effect size (0.58).When participants rated the surfaces overall , all surThe main goal of this study was to investigate the influence of surface stiffness of artificial turf on athlete performance. The results of the study indicate that changes in surface stiffness can influence athletic performance, alter kinematics and to a lesser extent subjective assessment of performance, with changes in performance being surface and movement specific.During steady state running, improvements in running economy of over 2.5% were observed when performing on the Soft surface (16% lower stiffness) and Softer surface (34% lower stiffness). This result supports a previous finding that surface stiffness can influence running performance ,24. UnfoDuring the 10 m sprint there were no differences in performance on any of the surfaces. This lack of difference was likely due to the magnitudes of stiffness differences not being substantial enough to elicit performance differences. Data from Gains et al. (2010)  would seDuring the cutting agility drill, the softest surface resulted in a significant increase in agility change of direction performance. This supports previous work, which has shown a more compliant surface results in improvements in change of direction performance ,27. ExamLastly, during the jump and reach movement the soft surface increased performance by 2.4%. When on this surface, participants were able to increase their peak ankle and knee joint angular velocity and as a result their center of mass velocity at takeoff. Apampatzis et al. (2004) [Subjectively, participants could not discern between any of the reduced stiffness surfaces in terms of surface cushioning; however, the Softest surface was rated closest to their ideal cushioning value (which was softer than the Control). Increasing stiffness of the surface did result in changes in subjective ratings with participants perceiving that the surface was stiffer, rating it as such and also providing this surface with a lower comfort rating. This lower comfort score potentially also resulted in the perception of a decreased performance on this surface . Lastly,2 vs. 1118 m/s2). This surface would provide increased performance during running and vertical jumping and would not negatively affect performance during the other movements (sprinting and agility). Based on the data in this study, when selecting surface properties such as stiffness, the main movements on the surface should be taken into consideration; for example, if rapid change of direction movements are commonly performed on the surface, then the Softest surface, with a reduction of 50% from the Control (559 m/s2 vs. 1118 m/s2), should be selected. Subjectively, participants could not distinguish between any of the softer surfaces in terms of surface cushioning; however, the stiffer surface was rated as harder and less comfortable. Overall, changes in surface stiffness altered athletic performance and, to a lesser extent, subjective assessments of performance, with changes in performance being surface and movement specific.Overall, in terms of performance, during the running, agility and vertical jump movements, there were specific surfaces that resulted in increased performance. Running was optimized on a Soft and Softer surface; agility was optimized on the Softest surface and jumping was optimized on the Soft surface. Therefore, from the surfaces measured in the current study, if maximizing performance is the desired goal, it is recommended that the Soft surface be used (16% softer than Control, 971 m/s


Dairy cows housed on pasture are commonly afflicted by face flies, which develop as larvae in cow manure. Some organic dairy producers graze chickens in succession behind cattle as an effort to disrupt the development of dung fly larvae, but this method has yet to be validated as a successful method of pest management. In a controlled research trial, pastured broiler chickens did not reduce the survival of face fly larvae that developed in cow dung pats. This finding was buoyed by broiler behavioral observations, which revealed the broilers were unwilling to forage in dung pats. In general, broilers were reluctant to leave their shelter as solar radiation increased and climatic conditions were associated with the displacement of time allocated to sitting and sleeping behaviors. Dairy producers should take heed when adopting methods of fly control that rely on broiler chickens to willingly forage in cow dung pats especially when climatic conditions are aversive.Musca autumnalis De Geer) larvae in cow dung pats on pasture. Ninety-nine pats in three replicates were inoculated with first-instar larvae and exposed to one of four treatment conditions for 3 to 4 days: (1) an environment-controlled greenhouse (GH); (2) pasture without broilers (NEG); (3) pasture with 25 broilers stocked at a low density of 2.5 m2 of outdoor area per broiler (LOW); and (4) pasture with 25 broilers stocked at a high density of 0.5 m2 of outdoor area per broiler (HIGH). Broiler behaviors and weather conditions were recorded twice daily. Survival rates of larvae  were similar for pats in the NEG , LOW , and HIGH  groups, and was greatest for larvae reared in the GH  group compared to all other groups. The proportion of broilers observed pasture ranging was 14.0% (6–28%) but was negatively related to solar radiation. Broilers were never observed foraging in pats. Results indicate that use of broilers may not be an effective method for controlling larvae of dung pat breeding flies.The objective of this study was to evaluate Freedom-Ranger broiler chickens as a method to control face fly ( Musca autumnalis De Geer) is a common pest of pastured cattle. Adults of the face fly feed primarily on excretions around their host’s eyes, and are notorious vectors for the bacterium Moraxella bovis, which causes infectious bovine keratoconjunctivitis—commonly known as pinkeye [On organic dairy farms in the United States of America (USA) and Europe, the face fly  on cattle for up to 1–3 days after application [The use of synthetic substances for fly control on organic cattle is restricted by regulations set forth by the United States Department of Agriculture National Organic Program, which maintains official federal standards for organic production practices §205.603) . The inc.603 . Thlication ,8. Some lication ; yet, efSource reduction of dung breeding flies with free ranging chickens may be a feasible option for organic dairy farms. Adult female dung flies lay their eggs in fresh cow manure, which provides nutrition and safety for the development of immatures . Once thSome producers believe that chickens will consume dung fly larvae in dung pats, and that grazing cattle and chickens in succession as part of a diversified system is an effective method of disrupting dung fly developments . In a suAlternative management strategies used in organic livestock production require support from controlled research trials to confirm that the strategies indeed improve animal welfare. Research surveying organic dairy producers and veterinarians in the USA acknowledged that the lack of scientific support for certain practices utilized by organic livestock producers jeopardizes animal welfare ,17. FlieLittle is known about broiler behaviors, such as movement on pasture, time budgets, and foraging from dung pats or elsewhere. The consumption of pasture contents, including forages, insects, and larvae, may be affected by weather and stocking density . TherefoThe objectives of this study were: (1) to determine if broiler chickens affect the survival rate of face fly larvae presented in cow manure pats on pasture, and (2) to assess broiler pasture ranging and behaviors and their responses to weather conditions.The University of Minnesota Institutional Animal Care and Use Committee approved all animal care and procedures specific to this experiment (protocol number #1607-33960A).Bos taurus L.) and broiler chickens . The dairy herd and pastureland used in this study had been certified organic since 2010 by the Midwest Organic Services Association, following regulations set forth by the United States Department of Agriculture National Organic Program. Cows in this study were housed on pasture for 22 h per day and spent the remaining 2 h per day for milking procedures which took place twice daily in a swing-nine para-bone milking parlor at 06:00 h and 17:00 h. A total of 80 cows grazed the pastures used in this study, which were rotationally stocked at a rate of 4 cows per ha. Cows rotated to a new paddock every 2 days based on forage biomass availability. Pastures included perennial forbs, grasses and legumes, such as alfalfa (Medicago sativa L.), chicory (Cichorium intybus L.), meadow brome grass (Bromus riparius Rehmann), meadow fescue (Schedonorus pratensis (Huds.) P. Beauv), orchard grass (Dactylis glomerata L.), perennial ryegrass (Lolium perenne L.), red clover (Trifolium pratense L.) and white clover (Trifolium repens L.). Cows had ad libitum access to minerals and water, and were supplemented with 2.72 kg of organic corn grain daily.The experiment was conducted from June to August 2018 at the West Central Research and Outreach Center  in pastures that were consecutively grazed by lactating dairy cows  in three replicate groups of 50 that hatched on 1 May, 29 May, and 9 July, respectively. The Freedom Ranger hybrid consisted of a four-line cross developed in the 1960’s to meet the French Label Rouge Free Range program standards. For each replicate group, day-old broiler chicks that were vaccinated for Marek’s at the hatchery were housed in a 2.22 mchickens ,22. PensFor the duration of the study, each group of broilers had ad libitum access to water and granite grit, and were fed a restricted diet of 113 g of concentrate per bird  daily at dusk (between 21:00 h and 22:00 h) prior to shelter confinement and removed between 05:00 h and 06:00 h the next morning to encourage pasture foraging. The health of each bird was assessed prior to study initiation, starting at 4 weeks of age and weekly thereafter. Hock lesions and foot pad lesions were assessed during each weekly heath assessment. No broilers had hock or foot pad lesions or showed signs of gait difficulties.M. autumnalis) larvae into 5 g of dung in each of 33 covered Petri dishes. Larvae were obtained from a lab colony. Petri dishes and their contents were stored at 23 °C to delay development until treatment assignment. At 12:00 h, one-liter dung pats  were consecutively deposited in treatment conditions and inoculated with maggots by random assignment among the four treatment conditions: (1) on 8 cm of sand in 5-L buckets in a naturally ventilated environment-controlled greenhouse ; (2) on pasture without broilers ; (3) on pasture with broilers stocked at a low density ; or (4) on pasture with broilers stocked at a high density . This study was conducted as a randomized complete block design with repeated sampling, blocked by replicate group. On each block’s day of treatment initiation , fresh dung was collected between 05:00 h and 06:00 h from randomly selected cows in neighboring paddocks, homogenized by hand mixing, and stored in a covered bucket until use the same morning. Inocula for dung pats were prepared by counting and transferring aliquots of 100 first-instar face fly  and HIGH (10 pats 0.5 m apart) treatment groups, and adjacent to the broiler pens for the NEG treatment group (10 pats 0.9 m apart). Pats were inoculated by each Petri dish into the center of a recipient pat. Treatment within replicate served as the experimental unit (3 replicates of 4 treatments per rep = 12) and pat within experimental unit was treated as a sub-sample. Over the three replicates, average (± SD) broiler age was 48 ± 10 days and average broiler weight was 1.94 ± 0.7 kg at the onset of the experiment.Once inspections indicated the transplanted larvae reached the third-instar, after 3–4 days, pats and the 3 cm of soil underneath pats in the NEG, LOW, and HIGH treatment groups were transferred to 5-L buckets with 8 cm of sand. The buckets were housed in the greenhouse neighboring the buckets housing pats of the GH treatment group until the larvae began to pupate after 3–5 days. The number of larvae and pupae were then counted in each bucket by wet sieving sand and pats through a 1.41 × 1.41 mm square wire mesh sieve to extract surviving larvae and pupae.Behavior observations were recorded by an observer for the second and third replicates of the study in the morning (between 09:00 h and 11:00 h) and afternoon (between 13:00 h and 17:00 h) when precipitation was not expected for a total of two observation periods per day. Prior to behavior observations, pasture ranging was recorded for each pen as the proportion of broilers outside of the shelter. Behaviors were then recorded in continuous 60 s observation periods on 10 individual focal broilers per pen using the Animal Behaviour Pro mobile app (version 1.2) . Focal bThe University of Minnesota West Central Research and Outreach Center weather station recorded measures of ambient humidity, ambient temperature, precipitation, solar radiation, and wind speed every 15 min. The comprehensive climate index (CCI) was calculated to describe the apparent temperature based on ambient humidity, ambient temperature, solar radiation, and wind speed variables . For eacglmmTMB package [Logistic regression models with beta error distributions and logit link functions were used to analyze seven binomial outcomes for larval survival, and broiler pasture ranging and behaviors. Modeling was accomplished in RStudio (version 1.3.1073)  using th package . All modp-values between stocking density. Therefore, observations were pooled, and the correlation coefficient is reported with the corresponding degrees of freedom (df).Nonparametric correlation coefficients, Spearman’s rho, were used to examine pair-wise relationships between pasture ranging and behaviors and weather conditions at each time of observation. Stocking density treatment could not be included as an independent variable in correlations, so each correlation was initially performed on each stocking density treatment and replicate; there were no differences in direction or The one weather variable with the strongest correlation with the chosen dependent variable was included in the models for pasture ranging and behaviors. For the analysis of pasture ranging, a fixed covariate of solar radiation was included. The analyses for behaviors of the time budget included a fixed covariate of CCI and a random effect of broiler ID to account for repeated sampling. For the analysis of foraging events, pen averages were taken to represent the proportion of broilers observed performing the behavioral event for each observation and no covariate was included in the model based on the absence of a relationship between foraging and climatic conditions.2 tests were used to test the significance of main effects and are reported with the corresponding degrees of freedom followed by number of observations. The Tukey adjustment was applied to compare groups when the corresponding main effect had p ≤ 0.05. Marginal mean rates and 95% confidence intervals (CIs) for all responses were transformed to the natural scale. Treatment groups were compared using rate ratios (RRs), the ratio of mean rates between two groups.Type II Wald χDaily weather conditions over the course of the experiment are displayed in 2 = 55.2, p < 0.01).Larval survival rates by treatment are shown in p < 0.01). The NEG, LOW, and HIGH treatment groups had similar survival rates (p > 0.70).For the effect of treatment, the survival rates (95% CI) were 54.4% (36–72%), 4.4% (2–9%), 5.6% (3–11%), and 3.2% (2–7%) for pats in the GH, NEG, LOW, and HIGH groups, respectively. The survival rate for larvae in the GH treatment group was greater  compared to the NEG , LOW  and HIGH  treatment groups (2 (64–679 W/m2), and 0.74 m/s (0–1.8 m/s), respectively.The means (range) for CCI, ambient humidity, ambient temperature, solar radiation, and wind speed recorded during observations were 30.7 °C (15–40 °C), 73% (57–87%), 23.2 °C (16–28 °C), 415 W/m2 = 8.9, p < 0.01). There was no effect of stocking density on pasture ranging. On average, only a small proportion of the flock was observed pasture ranging . Furthermore, no birds were observed pasture ranging for over a third (36%) of the observations. Results for the analysis of pasture ranging indicate that broilers are less likely to range in the pasture during periods of high solar radiation regardless of stocking density treatment and suggest that overall pasture use is low for the experimental conditions of the study, which were characterized by open cattle grazing pasture and lack of tree cover.There was an effect of solar radiation on pasture ranging, such that ranging decreased as solar radiation increased  = 6.2, p = 0.01) and sleeping  = 4.6, p = 0.03). On average, the time budget (95% CI) was comprised of 41.4% (31–52%) sitting, 30.1% (20–43%) standing, 14.1% (8–24%) sleeping, and 1.4% (1–3%) traveling.The time budget estimates for the effect of CCI are visualized in The time budget analyses indicated that for every 1 °C increase in CCI, the proportion of time broilers were observed standing increased by a factor of 1.10 . Alternatively, the proportion of time broilers were observed sleeping decreased by a factor of 0.92 for every 1 °C increase in CCI . These results indicate that increased CCI values between 16 °C and 39 °C may disrupt sleeping and standing behaviors.Correlations between time budget behaviors and other climatic conditions recorded during observations are shown in For the analysis of ground foraging, there was no effect of stocking density treatment. On average, the percentage of broilers recorded ground foraging during observations was 21.5% (95% CI = 6–54%). At least one broiler ground foraged during 90% of observations. Broilers were never observed pat foraging, but predation of insects and frogs was observed during ground foraging events.Correlations between ground foraging and climatic conditions recorded during observations indicated that ground foraging was not associated with any climatic condition .Cairina moschata L.) successfully consumed and reduced populations of house fly (Musca domestica L.) larvae and adults in closed calf rooms, but not in open maternity pens [Gallus gallus domesticus) and African geese (Anser cygnoides L.) reduced the number of insect pests in an apple orchard intercropped with potato crops [Freedom Ranger broilers had no effect on survival rates of face fly larvae. This study is the first to specifically examine predation on dung fly larvae by pastured poultry. Related studies on the utilization of poultry as fly predators reported that pastured laying hens were successful at managing weed seeds . Furtherity pens ,30. Anotto crops . Under fto crops ,30,31 agHermethia illucens L.), house fly (Musca domestica L.), and yellow mealworm (Tenebrio molitor L.) larvae can successfully be used as a palatable feed supplement for poultry. Although research on the palatability of face fly larvae for poultry is sparse, insect larvae in general is a highly attractive feed source for poultry.It is unknown whether face fly larvae are truly an attractive feed source for broilers. Anecdotal evidence suggests that face fly larvae and pupae are highly sought after when they are hand-fed to broilers. In an early study, Dashefsky et al.  successfThe Freedom Ranger broilers used in the current study were a hybrid cross of several strains and were originally bred for their suitability for pasture housing systems. Previous studies ,38 suggeStark differences in larvae survival rates were apparent between pats reared in the pasture treatment groups  and those raised in the greenhouse (GH). Valiela  also repThe overall survival rates of larvae in this study were lower than previous reports. Valiela  reportedCool temperatures may have increased the mortality of face fly larvae for the current study. First-instar larvae are especially prone to temperature extremes since their mobile abilities are not fully developed. In an experiment on the survival of face fly first-instar larvae, Valiela  found thSphaeridium spp.) larvae and rove beetles (Philonthus cruentatus Gmelin) preyed upon face fly larvae [S. lunatum Fabricius and S. scarabaeoid L.) and rove beetles (P. cruentatus) in Minnesota [S. scarabaeoid) and rove beetles (P. cruentatus) reduced the larvae survival rates by 14% and 57%, respectively. Moreover, the presence of both predators reduced the larvae survival rate by 66% (ibid). Based on this information, it is possible that naturally occurring dung beetles and rove beetles preyed on face fly larvae of the current study, which would explain the majority of the survival differences among pats raised in the greenhouse and pats raised in the pasture.Naturally occurring predatory arthropods may have consumed some of the face fly larvae. It is possible that dung beetle  larval survival from 45% to 10%. Based on this information, it is possible that the consumption of perennial ryegrass (L. perenne) included in the pastures of the current study resulted in the presence of these alkaloids and consequently lowered the survival of the fly larvae.It is possible that the cattle dung use in this study reduced the survival of fly larvae due to the presence of alkaloids. A recent study by Parra et al.  reported2. Hegelund et al. [Gallus gallus L.), which rely on vegetative cover for protection from predators [A fundamental necessity for the successful utilization of broilers as a method of controlling dung fly immature development is pasture ranging. For the current study, only an average of 14.0% of broilers were observed ranging, which was negatively affected by increasing solar radiation. Previous studies using slow-growing strains  similarly reported that 9 to 25% of broilers were observed ranging ,45,46 and et al.  reportedredators . Since tOutdoor structural enrichments providing cover may make pasture ranging more desirable to broilers by filtering solar radiation that causes excessive heat  and provBehavioral observations supplement the face fly larvae survival findings of the current study. Broilers were never observed foraging in the dung pats. In fact, broilers spent most of their time sitting. Fanatico et al.  also repIt is unknown whether or not broilers of an age group older than that used in the current study (approximately 7-weeks-old) would have yielded different study results. Fanatico et al.  reportedTo our knowledge, this is the first study to provide evidence that Freedom Ranger broilers do not forage for face fly larvae in cow dung pats in uncovered cattle pasture. Future research should investigate other poultry types and species, including laying hens, ducks, and geese, to fully understand whether poultry may be used as a biological control for managing dung flies on organic dairy farms.2 and 0.5 m2 of outdoor area per broiler had no effect on the survival of face fly larvae in cow dung pats in this study. Larva survival rates were greater when reared in an environmentally controlled greenhouse compared to those reared on pasture. Solar radiation had a moderate to strong negative association with broiler pasture ranging. The comprehensive climate index  was associated with broiler allocations of time spent sitting and sleeping, indicating that weather conditions may displace broiler time budgets. Broilers were never observed foraging in dung pats but were often observed foraging in other areas of the pen. Broiler pasture ranging and behavioral results indicate that weather conditions may affect the behaviors necessary for dung fly larva predation, but nevertheless pastured Freedom Ranger hybrid broiler chickens were not a successful method of face fly larva control in this study.Pastured Freedom Ranger hybrid broiler chickens stocked at 2.5 m


The majority of fungi show distinct patterns of seasonal mycelial production, with most ectomycorrhizal fungi colonising ingrowth bags in the spring or summer, while the autumn and winter colonisation was mostly due to moulds. Our results indicate that fungal taxa differ in their seasonal patterns of mycelial production. Although fungal biomass turnover appears all-year-round, its rates are much faster in the period of plant activity than in the cold season.In temperate forests, climate seasonality restricts the photosynthetic activity of primary producers to the warm season from spring to autumn, while the cold season with temperatures below the freezing point represents a period of strongly reduced plant activity. Although soil microorganisms are active all-year-round, their expressions show seasonal patterns. This is especially visible on the ectomycorrhizal fungi, the most abundant guild of fungi in coniferous forests. We quantified the production of fungal mycelia using ingrowth sandbags in the organic layer of soil in temperate coniferous forest and analysed the composition of fungal communities in four consecutive seasons. We show that fungal biomass production is as low as 0.029 µg g Fungi play important ecological roles in forests: besides the free-living saprotrophs, diverse fungal groups interact with plants as mycorrhizal symbionts or important pathogens. Especially in the temperate and boreal regions, the research on fungi in forest ecosystems substantially increased our understanding of their ecology  and biogFungal mycelia form a substantial portion of belowground microbial biomass ,4, and fPicea abies [−2 [−2 y−2 and being considerably higher in coniferous than deciduous stands [In temperate and boreal forests dominated by trees forming ectomycorrhizal (ECM) associations, most of the fungal biomass is formed by ECM fungi ,11. Up tea abies  and otheea abies . The stabies [−2 ,15, the s stands ,16.While the C cycling models and predictions have been improved recently by including the data on fungal biomass production ,10,15,17The differences in ECM fungal biomass production are visible through the seasonality of total fungal biomass. Its highest stocks were reported in the early autumn for northern ECM coniferous forests ,27, whilPicea abies forest did not show significant differences between the summer and winter [In addition to seasonal changes in fungal biomass production, the changes of fungal community composition across seasons was also occasionally observed in ECM deciduous forests ,32, withd winter .Our previous analysis of the microbiome seasonality in the ECM coniferous forest soil indicated that the share of fungi on the total microbial transcription is approximately twice as high in late-summer than in late-winter . Using tHowever, transcriptome analyses only report the activity at the exact time of sampling, and as such, they do not provide reliable information about fungal productivity and activity across whole seasons. Moreover, the low taxonomic resolution of a transcriptome analysis does not allow to address the seasonality of fungal guilds or individual taxa. In this experiment, we addressed the question of seasonal production of extrametrical ECM fungal mycelia in a mature spruce forest using the incubation of ingrowth bags filled with sand across four consecutive three-month periods representing different seasons and analysed the composition of the fungal community within the bags to track the seasonality of mycelial production of different fungal species across the year. Since many fungi depend on root activity and respond to changing temperatures ,36, we hPicea abies) forest. The mean annual temperature was 5.9 °C, and the mean annual precipitation was 1100 mm. The snow cover lasts from November until April, while precipitation shows little seasonality. The understory was either missing or composed of grasses , bilberries (Vaccinium) and mosses. The same study area was explored previously to identify the total and active microbial communities and to describe the seasonality of the microbial processes [The study area was located at high altitudes (1170–1200 m) of the Bohemian Forest mountain range, Czech Republic  and was covered by an unmanaged Norway spruce . This mesh size allows fungi, but not roots, to grow through. Starting in June 2017, each three months, we placed 15 bags in the humic horizon (approx. until 10-cm depth) at random locations spanning 5 ha within the sampled area and retrieved them after three months when a new batch of 15 sandbags was placed at the same locations. We refer to the June–September incubation period as summer, September–December as autumn, December–March as winter and March–June as spring. Along with sandbags, soil was sampled at three defined locations within the experimental area to determine the overall community present. At each location, sixteen soil cores (4-cm diameter) were collected up to the same depth where the bags were placed. Litter and roots were removed, and soil was passed through a 5-mm sterile mesh and mixed to give a composite sample for each location. Samples were kept on ice during transport to the laboratory (within 1 day), frozen and kept at −20 °C until freeze-dried. Temperature was recorded using multiple TMS4 probes  and filled with 50-g acid-washed quartz sand  at a 5-−1. Ergosterol was identified by UV detection at 282 nm. To estimate the fungal biomass, the conversion ratio of 3.8 ± 2.0-mg ergosterol per g fungal biomass was used [Fungal biomass in bags was estimated based on the quantification of the ergosterol content . Total ewas used .DNA was extracted from each sandbag sample using the modified Miller method  with the−1), 1 μL of each primer (0.01 mM), 0.5 μL of PCR Nucleotide Mix (10 mM each), 0.25 μL Q5 HiFi DNA polymerase (2 U μL−1) and 1 μL of template DNA. Cycling conditions were 94 °C for 5 min, 30 cycles of 94 °C for 30 s, 56 °C for 30 s, 72 °C for 30 s and a final extension at 72 °C for 7 min. The PCR products of each sample were pooled and purified using MinElute Purification Kit  and then quantified on Qubit. Equimolar mixtures of amplicons were used for library preparation with the TruSeq DNA PCR-Free LT Kit (Illumina) and sequenced in-house on the Illumina MiSeq with 2 × 250 reads (MiSeq v2 Reagent Kit).For the fungal community analysis, PCR amplification of the fungal ITS2 region was performed using barcoded gITS7 and ITS4 primers  in threeThe amplicon sequencing data were processed using SEED 2.1.05 . Brieflyp-value < 0.05 was set as the limit for statistical significance.Nonmetric multidimensional scaling (NMDS) on relative abundances of fungal taxa was used with Bray-Curtis dissimilarity metrics to visualise the differences among fungal community composition in treatments. ANOVA was used to compare the ergosterol content in the ingrowth sandbags among the seasons. The effect of season on the relative abundances of fungal taxa and eco-physiological groups was analysed using Permutational Analysis of Variance (PERMANOVA). Mann-Whitney test was used to analyse the differences in relative abundances of individual taxa among seasons. All statistical analyses were performed using the R environment for statistical computing , and p-v−1 sand and 0.122 ± 0.019 µg g−1 sand) than in the autumn and winter . Furthermore, the fungal communities in the sandbags were also significantly different from those in the soil (Ascomycota (63–79%), while the soil communities were dominated by Basidiomycota  compared to soil , Piloderma (8–15%), Russula (7–14%) and Elaphomomyces (6–14%) species, the sandbag communities were dominated by Penicillium (1.5–21%), Xerocomus (0.6–16%) and Oidiodendron (1.5–14%) species, with many taxa dominant in the soil virtually missing in the sandbags , while ericoid mycorrhiza accounted for approximately 3% in all seasons, and 14–22% of the community was composed of saprotrophs and moulds D. The fuGiven that ectomycorrhizal fungi account for a large proportion of the total soil microbial biomass in some systems, e.g., boreal and temperate forests , the deaUnfortunately, the biomass production was not yet studied systematically across the whole year, and our knowledge of ECM fungal biomass production is largely restricted to the period of vegetation activity. Here, we report the seasonal production of mycelia in sandbags to peak during the spring and summer . The sumCortinarius), because they are adapted to an environment where they utilise organic nutrients from soil organic matter [Xerocomus spp. [The use of ingrowth bags filled with sand was once proposed as a method to estimate the growth of ectomycorrhizal fungi , and it c matter . Therefomus spp. ,65). TheOn the other hand, the important advantage with the sandbag method is that the fungi present are recently formed, while the fungi that we can detect in the soil can be old and inactive. Despite the much lower fungal activity, the ergosterol content in the coniferous forest that we explored was almost constant between the summer and winter , althoug−1 sand and only 0.0007 and 0.0015 µg g−1 sand in the autumn and winter, respectively, i.e., with an approximate mycelial production of 2–5% of peak productivity in the summer. It is unclear why the share of ECM is lowest in the autumn when temperatures are still favourable for tree photosynthetic production and Picea abies root tip production is similar as in the spring [Whatever imperfect may be the representation of the total fungal community in the sandbags, their use allows to assess the seasonality of mycelial production across those taxa that colonise them. In this respect, our results show that the seasonal variation in mycelial growth is widespread among fungi, since more than 80% of dominant fungi, belonging to a wide range of ecological guilds, show preferential sandbag colonisation in certain seasons A. In a pe spring .Compared to ECM fungi, the relative abundance of ericoid mycorrhizal fungi in the sandbags was higher in the autumn and winter, although their host plants were, most of the time, inactive under the snow cover. Previously, the ericoid mycorrhizal fungal gene repertoire revealed a capacity for a dual saprotrophic and biotrophic lifestyle . Indeed,Mortierella spp., frequently colonise decomposing fungal mycelia [Contrary to our expectations, the ratio of moulds and saprotrophs was higher in the autumn and winter than during the months of tree production. High shares of moulds in the winter were also reported previously for soils . Since m mycelia ,53, thei mycelia  that areOur results also indicate that many fungi produce most mycelia at certain period of time during the year. This is an interesting and unique observation that would deserve further exploration.Boletus edulis, showing the highest biomass in February, Lactarius deliciosus in December [Lactarius vinosus in February and May [A few studies previously reported on the seasonality of the biomass production of individual ectomycorrhizal species, typically those picked for revenue, e.g., December  or Lacta and May , in all Our results indicate that fungal biomass production peaks in the summer and spring but also suggests that fungi, including ectomycorrhizal root symbionts, keep proliferating also during the winter under snow cover. It remains unclear why the autumn season with favourable temperatures and tree activity is associated with decreased growth. Since much less seasonality is seen in the composition of the total soil community, it appears that the replacement of old mycelia by various fungi takes place at different seasons. Our results also clearly demonstrate that fungal taxa differ in their seasonal patterns of mycelial production. In the future, it would be advisable to develop tools to study the biomass turnover of all ectomycorrhizal species, including those that avoid sandbags, and to advance our knowledge of the seasonality of fungi in soils.


Shallow/sandy sites had benthic diatoms, while at deep/muddy sites, settled pelagic microalgae were found. The OM in surface sediments was always higher at muddy than at sandy sites, and biochemical analyses revealed that at muddy sites the OM nutritional value changed seasonally. In spring, sandy sediments were net autotrophic and retained N, while muddy sediments were net heterotrophic and displayed higher rates of denitrification, mostly sustained by Dw. In summer, benthic oxygen demand increased dramatically, whereas denitrification, mostly sustained by Dn, decreased in muddy and remained unchanged in sandy sediments. The ratio between denitrification and oxygen demand was significantly lower in sandy compared with muddy sediments and in summer compared with spring. Muddy sediments displayed seasonally distinct biochemical composition with a larger fraction of lipids coinciding with cyanobacteria blooms and a seasonal switch from inorganic N sink to source. Sandy sediments had similar composition in both seasons and retained inorganic N also in summer. Nitrogen uptake by microphytobenthos at sandy sites always exceeded the amount loss via denitrification, and benthic diatoms appeared to inhibit denitrification, even in the dark and under conditions of elevated N availability. In spring, denitrification attenuated N delivery from the estuary to the coastal area by nearly 35%. In summer, denitrification was comparable (~100%) with the much lower N export from the watershed, but N loss was probably offset by large rates of N-fixation.The interaction between microbial communities and benthic algae as nitrogen (N) regulators in poorly illuminated sediments is scarcely investigated in the literature. The role of sediments as sources or sinks of N was analyzed in spring and summer in sandy and muddy sediments in a turbid freshwater estuary, the Curonian Lagoon, Lithuania. Seasonality in this ecosystem is strongly marked by phytoplankton community succession with diatoms dominating in spring and cyanobacteria dominating in summer. Fluxes of dissolved gas and inorganic N and rates of denitrification of water column nitrate (D The pasroducers . A majorers 3−;  and may ers 3−; .During low-discharge periods, decreased N export from watersheds enhances the competition between primary producers and bacterial communities in estuaries, resulting in limited N losses . HoweverIn eutrophic estuaries, turbidity is due to resuspension or repeated phytoplankton blooms, often sustained by different algal communities. During the high discharge spring period, large N and silica (Si) transport may favor diatom blooms, whereas cyanobacteria may dominate the algal community during the low discharge summer period. Buoyancy and N-fixation capacity provide indeed a competitive advantage to cyanobacteria under N-limited and turbid conditions . Settled2) depletion (3− ammonification over denitrification (Post-bloom settling of phytoplankton enriches sediments with organic matter (OM). A moderate organic enrichment may stimulate denitrification, whereas a large enrichment may lead to oxygen . This lagoon displays pronounced seasonal variations of nutrient loads and stoichiometry (from N and Si excess in spring to N and Si limitation in summer) and phytoplankton community composition (from being diatom-dominated in spring to being cyanobacteria-dominated in summer) and two main sedimentary types , shallow (mean depth 3.8 m), highly eutrophicated and mainly freshwater estuary connected to the Baltic Sea by a narrow strait  and for sediment characterization . Once collected, intact cores for flux measurements were leveled in order to have 10 cm of sediment and 15 cm of overlying water. All cores were submersed with the top open in boxes containing site water cooled with ice packs and brought to the laboratory within a few hours from sampling for further processing and incubation. In addition, ~50 L of water was collected from each site for core maintenance, preincubation, and incubation activities. During sampling, bottom water was characterized for temperature, salinity, dissolved O2, and irradiance ; in the laboratory, bottom water was analyzed for chlorophyll a (Benthic processes were studied at four sites during two field campaigns carried out between 23 and 29 March and between 20 and 26 July 2009 . Two sitophyll a  and dissThe upper sediment layer (0–3 cm) was characterized for (i) bulk density, determined as the ratio between wet weight and volume (5 ml) of sediment; (ii) water content, determined after desiccation of a known fresh sediment volume at 60°C until constant weight; (iii) porosity, calculated as the ratio between the volume of water and that of fresh sediment; and (iv) OM, measured as percentage of weight loss on ignition  from dried sediment.For the general composition of the benthic microalgal community, the 3-mm uppermost sediment layer was sliced and immediately frozen. The samples were thawed one by one and viewed by epifluorescence microscopy  to get an overall view of the composition and dominating algal groups; the cells were identified to the nearest possible taxon. No actual cell counts were made.a and phaeopigments) were extracted from about 1 g of sediment (n = 3) taken from the upper 1 cm with 5 ml of 90% acetone and determined fluorometrically according to a and phaeopigment concentrations (−1 (Pigments (chlorophyll trations  and convions (−1 .n = 3) on the top 1 cm of the sediment. Protein, carbohydrate, and lipid concentrations were converted to carbon (C) equivalents by using the following conversion factors: 0.49, 0.40, and 0.75 mg C mg−1, respectively , and inorganic N forms . Irradiance at the sediment surface reflected that measured in situ and was obtained by halogen lamps and screens. In spring, reproduced irradiance was 150 and 90 μE m−2 s−1 and in summer 120 and 60 μE m−2 s−1 at shallower sandy and deeper muddy sites, respectively. In both periods, incubation time was set to keep O2 concentration at the end of the experiment within ±30% of the initial value. To this purpose, O2 was frequently monitored via microelectrodes  inserted through the lids. Cores were incubated for 6 h in spring (water temperature 2.5°C) and for 2 h in summer (water temperature 19°C). Water samples (60 ml) were collected at the beginning and at the end of the incubations using plastic syringes from each core water phase (~750 ml).In the laboratory, intact cores were preincubated and incubated according to 2 and TCO2 determinations were transferred to 12-ml exetainers (Labco Ltd). Winkler reagents were added immediately to the O2 samples, which were titrated within 2 days  ethylenediamine (Samples for On 2 days . SamplesN of HCl . Samplesediamine .−2 h−1 or mmol m−2 h−1). Negative values indicate fluxes from the water column to the sediment, whereas positive values indicate fluxes from the sediment to the water column. Daily fluxes were obtained by multiplying hourly fluxes measured in the light and in the dark by the number of light and dark hours of the corresponding sampling period, assuming constant rates.Fluxes of dissolved gases and nutrients were calculated from the change in concentrations in the cores with time and expressed on areal basis  by benthic algae, including settled phytoplankton and microphytobenthos, was calculated from net Oof 8 ± 1 . TNU mayidations .via isotope pairing technique  que IPT; . The sectot) into denitrification of NO3− diffusing to the anoxic sediment from the water column (Dw) and denitrification of NO3− produced within the sediment due to nitrification (Dn). Methodological concerns have been raised about the IPT due to the co-existence of anaerobic ammonium oxidation (anammox), which cannot be discriminated from denitrification as a source of N2 and makes invalid the assumptions on which IPT calculations are based  were added to the water column of each of the five replicate cores to perform a concentration series experiment  were collected from each core to calculate the 14NO3− to 15NO3− ratio in the water column. Top lids were positioned after 30 min from the 15NO3− addition in spring and after 5 min in summer due to different O2 penetration in sediments; incubation time was identical to that of flux measurements . At the end of the incubation, 5 ml of ZnCl2 (7 M) was added to the water phase of each core, and then sediment and water were gently slurred. An aliquot of the slurry was transferred to a 12-ml exetainer; 14N15N and 15N15N abundance in N2 was analyzed by gas chromatography-isotopic ratio mass spectrometry (GC-IRMS) at the National Environmental Research Agency, Silkeborg, Denmark. As the genuine 28N2 production was independent from the concentration of the added 15NO3−, denitrification rates were calculated according to the equations and assumptions of 2, was calculated as the ratio between N-N2 fluxes and the sum of N-N2 fluxes plus N-DIN effluxes from sediments.The IPT allows partitioning total denitrification , sediment type , and incubation condition  as factors. The factor S contrasted two groups, as data from the deeper muddy stations (Arkliu Ragas and Nida) and from the shallower sandy stations (Kairiai and Vente) were pooled. Differences between the denitrification to sediment O2 demand ratios were analyzed by two-way ANOVA with time  and sediment type  as factors.Differences between fluxes of dissolved gas and nutrients, and rates of denitrification were analyzed by three-way analysis of variance (ANOVA), with time  and sediment type  as fixed crossed factors, and site  nested in S, with n = 3 as the combination of factors. Prior to the analyses, homogeneity of variance was tested using the Cochran test, and wherever needed, the data transformed to meet the ANOVA assumptions. When significant differences among levels of the fixed factors were observed, Student-Newman-Keuls (SNK) post-hoc comparison tests were also carried out. To test variations in the biochemical composition of sedimentary OM, a distance-based permutational multivariate ANOVA , while for all of the conditional tests, the routine uses 999 permutations of residuals under a reduced model. Predictor arrays of variables included the following: (i) protein, carbohydrate, lipid, and phytopigment sedimentary contents (composition); and (ii) protein to carbohydrate ratio values, and protein and algal fractions of biopolymeric C . Statistical significance was set at p < 0.05.To assess whether and how much the composition and  quality of sedimentary OM explained changes in the benthic fluxes and in the rates of denitrification, non-parametric multivariate multiple regression analyses that were based on Euclidean distances were carried out using the routine DISTLM forward . The fora concentration in the lagoon water column was 23 ± 8 μg L−1 and the phytoplankton assemblages were dominated by diatoms (70–80%), whereas in summer, chlorophyll a concentration averaged 56 ± 11 μg L−1 with a dominance of cyanobacteria  than in summer (3–5 μM), whereas NH4+ concentrations remained similar in the two seasons  exceeding those in sandy sediments by a factor of 5–30 (p > 0.05) but varied among sites. Lipids displayed the highest concentrations at Arkliu Ragas (mud) where values had increased significantly from spring (11.9 ± 1.2 mg g−1) to summer (16.4 ± 1.9 mg g−1). Almost all sedimentary variables, except for the protein fraction of biopolymeric C  had an OM content (LOI) of ~20%, whereas sandy sediments (Kairiai and Vente sites) had an OM content of ~1%. Similar differences were revealed by pigments and biochemical sediment analyses, with concentrations of chlorophyll  of 5–30 . The thrymeric C , showed Thalassiosira, Cyclotella, Coscinodiscus, and Fragilaria or by green algae of the genera Scenedesmus and Pediastrum, whereas no benthic microalgal species were present. In contrast, at the two shallower sandy sites, a well-developed microphytobenthic flora was present in spring, when two Navicula species dominated at Kairiai, while at Vente, the community was more diverse. Some planktonic diatoms were also present at both sandy sites. In summer at Kairiai, epipelic diatoms together with the benthic cyanobacterium Merismopedia sp. co-dominated the sediment algal assemblages. At Vente, epipsammic diatoms were more abundant than at Kairiai.The deeper muddy sites were characterized by the exclusive presence of settled, though vital, planktonic diatom species of the genera 2 flux was negative at muddy sites , whereas sandy sites acted as O2 sources  between the factors sediment type and incubation condition and between incubation condition and time; i.e., differences between sediment types and time depended on the light or dark regimes.In spring, the daily O2 were only partially coupled to those of O2  averaged 0.18 , suggesting that only a minor fraction of the O2 produced during photosynthesis was released to the water column or that other processes apart from photosynthetic C-fixation were responsible for a fraction of TCO2 uptake. In summer, the benthic respiratory quotient  was higher than 1 and suggested an accumulation of anaerobic metabolism end-products. Daily fluxes of TCO2 were negative at all sampling sites and exhibited a similar pattern among stations in the two seasons; both the highest (Arkliu Ragas) and lowest (Nida) daily fluxes were found in muddy sediments (p < 0.01).The fluxes of TCOse of O2 . In boththe dark . In spriediments . The thr3− were larger in spring than in summer and mostly directed towards the sediment, whereas fluxes of NH4+ were higher in summer and mostly directed out of the sediment, except for the sandy Kairiai site . The effect of sediment type depended on the sampling period for both NH4+ and NO3− fluxes . In spring, muddy sediments displayed high uptake of NO3− sustained by its large availability in the bottom water, whereas lower uptake or slight production was found at the two sandy sites (Kairiai and Vente). In summer, considerably decreased NO3− concentration resulted in much lower rates of NO3− consumption at all sites . Overall, NO3− fluxes drove most of DIN fluxes in both sampling periods and at all study sites.Some general patterns appeared for nutrient fluxes. On a daily basis, sandy sediments acted mostly as net sinks for DIN, while muddy sediments switched from DIN sinks (spring) to DIN sources summer; . Fluxes iai site . Fluxes ll sites . There w28N2 production was independent from 15NO3− amendments, suggesting negligible contribution of anammox to N2 production. Total denitrification (Dtot = Dw + Dn) varied between 0.6 and 135.5 μmol N m−2 h−1 in spring and between 2.4 and 67.5 μmol N m−2 h−1 in summer . In spring, denitrification was sustained mainly by Dw, representing 85–90% and 60–76% of Dtot in mud and sand, respectively. In summer, Dn dominated . In both seasons, denitrification rates did not vary significantly between light and dark conditions .In all experiments, genuine n summer . Muddy s3− demand. Rates of N removal via denitrification were comparable (Arkliu Ragas) or higher (Nida) than TNU rates. In the same period, at shallow sandy sites, TNU rates were similar to (Vente) or exceeded (Kairiai) measured DIN fluxes. At sandy sites, the vast majority of inorganic N fluxes were channeled to the biomass of benthic algae via uptake, whereas the fraction that was denitrified was comparatively insignificant.Theoretical inorganic N uptake (TNU), total denitrification rates, and net dissolved inorganic N fluxes measured in light incubations during the two sampling periods are reported in 2 production resulted in low TNU. The absence of a DIN sink at the sediment-water interface and the increase of mineralization rates reversed the flux of inorganic N, which became positive. At muddy sites, denitrification drove a major fraction of benthic N fluxes; however, it decreased compared with that in spring, likely due to decreased NO3− concentration in the water column and limited nitrification. At sandy sites, in summer, TNU by microphytobenthos remained the most important inorganic N flux, and denitrification remained a scarcely relevant process. The net DIN flux to the sediments represented a fraction of theoretical N requirements by benthic algae, in particular at Vente  and muddy stations (30–40 mg biopolymeric C g−1) in the Curonian Lagoon, with the latter stations hypertrophic and under the risk of hypoxic or anoxic events  and in summer (only Vente). They were mostly sinks for inorganic N and displayed lower rates of denitrification than muddy sediments. This is in agreement with previous studies by 2 production was also measured at muddy sites in spring, but the rates were low. This fact was probably due to higher depth and reduced light availability, elevated OM content, and elevated microbial respiration, determining the net heterotrophy of these enriched sediments in both sampling periods. The analysis of the microalgal assemblages revealed that muddy sites hosted only settled pelagic algae, probably because the reduced light availability strongly limited the development of microphytobenthos. As the average depth of the Curonian Lagoon is 3.8 m, shallow areas represent a minor fraction of the whole lagoon surface (<5%), and the water column chlorophyll a concentrations were exceptionally low in summer 2009  or higher (Nida) than N requirements by benthic primary producers. In the same season, at shallow sandy sites, high rates of primary production resulted in TNU rates similar (Vente) to or exceeding (Kairiai) measured DIN uptake. These results suggest that N requirements by benthic microalgae at sandy sites were sustained by N availability in both the water column and sediment pore waters. Despite high NO3− concentrations in water, denitrification rates measured in sandy sites were insignificant compared with measured DIN uptake and TNU, likely due to much lower OM pool in sediments and inhibition of denitrification activity by microphytobenthos. Sandy sites had >10-folds lower concentration of OM than muddy sites, with a major proportion of the total biopolymeric C represented by the algal fraction (32–36% in sandy vs. 8–12% in muddy sediments).The spring sampling was characterized by elevated NOctory OM . High NO3− availability in the water column, limited O2 penetration affecting nitrification, and different biochemical qualities of the sedimentary OM . In summer at sandy sites, total denitrification rates remained low but did not change significantly as compared with those in spring; what changed was the relative importance of Dw (higher in spring) and Dn (higher in summer) to the total process. Similar total denitrification in the two seasons was likely due to environmental changes resulting in contrasting effects on dissimilative N reduction as increased water temperature, increased ammonification, decreased water column NO3−, and decreased O2 penetration  or lower (muddy sediments), despite significant differences of water temperature in the two seasons (~2.5 and ~19°C) and a 2–5 fold increase of sediment O2 demand. In moderately enriched sediments with low NO3− concentration in the overlying water, denitrification is demonstrated to increase with OM, but it is better correlated with sediment O2 demand and therefore with the mineralization capacity of sediments and with nitrification rates . In particular, ratios were always higher at muddy  than at sandy sediments  and in spring than in summer. This means that denitrification represented the major fraction of O2 uptake during winter at muddy sediments, whereas it represented the lowest fraction of O2 uptake during summer and at sandy sediments. These results support the complex regulation of denitrification in the Curonian Lagoon sediments, where NO3− concentrations, sediment O2 demand, the OM content and quantity and the activity of benthic algae interact as factors. 2 production (μmol N2-N m−2 h−1) and sediment O2 demand (μmol O2 m−2 h−1) in 12 benthic habitats within three different estuaries. Such variable slopes were correlated with OM C:N ratio and its δ13C signature, suggesting for the first time the importance of the origin and of the nutritional quality of the OM pool as regulators of denitrification.In the present study, dark denitrification to sediment O3− from sediment O2 demand and NO3− to O2 availability in bottom water, allows to compare measured and predicted Dw in the two sediment types. At muddy sites Arkliu Ragas and Nida, there was a good agreement between measured and predicted rates in both sampling periods , whereas at sandy sites Kairiai and Vente, the regression between theoretical and measured rates was not significant  and loads  as Dw is limited by low NO3− in the bottom water, and that denitrification is correlated with the organic carbon content of sediments , which overlap those measured in the last 30 years  had also decreased, but only by 35% and was comparable with the N input from the Nemunas River. To our knowledge, only two annual N budgets (2012–2013) have been made for the Curonian Lagoon. They were made by comparing the loads from the Nemunas River with the loads from the lagoon to the Baltic Sea  and of total N in the 2 years . 3− loads from the Nemunas River occurred in spring, which is in agreement with the high rates of denitrification of water column NO3− that are reported in this study. During summer, riverine NO3− concentrations were much lower, and denitrification was mostly sustained by nitrification.In the Curonian Lagoon, benthic N-cycling underwent a strong seasonality. Denitrification (at muddy sediments) and benthic N uptake (at sandy sediments) were dominating processes in the spring, with high discharge and dominance by diatoms. During summer, with low discharge and dominance by cyanobacteria, microphytobenthos uptake continued to drive inorganic N fluxes at sandy sites, whereas at muddy sites, denitrification decreased and inorganic N was recycled to the water column. In spring, the average daily load of total N discharged in the Curonian Lagoon from the Nemunas River was estimated to be 97.3 ± 35.8 tons N day30 years . As shalltic Sea . Such bu−1, assuming a standard pro capita N production of 12 g N IE−1 day−1. These N loads represent nearly 2 and 10% of riverine N inputs in spring and summer, respectively; but they are overestimated as the city of Klaipeda has a wastewater treatment plant operating denitrification. A similar amount of N is likely produced during summer by the fluctuating population of tourists visiting the Curonian Spit . If N loads from civil sources represent minor N inputs, the rates of summer fixation of N2 recently estimated by −1 represent an important N input term to the Curonian Lagoon. Such net import of N via fixation nearly doubles summer riverine loads and offset rates of N abatement via denitrification.The present work and that of 2 sources, due to the uptake by benthic algae (in particular at sandy sites) and denitrification of water column NO3− (in particular at muddy sites). Shallow sandy sites had mats of active benthic algae that depressed denitrification rates due to strong control of nitrification or production of inhibitory compounds. This was not evident at deeper sites, which had only settled pelagic algae and were significant N2 sources. In summer, sandy sites continued to be temporary N sinks via microphytobenthos uptake, whereas at muddy sites, the drastic reduction of inorganic N availability in the water column resulted in lower rates of denitrification.Results from this study suggest pronounced seasonal differences between sandy autotrophic and muddy heterotrophic sites in the (i) nutritional quality and total amount of the OM in surface sediments; (ii) inorganic N uptake by benthic primary producers; and (iii) denitrification rates. In spring, sediments acted as inorganic N net sinks and NThe analyses of the macromolecular composition of the OM revealed striking differences between sandy and muddy sites in both sampling periods, which are in agreement with differences in metabolic measurements. At sandy sites, the OM content was lower but had better quality than muddy sediments. Here, the bulk of OM mostly consisted of benthic microalgae, and the organic pool was similar in terms of macromolecular composition in both sampling periods. On the contrary, muddy sediments had much higher concentrations of OM, but with lower nutritional value.The Nemunas River represents the largest freshwater and nutrient inputs to the lagoon and acts as an upstream regulator of the Curonian Lagoon benthic metabolism. Seasonally variable riverine N loads affect the competition between benthic microalgae and microbes and the rates of denitrification. Pronounced summer N-limitation and turbidity favor the shift from the dominance of diatoms to the dominance of cyanobacteria and affect the nutritional value of phytoplankton and the macromolecular composition of the sedimentary OM. The marked increase of lipids in muddy sediments probably reflects this seasonal shift, whose effects on benthic N cycling and specifically on denitrification need further investigations.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.MBa, DN, AP, AR-B, and PV planned the activities. MBa, DN, AP, SB, MBr, and MZ performed the measurements. MBa, DN, AP, and SB performed the analysis and processed the experimental data. MBa, MZ, AP, SB, AR-B, and KS drafted the manuscript. All authors discussed the results and commented on the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Pelvic organ prolapse can significantly affect a woman’s quality of life by compromising physical, social, psychological and sexual function. Pelvic organ disorders and its consequences have higher economic burden to the patient as well to the country. Therefore, this systematic review and met- analysis aimed to estimate the burden of POP in Ethiopia.2 statistic. Subgroup analysis was computed for the evidence of heterogeneity.International databases , having < 18.5 BMI , I2 = 59.9%, P = 0.64), and age > 40, I2 = 75.9%, P = 0.016) were the associated risk factors for pelvic organ prolapse.This systematic review and meta-analysis revealed that the overall national prevalence of pelvic organ prolapse in Ethiopia was 23.52% . Being rural resident , IThe pooled prevalence of pelvic organ prolapse was high. Residence, body mass index and age of the women were the predictors of pelvic organ prolpase. Creating awareness and identifying the modifiable and non modifiable risk factors for pelvic organ prolpase is a crucial strategy to prevent further complications and risk of operation. Pelvic organ prolapse is a complex condition resulting from the weakness and defects of pelvic floor structures. Pelvic organ prolapse (POP) is the descent of one or more aspects of the vagina and uterus: the anterior vaginal wall, posterior vaginal wall, the uterus (cervix), or the apex of the vagina  .Worldwide, millions of women have been affected by pelvic floor disorders. One in every nine American women will undergo surgery for a pelvic floor disorder in her lifetime, with 30% of women having a chance of requiring additional surgery for the same condition , 3.Pelvic organ prolapse occurs when the pelvic floor no longer supports the proper positioning of the pelvic organs, i.e. the vagina, bladder, rectum or uterus. In unites states of America, around 6–7% of the women having pelvic floor disorders were experiencing pelvic and urinary symptoms. Feeling of vaginal bulging and/or pelvic pressure, urinary incontinence, and constipation has been identified as symptoms of pelvic organ prolapse –6. In diPOP and its complications make an impact on a considerable economic burden on the affected person. About 11% of the American women undergo surgery for POP or incontinence before the age of 79, with 29.2% of the women having a chance of requiring additional surgery .Pelvic organ prolapse is highly prevalent among women with the age of over 40 years old, geriatric women, and postmenopausal women with the estimated prevalence of 41–50% , 12.As different studies, in low and middle income countries showed the mean of pelvic organ prolaps is 19.7% with the estimated range from 3.4 to 56.4%. Moreover, most studies were small and not population based, as a result methods of ascertaining of POP and definitions have been varied [High parity, older age, obesity, pregnancy and vaginal delivery, menopause, constipation, persistent coughing, early age at first delivery, forceps delivery, prolonged second stage labor, and prolonged heavy lifting are the revealed contributing factors to cause strain to the pelvic floor. The global burden of Pelvic floor disorder is increasing due to increasing the age of the population .The symptoms pelvic floor disorders had affect many aspects of a woman’s life, such as social, psychological, occupational, domestic, physical, cognitive, behavioral and sexual domains. In general, pelvic floor disorders have a negative impact on women’s lives, emotional and quality of life. Certainly, POP may be associated with a variety of systemic symptoms such as urinary, bowel and sexual symptoms which may significantly confrontation the quality of life of the women have been facing different mental and psychological illness such as mood and personal disorders , 15.In Ethiopia, institutional delivery is limited, high fertility rates and higher rates of gynecologic disease have been reported and only 48% of women deliver in health institutions .In Ethiopia, there is no any take apart strategy to prevent and manage pelvic floor disorders both in private and governmental health institutions. Even if, different single studies have been tried to identify the types and levels of pelvic floor disorders, there has been limited source of evidence regarding types, and burdens of POP in Ethiopia. As a result, this study helps to estimate the national burden of Pelvic organ prolapse at national level to design appropriate preventions and management modalities.This systematic review and meta-analysis were conducted to estimate the national burden of POP and its associated factors in Ethiopia using the standard PRISMA checklist guideline.International databases  were searched and included in this study. Searching terms were used using PICO formulating questions. The following Searching terms were used: pelvic floor disorders, POP, utero-vaginal prolapse, vault prolapse, rectocele, cystocele AND Ethiopia and related terms.Observational studies  were included.Only studies conducted in Ethiopia without time limiting and reported the prevalence or at least one least adjusted associated factor of pelvic organ prolapse were included.Only English language articles both published and unpublished reported studies were included.Articles without full abstracts or texts and articles reported out of the outcome interest were excluded.After collecting the findings from all databases, the articles were exported to Microsoft Excel spreadsheet. Two authors (GG & AD) independently extracted the data and reviewed the screened and eligible articles. Any disagreement was handled by the two reviewers (GG & AD). Finally, a consensus was reached between two authors through discussion. The methodological quality of each study , comparability and outcome were checked using the NOS tool. Newcastle-Ottawa Quality Assessment Scale (NOS) for cross sectional and case control studies were used to assess the methodological quality of a study and to determine the extent to which a study has addressed the possibility of bias in its design, conduct and analysis. All of the included articles scored (NOS) 7 and more can be considered as “good” study with low risk Table S.POP-Q stage or the traditional classification of POP.In this study measurement of outcome was measured and included from studies report POP depending on either Stage-0 “no prolapse”Stage I is when the most distal portion (leading surface) of the prolapse is 1 cm above the level of the hymen Stage II is when the most distal portion (leading edge) of the prolapse is #1 cm proximal to or extends 1 cm through the plane of hymen Stage III is when the most distal portion of the prolapse is .1 cm below hymen but no further than 2 cm less than the TVL Stage IV is when there is complete eversion of the total length of the pelvic organ, meaning the pelvic organ protrudes at least the total vaginal length minus 2 cm beyond the hymen.1st: Descent within the vagina2nd: Descent to the introitus3rd: Descent outside the introitusAny pelvic disorder at least reported any of one of the pelvic floor disorders  with any stages were considered as the primary outcome of the study.Hernia of anterior vaginal wall often associated with descent of the bladder.Hernia of the posterior vaginal segment often associated with descent of the rectum.Descent of the apex of the vagina into the lower vagina, to the hymen, or beyond the vaginal introitus.Micro-soft Excel (2016), and STATA version 11 software were used for data entry and analysis respectively. Two authors (AD and GG) independently extracted all the important data using a standardized JBI data extraction format. Substantial agreement between reviewers i.e. Cohen’s kappa coefficient > 0.60 were accepted. Any disagreement between reviewers was resolved through discussion and then consensus was reached. During data extraction; name of the author, sample size, publication year, study design, prevalence, response rate, population outcome, study site, and different contributing factors were included. Moreover, prevalence of pelvic organ prolapse with 95%CI and associated factors were collected .Egger’s regression test and funnel plot were computed to check the publication bias across and within the studies. Cochrane Q-test and I-squared statistic were used to check the heterogeneity of studies . Pooled 238 articles were retrieved using a search strategy about pelvic organ prolapse and associated factors in Ethiopia using online international datasets such as; MEDLINE/PubMed, Hinari, Scopus, Google scholar, African journals and literatures. After duplicates were removed, 117 studies remained.68 articles were excluded after review of their titles and abstracts from the remaining 117 articles. Therefore, 49 full-text articles were accessed and assessed for inclusion criteria, resulting further exclusion of 40 articles primarily due to reasons .The overall burden of pelvic organ prolapse is presented with a forest plot Fig. . Therefo.Subgroup analysis was employed with the evidence of heterogeneity. In this study, the Cochrane IIn this study, having body mass index (BMI) < 18.5, being rural resident and having age of the women > 40 years were the determinants factors of pelvic organ prolapse.2 = 47.5%, P = 0.167) 3.29 times prevalent among women who resided in rural areas than those who were living in urban areas , I2 = 75.9%, P = 0.016) times more likely among women having more than 40 years old than the younger population , I2 = 59.9%, P = 0.64), 2.59 times more likely among women who have less than 18.5 body mass index than the counterparts , I2 = 98.4%, P < 0.001). The finding of this study is consistent with the study done in China [In this meta-analysis, the national magnitude of pelvic organ prolpase in Ethiopia was 23.52%  were 3.56 times more likely to have POP than the women living in urban areas. This might be justified by the burden of POP in African’s people living in United States of America and those residing in Africa comparatively higher number of home deliveries, difficult access to skilled delivery attendance, low attendance of institutional deliveries, lack of awareness on important risk factors, low coverage of family planning, lack of antenatal care follow up, lack of adequate postnatal care follow up with preventive measures, and heavier physical work load among people residing in living Africa predominantly in sub-Saharan Africa .Age > 40 years  is the determinant factor to increase the risk of pelvic organ prolapse. This study finding is consistent with the study done in –37. This2  is increasing the burden of pelvic organ prolapse. While weight gain is a risk factor for developing prolapse, weight loss does not come into sight to be significantly associated with the waning of POP, suggesting that damage to the pelvic floor related to weight gain might be irreversible [Despite obesity (BMI 25 kg/m2) could increase the risk of POP, this systematic review and meta-analysis revealed a contrary finding that being underweight  increases the risk of POP threefold , 41. On versible .Even though the original studies reported, high parity is one of the predictors of POP, estimating odds ratio is difficult since they simply reported the presence of association with chi square. However high parity (≥4) increases the risk of POP , 40. ThiThe pooled prevalence of pelvic organ prolapse was higher. Residence, age and BMI were the predictors of pelvic organ prolpase. Identifying the modified and non modified risk factors for pelvic organ prolpase is a crucial strategic way to prevent further complications and risk of operation.Additional file 1: Table S1. NOS Quality assessment tool for cross sectional and case control studies.


Attenuated decreases in lung function can signal the onset of acute respiratory events known as pulmonary exacerbations (PEs) in children and adolescents with cystic fibrosis (CF). Univariate joint modeling facilitates dynamic risk prediction of PE onset and accounts for measurement error of the lung function marker. However, CF is a multi-system disease and the extent to which simultaneously modeling growth and nutrition markers improves PE predictive accuracy is unknown. Furthermore, it is unclear which routinely collected clinical indicators of growth and nutrition in early life predict PE onset in CF.Using a longitudinal cohort of 17,100 patients aged 6–20 years , we fit a univariate joint model of lung-function decline and PE onset and contrasted its predictive performance with a class of multivariate joint models that included combinations of growth markers as additional submodels. Outcomes were longitudinal lung function (forced expiratory volume in 1 s of % predicted), percentiles of body mass index, weight-for-age and height-for-age and PE onset. Relevant demographic/clinical covariates were included in submodels. We implemented a univariate joint model of lung function and time-to-PE and four multivariate joint models including growth outcomes.P < 0.0001), and all had reasonable predictive accuracy . None of the growth markers alongside lung function as outcomes in multivariate joint modeling appeared to have an association with hazard of PE. Jointly modeling only lung function and PE onset yielded the most accurate (area under the receiver-operator characteristic curve = 0.75) and precise (narrowest interquartile range) predictions. Dynamic predictions were accurate across forecast horizons  and precision improved with age.All five joint models showed that declining lung function corresponded to slightly increased risk of PE onset (hazard ratio from univariate joint model: 0.97, Including growth markers via multivariate joint models did not yield gains in prediction performance, compared to a univariate joint model with lung function. Individualized dynamic predictions from joint modeling could enhance physician monitoring of CF disease progression by providing PE risk assessment over a patient’s clinical course. We assume a proportional hazard model for the risk of the event:γ is the corresponding regression coefficients vector, and a1 and a2 are the coefficients that connect the longitudinal and event processes. In our case, these parameters represent the strength of the association between FEV1 and BMIp with onset of PE. To better understand the connection between the event and longitudinal parts in our model, we explain the meaning of the a1 and a2 parameters. Specifically, for a one unit increase in the underlying value of FEV1 for patient i, the hazard ratio is exp(a1) assuming that the baseline covariates and BMIp remain the same. Similarly, exp(a2) is the hazard ratio when the underlying value of BMIp for the i -th patient is increased by one unit assuming that the baseline covariates and FEV1 remain the same.For the PE part, we assume 1; others included ii) BMIp; iii) HFA; iv) WFA; v) WFA and HFA. The multivariate joint models in (ii) – (iv) were implemented to evaluate the impact of different measures of nutritional status on predicting PE onset. Due to the large number of parameters in scenario (v), we assumed a less flexible evolution for FEV1 and BMIp over time. In particular, we postulate natural cubic splines with two degrees of freedom to estimate this evolution instead of natural cubic splines with three degrees of freedom assumed in the other scenarios.We employed Markov-Chain Monte-Carlo (MCMC) via Gibbs sampling using the ‘JMbayes’ package (Version 0.8–82) in R  to obtain the parameters from the respective posterior distributions under the multivariate joint model . The higWe calculated the area under the receiver-operator characteristic curve (AUC) to evaluate predictive accuracy of each model with respect to PE events using ten-fold cross validation. A large value of AUC indicates the preferred model. To obtain correct estimates of the AUC we performed a 5-fold cross validation procedure, wherein each time we selected 700 individuals from the large data set and we split it in five subsets. Each time we fitted the model in four of the subsets, we calculated the AUC in the subset that was excluded. The calculation of the AUC was performed at 12 and 16 years of age with prediction windows of 0.5, 1, 2 years, in order to mimic clinically meaningful age strata and prediction windows. This procedure was repeated 100 times. Appropriate diagnostics for joint models were examined. The code of the analysis and cross validation are shown in the There were 16,455 patients contributing 245,513 observations to the analysis cohort  – (iv) did not impact association between FEV1 and PE onset, and their associations with PE onset did not reach statistical significance.Each Gibbs sampler ran for 900 iterations, and the first 600 iterations were discarded for burn-in. Shared parameter estimates, which represent associations between each longitudinal process and the PE event, are shown for all five fitted joint models Table . The log1. There were nonlinear associations, as reflected by spline coefficients, between each of genotype, sex, SES, MRSA, Pa and CFRD and FEV1 decline. In the PE event submodel, patients who were male, used pancreatic enzymes, had lower SES, infection with MRSA and Pa and were diagnosed with CFRD had greater risk of PE onset. The multivariate joint models, each of which included a longitudinal submodel for FEV1, had similar association results for the clinical/demographic covariates and shared parameters regarding FEV1.The univariate joint model (i) in Table SThe multivariate joint model (ii) in Table S1, provided the highest AUC value and was most robust across age strata and prediction windows. Precision of the predictions was assessed by examining the interquartile ranges of the boxplots in Fig. The results of the predictive performance of the joint models presented in Table 1 and BMIp. Her first recorded FEV1 and BMIp were 98.5% predicted and at the 48.2 percentile, respectively. She began taking pancreatic enzymes and had a positive culture for Pa around 10 years old. Her monitored outcomes are depicted across four clinic visits from ages 8.2 to 14.3 years, along with probability of not having a PE over follow up. Her long-term risk of PE appears higher during an earlier visit , compared to later visits that are informed by dynamic predictions from the multivariate joint models . Commensurate with these results are the changes in her FEV1 and BMIp trajectories, which imply minimal rate of decline and improving nutritional status, respectively. She did not experience a PE event during follow up. Her projected PE-free probabilities over follow up using a multivariate joint model replacing BMIp with WFA and HFA were similar  are shown in Fig. 1) are endogenous variables. In this epidemiologic study, we assessed predictive performance of these markers using a series of joint models. Our novel application confirmed the reliance of changes in the FEV1 trajectory on predicting PE events but revealed the clinical utility that these novel models could have for monitoring multiple indicators of disease progression for an individual patient. In parallel, our application highlights that, although pancreatic enzyme use is commonly employed as a marker of pancreatic insufficiency, their use was associated with lower PE frequency over follow-up ; however, it appears that including BMIp as a submodel introduces additional noise into the joint modeling of these processes, thereby making predictions less accurate and more variable . Furthermore, in this research we assumed the underlying value of the biomarkers  to be associated with PE. A special feature of these biomarkers is that they are time-dependent, therefore the assumption of the underlying value might be too strict. Future research could focus on investigating whether other structures, such as the slope of these markers, could provide a stronger association with PE and a better predictive performance.The multivariate joint models afforded the opportunity to obtain dynamic predictions at the individual patient level Fig. ; howeverA limitation of this study is that the models cannot be used to draw conclusions about recurrent PE events, since the PE event submodel estimates time-to-first PE. Although this focus simplifies analyses, time-to-first PE during follow up tended to occur in early adulthood Fig. . It is p1, and multivariate joint modeling of FEV1 and other outcomes related to nutritional status and growth can be used for routine medical monitoring of an individual patient and dynamic assessment of PE risk over time.The univariate joint modeling of the CFFPR demonstrates the reliance of PE diagnosis on FEVAdditional file 1: Table S1. Joint Model with Longitudinal FEV1 and PE onset. Table S2. Joint Model with Longitudinal FEV1, BMIp and PE onset. Table S3. Joint Model with Longitudinal FEV1, HFA and PE onset. Table S4. Joint Model with Longitudinal FEV1, WFA and PE onset. Table S5. Joint Model with Longitudinal FEV1, WFA, HFA and PE onset.Additional file 2. Multivariate joint modeling to identify markers of growth and lung function decline that predict cystic fibrosis pulmonary exacerbation onset.