What exactly is the short-time rate of change (growth rate) in the trend of  Are global events such as the natural climate phenomena, the major economic recessions or the COVID-19 global crisis and economic shutdown visible in the continuous monitoring of carbon dioxide in the atmosphere? This is a timely question that probably can not be given a definite answer, but which nevertheless is worthwhile to study and to discuss. This query also leads directly to the follow up question regarding how the short-time rate of change in the trend of 5. To this end, continuous monitoring was started by David Keeling at NOAA’s Mauna Loa Observatory (MLO) in Hawaii, which gives access to well-mixed clean air at 3.5–4 km altitude. These measurements later became known as the “Keeling curve”, see e.g.6.The continuous monitoring of the atmospheric greenhouse gases as well as their historical, pre-industrial levels continues to provide an irreplaceable source of data, information and analyses that are becoming increasingly important for policymakers in their quest to mitigate the worst scenarios concerning the global warming, see e.g.7. In this paper, we will revisit some of the basic regression analysis techniques and perform a statistical analysis based on weekly data from the Keeling curve covering the period from 1974-05-19 to 2020-03-29, cf.8 as well as the master’s thesis9. The purpose of this study is to validate a simple short-time estimate of the rate of change (or growth rate) in the trend of the Trends and analyses of local as well as of global carbon dioxide cycles at various time-scales are continuously monitored and analysed by the National Oceanic and Atmospheric Administration (NOAA), see e.g. the curve fitting methods described in7. The difference to the NOAA approach, however, is that we are using here a short-time data window of only 2 years and no postfiltering of the residuals. This enables us to perform a statistical analysis of the residual errors and to establish the corresponding estimation accuracy. We will demonstrate that the resulting residual errors based on a 2-year data window are in good agreement with the statistical assumption that the weekly data from 1974 to 2020 are corrupted by additive, uncorrelated Gaussian noise. Indeed, most of the daily variability in this data is caused by weather systems that bring different air masses to MLO so that there is memory from day to day, but not from week to week. There can also be variability on a seasonal scale, caused for example by droughts, or an early spring, etc., and which will then be seen as local changes in the short-time trend. We will show that the regression analysis that is considered here is perfectly consistent  trend and its rate of change. As a reference, the simple approach can always be validated by a comparison with any of the more sophisticated linear regression techniques that are available. In this study, we consider a well-established linear regression analysis based on 3 polynomial coefficients and 8 Fourier series coefficients (4 yearly harmonics) followed by smoothing (low-pass filtering) of the residuals, as is employed in10. Hence, a regularization, or smoothing, is necessary. In a discrete-time linear regression analysis with a linear least squares (pseudo-inverse) solution, this ill-posedness will manifest itself as an increasingly ill-conditioned system matrix when the observation interval decreases. Obviously, the ill-conditioning also increases with an increasing number of regression parameters . To obtain error estimates in such inverse problems, it is common to employ the Singular Value Decomposition (SVD) as well as very effective L-curve techniques where the residual error is plotted against some regularizing parameter12. Due to the Gaussian assumption referred to above, we can take a more direct approach here and consider the Maximum Likelihood (ML) estimation and the associated Cramér–Rao Lower Bound (CRLB)13 of the pertinent parameter as the objective for the L-curve analysis. The subsequent analysis will show that a stable estimate of the rate of change can be obtained with the 2-year window yielding a relative estimation error of less than 5 9. Considering the long term data used in this study (1974–2020), it is finally worth noting that the error estimates that have been presented here are very much coherent with the 1.The question about the smallest useful window length in the short-time estimate of the rate of change is an interesting, subtle issue. It is noted that the task to estimate the trend of the Keeling curve by averaging of continuous-time data is a well-posed problem. However, the task to differentiate the data is an ill-posed problem in the sense that the derivative does not depend continuously on the given dataLet mentclass2pt{minim9. Hence, the averaging  which is defined for uniformly sampled discrete frequencies14, p. 456. The DFT is usually computed by using an algorithm referred to as the Fast Fourier Transform (FFT). Similarly, the differencing . Let Define a time window of 7, but other model orders can easily be incorporated and investigated in a similar way. The covariance matrix of the noise is given by Consider now the following statistical model13. The corresponding Cramér–Rao Lower Bound (CRLB) is given by13. Here, we are particularly interested in the Cramér–Rao lower bound of the two parameters The Fisher Information Matrix (FIM) and the Maximum-Likelikelihood (ML) estimate for this situation are given byal model  is lineaDefine the residual errorBased on , it is r results  depend o results  is emploThe estimates  can now entclass1pt{minima^0 using  for a \d7. The NOAA estimate shown here is based on a long-term trend and where a smoothing of the residual data has been employed with a Full Width at Half Maximum (FWHM) of 1.4 year to match the amplitude of the short-time estimates.In Fig. ^1 using  for the entclass1pt{minimaTo validate the Gaussian assumption above, we perform a statistical analysis of the residual error fined in . The 2-yfined in  is estimBased on , the varnce with .Figure 42. For 2, and which agrees perfectly with the previously obtained value.Finally, we evaluate the Gaussian assumption by stacking all the ollowing  we obtaiM. All the weekly data between 1974 and 2020 have been used to obtain the mean value, and as the variance of the noise we have employed the estimate 2.To obtain a unitless measure of the estimation errors we consider the following normalized Cramér–Rao lower bounds (relative errors)mentclasspt{minimagiven by , and whe9. Nevertheless, provided that the window length M (the regularizing parameter) is large enough, we can indeed have a stable estimate of the derivative The relative error in the estimate of the rate of change (the derivative) It may be of interest to compare or to correlate the estimated rate of change in the trend of the Keeling curve with natural phenomena as well as the major anthropogenic activities. Of course, any conclusions based on such a comparison must be treated with great care considering the vast complexity of the Earth system. Nevertheless, to demonstrate the application of the estimation of trends in y-axis, together with estimated values of global 15 which is presented here in units of y-axis. It is noted that the last update of CDIAC is from 201415. The values for 2015–2018 have been extrapolated from BP review by multiplying the increase factors from BP review to the carbon numbers in CDIAC. The values for 2019–2020 are assumed to be constant. The plot in Fig. 5. Many people are confused about emissions and 16. That is why the trend of In Fig. y-axis. The NOAA growth rates of Fig. 17. These SSTs are plotted here as y-axis of the figure. In the same figure, we have also plotted year-to-year differences (dCDIAC) of the CDIAC data that was shown in Fig. 19. If the emission change is for 1 year, then there has not been enough time for the anomaly to spread uniformly through the atmosphere. The Southern Hemisphere (SH) has only partially caught up with the NH where the emissions change originated, nor has the stratosphere. So, in 1 year the emissions are effectively diluted into 70–80 In Fig. entclass1pt{minima20. It may also be noted that the eruption of Pinatubo was estimated to produce some extra 50 The changes seen in dCDIAC seem to correlate somewhat with the major economic recessions in 1980–1983, 1990–1993, 2001–2002 and 2008–2009. However, the corresponding changes in dCDIAC are too small to be reliably connected to the rather strong fluctuations that are seen in the estimated growth rates 21. In Fig. It is observed that the statistical analysis presented in this paper is restricted to one station only, the MLO in Hawaii. The main reason for choosing this particular station is the uniqueness of the extensive record of weekly data that is available since 1974, and which have made it possible to assess the Gaussian statistics with very high precision. Nevertheless, the simple estimation strategy expressed in  is readiIt may finally be of interest to consider the potential impact that the COVID-19 crisis may have on the present and future We have proposed a simple strategy for estimating the short-time rate of change in the trend of the Keeling curve. This estimate is based on a centered 1-year sliding average to estimate the trend, and a corresponding centered 2-year sliding data window with differencing to determine its rate of change. To validate this estimator, we have compared it to a more sophisticated regression analysis based on a combined Taylor and Fourier series expansion and found a very good agreement based on 3 Taylor coefficients, 8 Fourier series coefficients (4 yearly harmonics) and a 2-year data window to determine the parameters. A statistical analysis based on weekly data for the years 1974–2020 has shown that the model errors can be considered to be uncorrelated and identically Gaussian distributed. The Gaussian assumption justifies the use of standard formulas for Maximum Likelihood (ML) estimation, Fisher information and the related Cramér-Rao Lower Bounds (CRLB). An L-curve technique based on the CRLB has been used to study the accuracy and stability of the regression analysis. With the regression model that has been studied here, it is found that the limit of stable inversion for the rate of change in the trend of the Keeling curve is about 50–60 weeks, and that the 2-year window of 104 weeks yields a relative error less than 5


The anti-angiogenic effect of Apatinib was explored by bioassays in human umbilical vein endothelial cells (HUVECs), including cell migration, invasion and apoptosis, tube formation, and wound healing. Further experiments showed that Apatinib inhibited tumor microangiogenesis to achieve the aims of inhibiting tumor growth and recurrence by means of down-regulating the phosphorylation of the RAF-mek-erk, PI3K-akt and P38MAPK pathways. The antitumor growth and anti-angiogenic effect of Apatinib was further validated by the animal experiment. Taken together, we concluded that Apatinib inhibits the angiogenesis and growth of liver cancer by down-regulating the PI3K-akt, RAF-mek-erk and P38MAPK pathways, and has a stronger inhibitory effect in hypoxic environments. Combining TAE with adopted iodized oil containing Apatinib has a stronger inhibitory effect in VX2 liver tumor growth and metastasis, which suggesting such combinations may provide a new target and strategy for interventional therapy of liver cancer.Transcatheter arterial embolization (TAE) plays an important role in clinical liver tumor therapy. However, hypoxia after TAE limit the medium-long term efficacy of TAE. Thus, in our study, we explored the treatment effect and mechanism of combining transcatheter arterial embolization with adopted iodized oil containing Apatinib on suppressing tumor growth and metastasis. We simulated the changing of tumor microenvironment before and after TAE both  Due to the concealment of the onset of liver cancer, most patients are already in the advanced stage at the time of diagnosis. Transcatheter arterial embolization (TAE) is playing a major role in the therapy for patients who are not candidates for surgery4. However, although TAE therapy prolongs the survival time of many patients5, the inability of conventional TAE therapy with iodine oil to effect thorough necrosis of the tumor cells should not be ignored7. Incomplete necrosis of the tumor could aggravate hypoxia in the tumor9. And hypoxia can further activate angiogenesis and tumor growth, which often associated with the tumor metastasis and recurrence, and is the critical factor limiting the treatment effect of TAE11. Hence, it is mightily vital to explore new strategies for HCC treatment.Hepatocellular carcinoma (HCC) is garnering more research and clinical attention as the third-leading cause among cancer patients13. Tumors often remain hypoxic due to decreased blood flow, leading to the sustained overproduction of vascular endothelial growth factor (VEGF) after TAE therapy15. VEGF is a critical factor that induces developmental angiogenesis via VEGF receptor (VEGFR)-dependent signaling, which in turn leads to tumor recurrence and metastasis17. VEGFR2 is mainly expressed on endothelial cells, mediating the angiogenic effects of VEGF19. However, this neovascularization produces abnormal leaky vessels that produce interstitial hypertension, edema and tumor hypoxia. This process forms a vicious circle of nonproductive angiogenesis, tumor growth and hypoxia after TAE20. Accordingly, suppression of the VEGF signaling pathway employing VEGFR2 tyrosine kinase inhibitors has become a hopeful therapeutic strategy to decrease excessive angiogenesis in HCC after TACE.Malignant angiogenesis is believed to be the most crucial aberrantly activated pathway; this belief is highlighted by the nature of HCC as a hypervascular tumor22. Apatinib has antineoplastic and antiangiogenic activities in gastric cancers, colon, breast, non-small cell lung and so on24.Apatinib (YN968D1), a novel tyrosine kinase inhibitor, is a highly selective VEGFR-2 inhibitor, with a binding affinity 45 times that of sorafenibHerein, we hypothesize combining iodized oil containing Apatinib with TAE has its potential activities in treating HCC. Owing to our limited understanding of the molecular mechanisms of Apatinib for HCC treatment and the Apatinib-mediated downstream pathways in HCC cells, further detailed studies are needed to elucidate the mechanism of Apatinib in HCC. Together, these results will be of great benefit to the strategies against human HCC.2 (normoxic conditions), and hypoxic conditions were simulated 24 h by incubation in RPMI 1640 medium containing 200 μM CoCl225. Primary antibody was obtained from Bioss (China); second antibody was obtained from Aspen.HepG2 was maintained in Dulbecco’s modified Eagle’s medium  with 10% fetal bovine serum (FBS), 100 mg/mL penicillin, and were cultured at 37 °C with 21% OHuman umbilical vein endothelial cells  were cocultured with HepG2 cells under normoxic or hypoxic conditions on Matrigel. The study design included 8 treatment groups: Groups A, B, C, and D were normoxic matrices with different concentrations of Apatinib  , and groups E, F, G, and H were hypoxic matrices with different dose of Apatinib . All experimental methods were ratified by the Animal Experiment Committee of Institute for Huazhong University of Science and Technology. And we confirmed that all experiments were performed in accordance with relevant guidelines and regulations.HepG2 cells were cultured and plated into 96-well flat bottom plates (100 mL per well) for 24 h under normoxic or hypoxic conditions. The cells were then supplemented with Apatinib at concentrations of 0, 0.1, 1, 10 or 50 µM. After 48 hours of treatment, CCK-8 solution was added and incubated at 37 °C for 4 hours. Cells were cultured for 1–4 h under the above conditions, and measured using microplate reader  with absorbance at 450 nm.5 cells was added to each well. After the cells are covered with the bottom of the well, the cells are crossed with the gun head perpendicular to the horizontal line of the marker pen. The smeared cells were gently rinsed with PBS and added to the medium. The cells were cultured in a cell culture incubator, and the well plates were taken out at 0 and 24 hours for photographing under an inverted microscope (Olympus).First draw a parallel line on the back of the 6-well plate with a marker pen and traverse the hole. 2 mL of medium containing approximately 5 × 105 cells was taken into the transwell chambers . Subsequently, 500 µL of complete medium containing 10% FBS was added to the 24-well plate, and the chamber was placed in the plate. Incubate for 48 h at 37 °C in a CO2 (content 5%) incubator. The stain was prepared and stained and photographed on the non-cell inoculated side.200 ul of serum-free cell suspension containing 104 HUVECs in 100 µL of complete medium containing different concentrations of apatinib were plated on the solidified Matrigel suspension. Twelve hours after the HUVECs were overlaid, the cocultures incubated on Matrigel  were inspected and photographed at 200 × magnification. Check 5 separate fields per well and calculate average tubes/field.Via a precooled tip, 50 µL of liquid Matrigel  was embedded into a 96-well plate at 4 °C. A total of 2 × 10PBS was prechilled at 4 °C and diluted with an appropriate amount of binding buffer. Then, the cells were collected in a flow tube and rinsed twice with PBS. Cell pellet resuspended in 300 µl Binding Buffer. Subsequently, 5 µL of annexin V-FITC was added, mix and incubate for 10 min in the dark. 5 µL PI was added, mixed and incubated. On-board detection within 1 h, FITC excitation 494 nm emission 520 nm, PI excitation 493 nm emission 636 nm.Cells were resuspended, centrifuged, and the cell pellet was collected. Add Protease Inhibitor Cocktail(ROCHE) and cell protein extraction reagent, repeatedly beat upon with a pipette to ensure complete cell lysis. After centrifugation at 13,000 g for 5 min at 4 °C, the supernatant was collected, which was the total protein solution. The sample protein concentration was determined using a BCA protein concentration assay kit , and ensure that the total amount of protein in each sample is 40 ug. Separation of proteins by SDS-PAGE  electrophoresis. And transferred onto PVDF membranes . Add primary and secondary antibodies for antibody incubation. The freshly prepared ECL  mixed solution was added dropwise to the protein side of the membrane, and exposed in a dark room. The film was scanned and archived, and the optical density of the target bands was analyzed by the AlphaEaseFC software processing system.HUVECs were added on sterilized coverslips in 6-well plates and treated according to the groups. 4% paraformaldehyde was fixed for 30 min and permeabilized using 3% H2O2 for 20 min. The cells were covered with a 5% BSA diluted primary antibody and incubated in a humidifying box overnight. Following incubation with a FITC- or Cy3-labeled goat anti-rabbit secondary antibody for 50 min, 50–100 ul of DAPI stain was added dropwise to each well and incubated for 5 min. Add anti-fluorescence quencher to the cells, cover the slides, and observe under a fluorescence microscope.The 2.5–3.0 kg adult New Zealand white rabbits used in this study were all purchased from the Animal Experimental Center of Huazhong University of Science and Technology. All experimental plans were ratified by the Animal Experiment Committee of Institute for Huazhong University of Science and Technology.The study design included 4 treatment groups and ten rabbits per group: the sham (NS) group ; the AI group (treatment with both 3 mL of lipiodol containing 50 mg of Apatinib and TAE); the I group (treatment with both 3 mL of lipiodol supplemented with a gelatin sponge); and the A group .3 VX2 tumor tissue, take from tumor-bearing rabbits, was implanted into left medial lobe of the liver approximately 0.5 cm in depth, and then covered by gelatin. At 16 days after implantation, the tumor sizes were measured by CT scan and the rabbits carrying tumors of 10- 20 mm in diameter were used for subsequent experiments.The rabbit’s abdominal cavity was cut about 4 cm to reveal the left medial liver lobe. A piece of 1 mmAll rabbits were anesthetized, and femoral artery was dissected and catheterized. Then, catheter was super-selectively inserted to the HCC feeding artery from the femoral artery under the digital subtraction angiography (DSA). Subsequently, the drugs were injected into the catheter according to the different groups. Finally, the femoral artery was sutured, and all rabbits were intramuscularly injected with penicillin daily for three days.1) and transverse diameter (D2) of tumor were separately recorded and Tumor volume was calculated by using the following modified formula for elliptic volume: V = D1 × D22/2. The tumor growth rate was calculated by using the following formula: V7/V0 * 100%Tumor growth was monitored with contrast-enhanced CT on days 0 and 7. After scanning, all the images acquired were processed by the Syngo Fastview image processing system, and the size, location, shape and the presence of necrosis and intrahepatic metastasis of the implanted tumor were analyzed by twos senior doctors of radiology department. The maximum diameter   Fig. . The dat05) Fig. . The exp05) Fig. . It confWe can see from the figure that a concentration-dependent manner in which Apatinib inhibits basal tube formation and HUVEC proliferation agents from 0 to 50 μM, especially in the hypoxic environment (P = 0.000 < 0.001) Fig. . The apoin vivo experiments also proved this. Immunohistochemical staining for CD31 expression, which is known to be highly correlated with tumor angiogenesis, was carried out to investigate the expression of tumor MVD. Consistent with the vitro model, the CD31 staining data revealed that the AI group had a significantly lower tumor MVD than the other three groups (P < 0.01)  Fig. , which sWound-healing and migration assays were performed for evaluating the control effect of Apatinib on migration and invasiveness of HUVECs. Apatinib showed inhibition of HUVECs at a very low dose (1 µM). Subsequently, after HUVECs treated with 10 and 50 μM Apatinib for 24 h, the invasion reduced by 43% and 56%, respectively, under normoxic conditions, and by 49% and 79%, respectively, under hypoxic conditions Fig. . What coThe pathway downstream of VEGF-VEGFR, such as PI3K-Akt, RAF-MEK-ERK and P38 MAPK, also mediate metatasis and proliferation of endothelial cell. To confirm whether the pathway was involved in the antiangiogenic responsiveness of Apatinib, the phosphorylation of some kinases were inspected by Western blot analysis. The experimental results revealed that the phosphorylation levels of ERK, Akt, PI3K and P38 were decreased in HUVECs after treated with Apatinib Fig. . ApatiniThe blockade of these kinases by Apatinib was so drastic that we further verified the reliability of the results by immunofluorescence. The immunofluorescence results indicated that Apatinib potentially exerted its inhibitory effects on HUVECs by decreasing activity in the PI3K-Akt, RAF-MEK-ERK and P38 MAPK signaling pathways Fig. .26. But because of recurrence and metastasis due to the highly hypoxic microenvironment after TAE, the outcomes remain modest. It is necessary to further study the effect of interventional embolization on the angiogenesis of HCC and the corresponding intervention for the changes of angiogenesis after embolization. Up to now, there is no report on the use of adopted iodized oil containing VEGFR-2 inhibitor Apatinib in interventional therapy of hepatocellular carcinoma. Therefore, we propose a new concept of interventional embolization combined with adopted iodized oil containing Apatinib targeted therapy of liver cancer. The results show that this new administration protocol successfully interrupted cell migration and the recurrence of VX2 liver tumors.TAE, as mentioned above, has been widely used to treat advanced HCC, and there was no difference between the TAE with or without doxorubicin15. Realizing the limitations of TAE due to hypoxia, more and more studies have explored new ways of vascular normalization to treat HCC. Thus, the antiangiogenic impact of Apatinib was further validated in HUVECs by bioassays, including cell migration, invasion and apoptosis, tube formation, and wound healing assays. These results revealed that Apatinib inhibits HUVEC migration and invasion, especially in hypoxic environments. The results of vivo experiments also confirmed that there were significant differences between the Group A and Group NS in tumor growth rate and MVD. Comprehensively, our results indicate that Apatinib has great potential as a pharmaceutical treatment for human HCC by inhibiting cell migration, invasion and survival.Angiogenesis, a hallmark of tumor development, is essential for cancer invasion and migration28. Moreover, the interaction between VEGF and VEGFR2 supports HCC cell growth and migration through an angiogenesis-independent antiapoptotic pathway31. However, the drugs that block VEGFA, which is considered a major VEGF involved in angiogenesis, have not achieved tiptop results4; therefore, Apatinib, a potent VEGFR-2 inhibitor, is considered. In this study, we had simulated the changing of tumor microenvironment before and after TAE both in vitro and vivo models. We found out that overproduction of VEGF and HIF-1α after embolization, and there are no significant difference between-group AI and I. But we demonstrated that Apatinib mixed with lipiodol to enter the tumor through the hepatic artery significantly reduced the MVD. In other words, Apatinib plays an antiangiogenic role after interventional embolization, blocking the regeneration of blood vessels. And this new administration protocol could significantly suppress the GR of VX2 liver tumors; this effect was further confirmed by the inhibition of HepG2 cell proliferation by Apatinib in the CCK-8 assays. Interestingly, we found that Apatinib was more potent against HepG2 cell proliferation in a hypoxic environment than in a normoxic environment, in a dose-dependent manner. Thus, we concluded that Apatinib has a direct toxic effect on HCC cells, that Apatinib can effectively inhibit tumor cell proliferation in a concentration-dependent manner, especially in the anoxic environment. And this is the reason why Apatinb can work efficient with TAE.Angiogenesis is critical for the proliferation and metastasis of HCC, and a high level of MVD, which is demonstrated a harmful prognosis marker for HCC patients and related to a reduction in patient survivalWhat is the major gap in the knowledge about TAE is that the incomplete understanding of the mechanism between antiangiogenesis and tumor growth. Insight into this mechanism represents a necessary foundation on which to increase the effectiveness of TAE treatment paradigms. HIF-1α is elevated after hypoxia and triggers the VEGF/VEGFR pathway, thereby induceing genes expression involved in cell proliferation and angiogenesis. Therefore, exploring the effect of Apatinib on these downstream pathways is very important. The PI3K/Akt signaling pathway, overactivated in many malignant tumor, is playing a vital role in various cellular processes involved in angiogenesis in endothelial cells. In addition to the PI3K/Akt signaling pathway, the VEGF/VEGFR pathway activate endothelial cell proliferation and metastasis by inducing other downstream kinases, such as P38, ERK and FAK. Indeed, the Western blotting results demonstrated that Apatinib downregulated the protein levels of p-ERK, p-Akt, p-PI3K and p-P38 in a concentration-dependent manner, especially in a hypoxic environment, which suggesting that the mechanism underlying the antiangiogenic effect of Apatinib is blocking the activation of these kinases.In summary, Apatinib can effectively block the VEGF-VEGFR pathway by downregulating the activity of the RAF-MEK-ERK, PI3K/Akt, and P38 MAPK signaling pathways, which contributed to inhibiting the growth, invasion and migration of the residual tumor after embolization in an anoxic microenvironment. And these findings made it a promising potential therapy of combining TAE therapy with the VEGFR-2 inhibitor Apatinib for the treatment of HCC. And our efforts have deepened the study of interventional treatment of liver cancer into the field of the tumor microenvironment and hopefully provide a new target and strategy for interventional therapy of liver cancer.Supplementary information.


Prospective studies investigating risk factors for low back pain (LBP) in youth athletes are limited. The aim of this prospective study was to investigate the association between hip-pelvic kinematics and vertical ground reaction force (vGRF) during landing tasks and LBP in youth floorball and basketball players.Three-hundred-and-eighty-three Finnish youth female and male floorball and basketball players (mean age 15.7 ± 1.8) participated and were followed up on for 3 years. At the beginning of every study year the players were tested with a single-leg vertical drop jump (SLVDJ) and a vertical drop jump (VDJ). Hip-pelvic kinematics, measured as femur-pelvic angle (FPA) during SLVDJ landing, and peak vGRF and side-to-side asymmetry of vGRF during VDJ landing were the investigated risk factors. Individual exposure time and LBP resulting in time-loss were recorded during the follow-up. Cox’s proportional hazard models with mixed effects and time-varying risk factors were used for analysis.We found an increase in the risk for LBP in players with decreased FPA during SLVDJ landing. There was a small increase in risk for LBP with a one-degree decrease in right leg FPA during SLVDJ landing . Our results showed no significant relationship between risk for LBP and left leg FPA , vGRF  or vGRF side-to-side difference  during landing tasks.Our results suggest that there is an association between hip-pelvic kinematics and future LBP. However, we did not find an association between LBP and vGRF. In the future, the association between hip-pelvic kinematics and LBP occurrence should be investigated further with cohort and intervention studies to verify the results from this investigation.Prognosis, level 1b. Findings Based on the results of this study, peak vGRF is a poor risk factor for LBP in youth team sport players. Hip-pelvic kinematics are associated with increased risk for LBP; smaller angle between the femur and pelvis increases the risk for all LBP and non-traumatic gradual onset LBP.Implications One cannot discriminate players with future LBP based on the femur-pelvic angle during SLVDJ landing alone. The association between hip-pelvic kinematics and other movement patterns, such as trunk kinematics, and risk for LBP in athletes merits further investigations.Caution The data recording and statistical analyses in this study did not take into account the temporal nature of physical abilities during the follow-up nor did it include psychosocial factors. Statistical power might not have been enough to reveal small to moderate associations. The results should be verified by future cohort and intervention studies.Back pain is common among youth athletes . Our prePrevious studies investigating intrinsic risk factors for LBP in youth have focused mostly on lower extremity and trunk muscle strength and endurance, flexibility and anthropometric measures , 7. ProsIt has been stated that the trunk, including lumbo–pelvic–hip complex, is the central point of kinetic chains of most sports activities and essential in decreasing back injuries . FurtherBasketball and floorball  are sports that include running, sudden direction changes and stops. In addition, basketball players perform lots of jumping and landing . These mThe aim of this exploratory prospective study was to investigate if hip-pelvic kinematics, measured as femur-pelvic angle (FPA), and peak vGRF during landing tasks, are associated with LBP incidence in a large cohort of youth basketball and floorball players. The prospective design and consideration of the individual training and game exposure hours adds to the novelty value of this study. The hypotheses were that  decreaseThis study is part of the large Finnish PROFITS study (Predictors of Lower Extremity Injuries in Team Sports) carried out between 2011 and 2015 [Ten female and male basketball and 10 floorball teams were recruited from six sports clubs in Tampere, Finland. Players older than 21 and younger than 12 at baseline were excluded. Data were collected at baseline in April or May of 2011, 2012, or 2013 as the player entered the study, and at the beginning of each study year in which the player participated. The players were followed prospectively for up to 3 years. Data from all players entering the follow-up were included in the analyses for the time they participated.The baseline questionnaire covered the following demographics: age, sex, dominant leg, nicotine use, family history of musculoskeletal disorders, and training and playing history during the previous 12 months.The players’ history of back pain was recorded using the Standardized Nordic questionnaire of musculoskeletal symptoms (modified version for athletes) , 22. HisThe baseline tests were performed at the UKK Institute over 1 day at the beginning of every follow-up year. The test procedures are outlined in more detail in previous reports , 24–29 aThe SLVDJ was used to investigate hip-pelvic kinematics. In the SLVDJ the player dropped off from a 10-cm box followed by a maximal vertical jump. Hip-pelvic angles were estimated from a still video image by an investigator using Java-based software , and FPA, outlined in Fig. The VDJ was used to investigate the vGRF during landing. During a valid VDJ test the player stood on the 30-cm box, dropped off the box and immediately after landing the player performed a maximal vertical jump. Absolute and weight adjusted peak vGRF and side-to-side asymmetry were investigated as potential risk factors. The same methodology has been used previously by, for example, Nilstad et al., Mok et al. and Krosshaug et al. –29. TheyThe primary outcomes were traumatic and non-traumatic LBP. LBP was defined as pain in the lower back area that prevented the player from taking full part in team practices and games for at least 24 h. LBP that resulted from a specific identifiable event, such as falling, was referred to as acute traumatic LBP. Non-traumatic LBP had gradual onset, without an identifiable event of trauma. Acute traumatic LBP events were categorised as “contact”, “indirect contact”, and “non-contact” . A contaOnce a week one of the two study physicians contacted the teams to interview the injured players. A structured injury questionnaire (Supplementary Table IBM SPSS Statistics (v. 23–24.0) and Chi-square test and the t-test (Mann-Whitney test when appropriate) were used for descriptive statistical analyses and the results were reported as the mean and standard deviation (SD). Cox’s proportional hazard models with mixed-effects were used to investigate the associations between potential risk factors and LBP (yes/no). This method accounts for the sports exposure and variance in follow-up time between the players. Mixed effects were used to account for the sports club as a random effect. Time-dependent variables were used, when possible, due to the tendency of changes in investigated variables over time. The individual game and practice hours from the start of the follow-up until the first event (LBP) or the end of follow-up (if no event) were included in analyses. For players reporting more than one LBP after the baseline, only the first was included. Data from all eligible players entering the follow-up were included in the analyses for the time they participated.R  packageNine teams of both sports agreed to participate Fig. , with a n = 205) reported no history of LBP at baseline. Of the 383 players, 13% (n = 48) sustained LBP during the follow up, 35% of them (n = 17) had not had back pain prior to the study. Half of the players developing LBP during the follow-up were females . Fifty-four percent of floorball players and 46% of basketball players had LBP during the follow-up. Most of the players who developed back pain during the follow up did so during their first follow-up year (81%) and only one player was followed for 3 years before developing LBP. LBP incidence was addressed in a previous publication [During the follow-up, altogether 566 athlete-years were recorded. Fifty-four percent of players , but no significant differences were observed between previous study years Table .Table 4The aim of this study was to investigate whether hip-pelvic kinematics and peak vGRF during landing tasks were associated with LBP incidence in youth floorball and basketball players. The first hypothesis was that the movement pattern, where the FPA is decreased during SLVDJ landing due to increased movement of the hip in the direction of adduction and contralateral pelvis drop might predispose for LBP. The second hypothesis was that players with higher or asymmetric peak vGRF during VDJ landing are at increased risk for LBP. Contrary to our second hypothesis, we did not find a statistically significant association between LBP and peak vGRF. However, our results suggested that there is an association between hip-pelvic kinematics and LBP.The lumbo-pelvic function is an essential part of successful athletic performance . AccordiOur results showed a small increase in risk (8%) for LBP with a one-degree decrease in the right leg FPA during the SLVDJ landing. This means a 2.2-fold increase in risk in players with less than 80° FPA during the right leg landing, compared to the players with more than 80° FPA. However, no association was detected between the left leg FPA and the risk of LBP. The difference between the right and left leg results might be due to the test procedure where the starting leg was not randomized, that is, the test was always started with the right leg. Another explanation may be the fact that in most players the right leg was their dominant (kicking) leg and the left leg was their supporting leg. This may explain why the left side was more stable during the SLVDJ. Our results are in line with previous studies suggesting that hip-pelvic kinematics are associated with injuries in athletes , 44, 45.Our second hypothesis was that vGRFs that affect the lumbar spine  could poThe strengths of this study were the prospective design and the methods of LBP and playing exposure registrations. In addition, the sample size was relatively large. The length of follow-up varied across the sample and therefore we used Cox regression analysis. Cox regression analysis can adjust for variations in the amount of sport participation (follow-up time). Yet, due to the relatively low number of LBP events, we were unable to stratify the analyses by sex. However, it seemed that sex was not significantly associated with LBP in this sample.n = 17) of the LBP recorded during follow-up was first-time LBP. We compensated for this by adjusting the risk factor analyses with a history of LBP.Risk factors can change over time and therefore we used time-varying variables in the Cox analysis, when possible. In addition, over half (54.5%) of the players had a history of LBP at the beginning of the study and 35% (n = 383) were not included in the risk factor analyses. In the SLVDJ 25% of the players and in the VDJ 19% of the players had incomplete baseline test data. The absence of these players might affect the results of this study. We are also unaware whether players refusing to participate differ from our sample. Another limitation is that we did not test the reliability of the selected tests during this study. However, the reliability of vGRF measurements has been demonstrated previously by Krosshaug and Mok and their colleagues [We should not overlook the fact that up to 25% of all players participating (lleagues , 29. Herlleagues . One limThe aetiology of LBP has been shown to be multifactorial , meaningOur results suggested that there is an association between hip-pelvic kinematics and LBP, as measured in this study. However, we did not find a statistically significant association between LBP peak vGRF or side-to-side asymmetry of vGRF during VDJ landing. In the future, the association between hip-pelvic kinematics and LBP incidence should be investigated further to verify the results from this study.Additional file 1 Supplementary Table 1. Data collected in the structured injury questionnaire.Additional file 2 Supplementary Table 2. Differences between players with and without baseline test result.


Spring migration phenology is shifting towards earlier dates as a response to climate change in many bird species. However, the patterns of change might not be the same for all species, populations, sex and age classes. In particular, patterns of change could differ between species with different ecology. We analyzed 18 years of standardized bird capture data at a spring stopover site on the island of Ponza, Italy, to determine species-specific rates of phenological change for 30 species following the crossing of the Mediterranean Sea. The advancement of spring passage was more pronounced in species wintering in Northern Africa (i.e. short-distance migrants) and in the Sahel zone. Only males from species wintering further South in the forests of central Africa advanced their passage, with no effect on the overall peak date of passage of the species. The migration window on Ponza broadened in many species, suggesting that early migrants within a species are advancing their migration more than late migrants. These data suggest that the cues available to the birds to adjust departure might be changing at different rates depending on wintering location and habitat, or that early migrants of different species might be responding differently to changing conditions along the route. However, more data on departure time from the wintering areas are required to understand the mechanisms underlying such phenological changes. Migration phenology in birds and other animals has been shifting in recent years, along with overall climate change –4. This https://www.ncdc.noaa.gov/teleconnections/nao/, last accessed on July 2nd, 2020). These environmental data suggest that species wintering in the Sahel and actively using stopover sites in Northern Africa might be more affected than others in their timing of passage, which should be reflected in an earlier arrival in Southern Europe.Some of the methods used for detecting switches in phenology have been object of debate , 47. StuHere, we aimed at identifying recent changes in migration phenology of migrants that cross the Mediterranean Sea, with a particular focus on within-species comparison between early and late migrants and on differences between species with different wintering areas. To this aim, we analyzed a large dataset of captures of migratory birds  on spring migration from a small Italian island, where large numbers of individuals of several species are stopping over after crossing the Mediterranean Sea . We calc2) located about 50 km off Italy , where spring bird migration has been monitored since 2002 (www.inanellamentoponza.it). Ponza attracts large numbers of African-European migratory landbirds during spring migration as it is located along one of the main Mediterranean migratory routes, with daily peaks of over 1500 individual birds ringed occurring several times during the study period. Birds were caught using mist-nets from March (or April in some years) to May (exact start and end dates are shown in http://www.vbonardi.it/) and model  constant throughout the entire study period. The birds were ringed, aged and sexed according to the available literature Reviewers' comments:Reviewer's Responses to QuestionsComments to the Author1. Is the manuscript technically sound, and do the data support the conclusions?The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: PartlyReviewer #2: Yes**********2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: NoReviewer #2: N/A**********3. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.The Reviewer #1: NoReviewer #2: No**********4. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #2: Yes**********5. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: The study entitled “Recent phenology shifts of migratory birds at a Mediterranean spring stopover site: birds wintering in the Sahel advance passage more than tropical winterers” reports the description of the temporal variation in the dates of passage during the pre-nuptial migration of 18 bird species in a small island of the Mediterranean sea (Ponza). The main result is that most of the species under investigation advanced their passage time, and therefore add to the hundreds of studies reporting similar findings elsewhere in the globe. It also shows that species that migrate longer distances show a smaller temporal variation in phenology (e.g. the slope of the passage date against year) than those migrating further, as well as that males generally show steeper trends than females. The study is merely descriptive but worthy for a least two reasons: 1) it is conducted at an important passage site of which no information on migration time was available to date, and 2) because it was conducted in a rather recent period (2002-2019), and it therefore shows that birds are still shifting their phenology . I am therefore generally positive about the possibility that the paper would be accepted for publication. However, I am some issues that I would like to raise below in order to improve, I hope, the quality and the readability of the manuscript. I think that they should be easily addressed by the authors.1) Statistical analyses and implications of the results. The conclusions are reasonable and compatible with the wide literature about the topic. However, I am not sure that the authors could claim that their study shows difference in the phenological variation between the species wintering in Northern Africa and in the Sahel zone and those wintering further South in the forests of central Africa without properly testing for it. I therefore encourage them adopt a proper statistical test in order to check for differences among groups of birds showing different migration strategies (and/or different wintering regions). This is also the case for the supposed differences between the phenology of males and females of some species. I am aware that the number of the species included in the analyses in not very large, but I think that there is the scope for splitting the species at least into two categories. However, if the authors think that this is not possible, in my opinion they should at least justify why they cannot analyse the data and add a caveat in the Discussion by acknowledging the reader about the limitations of their results.2) Main migration period. The study is focused on the start, end, duration and peak of the so-called ‘main migration period’. The procedure used to define this period seems accurate to me, and it is not my intention to question it. However, since the vast majority of the hundreds of studies on migration phenology published to date usually focus on mean/median and/or first (as well as last) passage dates, I am wondering why the authors opted for this different procedure, which make their results difficult to be compared with the previous ones. I would suggest to at least better justify this decision and to provide some solid reasons why this procedure is better, at least for the case under study, than that used in most of literature.3) Tables. I have also a concern about how tables have been completed. Frankly, I do not agree with reporting only significant relationships in the tables. I think it is important to report all the associations, including non-significant ones. This good practice is important, for example, to limit publication bias in meta-analytic studies. I therefore strongly encourage the authors to fully fill the tables. In addition, since the main message of the paper is a link between migration strategy and phenological change, I also think that it would be very helpful for the readers  to have some additional information about the species in the first part of the manuscript (other than in the Discussion where they are now reported). A possibility is to add a column in Table 1 reporting the migratory behaviour and/or the main wintering region of each species.4) Introduction. On the whole, it is concise and well written. However, I was rather surprised not to read any clear mention about the effect of migratory behaviour on variation in migration phenology, also considering that the authors explicitly referred to short- and long-distance migrants in the Discussion. I understand that the authors mentioned where different species spend the wintering period, but information might not be enough for a generalist reader. According to literature, change in phenology depending on migratory behaviour is one of the most consolidated knowledge on the effect of climate change on birds. I would therefore encourage the authors to add a short paragraph on this (including relevant references), linked to that one focused on the effects of NAOI and wintering areas.5) Discussion. As briefly mentioned above, I think that one the main interesting point of the study is that migration data have been collected rather recently. I think that the paper would benefit from the inclusion of an additional paragraph where the authors emphasize that the phenological shifting is still ongoing and compare their recent trends with those obtained by previous studies performed on very long time-series .6) Literature cited. References quoted in the paper are generally relevant. However, I noted that only a few very recent papers (after 2015) have been cited, despite the vast literature produced in the last years. This is especially the case for Introduction, in which some very relevant and recent papers are missing. I therefore suggest to add some of them in order to better introduce the concepts, which will be developed through the manuscript. Please, find below some missing articles which are very relevant to the purpose of the study, and deserve to be cited .- Kluen, E., Nousiainen, R., & Lehikoinen, A. (2017). Breeding phenological response to spring weather conditions in common Finnish birds: resident species respond stronger than migratory species. Journal of Avian Biology, 48(5), 611-619.- Samplonius, J. M., Bartošová, L., Burgess, M. D., Bushuev, A. V., Eeva, T., Ivankina, E. V., ... & Mänd, R. (2018). Phenological sensitivity to climate change is higher in resident than in migrant bird populations among European cavity breeders. Global change biology, 24(8), 3780-3790.- Ambrosini, R., Romano, A., & Saino, N. (2019). Changes in migration, carry-over effects, and migratory connectivity. Effects of Climate Change on Birds, 93.- Radchuk, V., Reed, T., Teplitsky, C., Van De Pol, M., Charmantier, A., Hassall, C., ... & Avilés, J. M. (2019). Adaptive responses of animals to climate change are most likely insufficient. Nature communications, 10(1), 1-14.- Horton, K. G., La Sorte, F. A., Sheldon, D., Lin, T. Y., Winner, K., Bernstein, G., ... & Farnsworth, A. (2020). Phenology of nocturnal avian migration has shifted at the continental scale. Nature Climate Change, 10(1), 63-68.Minor comments:LL 62-65. Maybe add some references here.L 74. “near-passerine”. I think this should be defined, especially in a very generalist journal like the present one.LL 89-92 and Table 1. It is ok to include information about the total number of individuals captured per species. However, because the authors declared that they selected the species to be included in the analyses based on the yearly number of captures, I think that an important missing information is also the range of individuals captured per species per year. In addition, it is not clearly described which criterion was used to decide whether including or not a species. For example, what is the minimum number of specimens per year? In addition, did the authors exclude some years within species because they could not collect information on a minimum number of individuals? In my opinion, all this information should be added to improve the understanding of the procedures used.LL 113-115. Interesting that all the species show a significant temporal variation (advance or delay) in the phenology of migration. This is a quite unexpected result, if we compare it with the available literature. How do the authors explain this result? Is possible that the procedure used to identify the main migration period has somehow affected this result?L 244. Publication number XX. Maybe there is an error here.Reviewer #2: This paper aims to analyse the spring migratory phenology of 30 species of birds in a Mediterranean island, for a period of 18 years. Authors found a broadening of the time of passage overall, due to an advancement of the passage by mostly short-distance migrants.The paper is well written, it is easy to follow and the concepts and literature used are within the expected current state of the art. A have, however, some comments to do:Main comments:The data set used in the study is impressive, and this is a robustness of the paper. However, the paper is totally descriptive, and the authors ‘only’ analyse a linear effect of year on the object, dependent variables . It would be really nice (though I acknowledge that this would entail much more work) if the authors may also look for the potential effects of conditions at wintering sites or during the passage across the Mediterranean. These analyses would allow a richer discussion around the observed changes/results. This is what I would also expect in a journal like PLOS ONE.Minor comments:L94-96. Quite often, mist nets must be closed due to very adverse weather  or even logistical reasons . Even though the authors say that the fieldwork was done on a daily basis, I would like to know to what extent this protocol was done with a 100% of, most likely, whether there were some gaps. In these cases, many authors think that replacing raw data by theoretical distribution regressions is better, since these last allow to: deal with gaps in the data set and smooth the potential effects of the variables affecting capture rates . Furthermore, these theoretical distributions would also allow dealing with years when the campaign started after the onset of migration, or ended before its end. Authors should discuss/defend their statistical approach and explain why not dealing with the use of theoretical distribution curves.L103. A good reason to use theoretical curves?L106-109. For me, this would be an insufficient explanation. There can be other distribution curves that might fit reasonably well to your data.L139. Please, this should be mention in Methods section.L157. Overall, the discussion might be benefited if the authors would also consider to test for the effects of conditions in the wintering/passing areas on their dependent variables.Table 1. Please, add SE to the beta parameter estimtes (slope).Table 2. Too many NAs in the start and end of migration. Why? Maybe this might be improved by using theoretical curves? If not, please limit the analyses to the peak passage parameter.**********what does this mean?). If published, this will include your full peer review and any attached files.6. PLOS authors have the option to publish the peer review history of their article  digital diagnostic tool,  8 Jul 2020Please find our answers to the reviewers' and editor's comments in the attached file.AttachmentResponse to reviewers_final_final.docxSubmitted filename: Click here for additional data file. 11 Aug 2020PONE-D-20-09340R1Recent phenological shifts of migratory birds at a Mediterranean spring stopover site: species wintering in the Sahel advance passage more than tropical winterersPLOS ONEDear Dr. Maggini,Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.This new version was revised by the Reviewer that raised the most serius concerns on the first version. He/she was rather satisfied by this new version, but he/she also asked for some further minor changes. We think you can easily modify the manuscript to acccount for these further suggestions. Please submit your revised manuscript by Sep 25 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at Please include the following items when submitting your revised manuscript:A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocolsIf applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: We look forward to receiving your revised manuscript.Kind regards,Roberto Ambrosini, Ph.D.Academic EditorPLOS ONE[Note: HTML markup is below. Please do not edit.]Reviewers' comments:Reviewer's Responses to QuestionsComments to the Author1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.Reviewer #1: All comments have been addressed**********2. Is the manuscript technically sound, and do the data support the conclusions?The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes**********3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes**********4. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.The Reviewer #1: Yes**********5. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: Yes**********6. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: I am rather satisfied by the revision made by the authors because they provided all the main suggested changes to the manuscript. In my opinion, the paper has considerably improved and I therefore suggest it for publication. I have only a few additional minor comments (lines numbers refer to the version including track changes):LL 151-152. Please add references used to define wintering areas and to associate species to them.L 211.5 rather than 22…a huge difference!LL 211-237. The reader is lost until the last line of this long paragraph because the table and the figure are cited only at end. I suggest to mention them before.L 237. Fig. S2, not S2 Fig.Table 2. I am not sure that P values between 0.05 and 0.10 should be mentioned in a table, even considering that exact P-values are provided in the supplementary materials.LL 383-384. There is some evidence that in many species the advance in arrival date in the breeding area is less steeper than the passage date in the Mediterranean area. This point might deserve a short discussion and some references (please see below).Both, C. (2010). Flexibility of timing of avian migration to climate change masked by environmental constraints en route. Current Biology, 20(3), 243-248.Jonzén, N., Lind´en, A., Ergon, T., Knudsen, E., Vik, J.O., Rubolini, D., Piacentini, D., Brinch, C., Spina, F., Karlsson, L., Stervander, M., Andersson, A., Waldenstr¨om, J., Lehikoinen, A., Edvardsen, E., Solvang, R. & Stenseth, N. C. (2006). Rapid advance of spring arrival dates in long-distance migratory birds. Science 312, 1959–1961.Bitterlin, L. R., & Van Buskirk, J. (2014). Ecological and life history correlates of changes in avian migration timing in response to climate change. Climate Research, 61(2), 109-121.LL 390-391. A very important study to be cited here is: Dunn, P. O., & Møller, A. P. (2014). Changes in breeding phenology and population size of birds. Journal of Animal Ecology, 729-739.**********what does this mean?). If published, this will include your full peer review and any attached files.7. PLOS authors have the option to publish the peer review history of their article  digital diagnostic tool,  12 Aug 2020Reviewer #1: I am rather satisfied by the revision made by the authors because they provided all the main suggested changes to the manuscript. In my opinion, the paper has considerably improved and I therefore suggest it for publication. We thank the reviewer for the renewed assessment of our manuscript, and especially for her/his comments on the previous version that helped us to largely improve this new version.I have only a few additional minor comments (lines numbers refer to the version including track changes):LL 151-152. Please add references used to define wintering areas and to associate species to them.The references are given in line 95 (new line numbering)L 211.5 rather than 22…a huge difference!We agree. This was due to a mistake in the previous analysis that we corrected in the new version. In the previous version, the large number of significant slopes caught the attention of the reviewers and was highly unlikely.LL 211-237. The reader is lost until the last line of this long paragraph because the table and the figure are cited only at end. I suggest to mention them before.We moved the reference to table and figure at the beginning of the paragraph.L 237. Fig. S2, not S2 Fig.This was suggested in the information for authors. We will change this if requested.Table 2. I am not sure that P values between 0.05 and 0.10 should be mentioned in a table, even considering that exact P-values are provided in the supplementary materials.We removed the highlights from slopes with p between 0.05 and 0.10 (we did the same in Table 3).LL 383-384. There is some evidence that in many species the advance in arrival date in the breeding area is less steeper than the passage date in the Mediterranean area. This point might deserve a short discussion and some references (please see below).Both, C. (2010). Flexibility of timing of avian migration to climate change masked by environmental constraints en route. Current Biology, 20(3), 243-248.Jonzén, N., Lind´en, A., Ergon, T., Knudsen, E., Vik, J.O., Rubolini, D., Piacentini, D., Brinch, C., Spina, F., Karlsson, L., Stervander, M., Andersson, A., Waldenstr¨om, J., Lehikoinen, A., Edvardsen, E., Solvang, R. & Stenseth, N. C. (2006). Rapid advance of spring arrival dates in long-distance migratory birds. Science 312, 1959–1961.Bitterlin, L. R., & Van Buskirk, J. (2014). Ecological and life history correlates of changes in avian migration timing in response to climate change. Climate Research, 61(2), 109-121.We added a sentence to acknowledge this (l. 302-304).LL 390-391. A very important study to be cited here is: Dunn, P. O., & Møller, A. P. (2014). Changes in breeding phenology and population size of birds. Journal of Animal Ecology, 729-739.We added this reference.See also the attached file.AttachmentResponse to reviewers revision.docxSubmitted filename: Click here for additional data file. 8 Sep 2020Recent phenological shifts of migratory birds at a Mediterranean spring stopover site: species wintering in the Sahel advance passage more than tropical winterersPONE-D-20-09340R2Dear Dr. Maggini,We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. 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For more information, please contact Kind regards,Roberto Ambrosini, Ph.D.Academic EditorPLOS ONEAdditional Editor Comments :Reviewers' comments: 10 Sep 2020PONE-D-20-09340R2 Recent phenological shifts of migratory birds at a Mediterranean spring stopover site: species wintering in the Sahel advance passage more than tropical winterers Dear Dr. Maggini:I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. onepress@plos.org.If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact plosone@plos.org. If we can help with anything else, please email us at Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staffon behalf ofDr. Roberto Ambrosini Academic EditorPLOS ONE


Bacillus thuringiensis (Bt) Cry toxins have transformed insect management in maize and cotton, reducing insecticide use and associated off-target effects. To mitigate the risk that pests evolve resistance to Bt crops, the US Environmental Protection Agency requires resistance management measures. The approved resistance management plan for Bt maize in cotton production regions requires a structured refuge of non-Bt maize equal to 20% of the maize planted; that for Bt cotton relies on the presence of an unstructured natural refuge comprising both non-Bt crop and non-crop hosts. We examined how abundance of Bt crops (cotton and maize) and an important non-Bt crop (soybean) component of the natural refuge affect resistance to Bt Cry1Ac toxin in local populations of Helicoverpa zea, an important lepidopteran pest impacted by Bt cotton and maize. We show refuge effectiveness is responsive to local abundances of maize and cotton and non-Bt soybean, and maize, in its role as a source of H. zea infesting cotton and non-Bt hosts, influences refuge effectiveness. These findings have important implications for commercial and regulatory decisions regarding deployment of Bt toxins targeting H. zea in maize, cotton, and other crops and for assumptions regarding efficacy of natural refuges.Genetically engineered crops expressing  Bacillus thuringiensis (Bt) has transformed insect management, especially in cotton (Gossypium hirsutum L.) and maize (Zea mays L.), resulting in reduced insecticide use and associated off-target effects, enhanced yields, and increased farmer profits6. In 2020, Bt varieties accounted for 88 and 82% of the cotton and maize, respectively, planted in the US7. This widespread adoption has resulted in area-wide suppression of some targeted pest populations and benefits that transcend Bt crops10. Resistance management measures are mandated by the US Environmental Protection Agency [EPA] as a condition for registration of Bt crops to preserve their associated crop protection and broader environmental benefits. Nonetheless, the benefits of Bt technology in maize and cotton are threatened by the evolution of resistance in several key pest species16. Principal among these in the southern US is Helicoverpa zea (Boddie) (Lepidoptera: Noctuidae), a consistent pest of both cotton and maize, commonly referred to as bollworm or corn earworm. Field-evolved H. zea resistance to Bt crystal-forming (Cry protein) toxins in maize and cotton has resulted in increasing damage in both crops and an increase in insecticide use in cotton and sweet corn14.The widespread adoption of genetically engineered crops expressing insecticidal toxins from Bt crops relies on the presence of a refuge from selection for resistance comprising non-Bt host plants. To function effectively, the refuge should be spatially close to the Bt crop and concurrently produce enough Bt-susceptible insects to mate with Bt-resistant individuals emerging from the Bt crop, thereby minimizing the frequency of resistance alleles in the population12. This strategy is most effective when Bt-plants express the toxin at a concentration sufficient to kill individuals heterozygous for a recessive resistance allele; generally referred to as high dose17. Although Bt maize hybrids expressing a single Bt toxin continue to be planted in limited areas, Bt maize and cotton varieties expressing multiple Bt toxins (pyramids) have replaced single-toxin varieties. Insects resistant to one of the toxins in a pyramid can be killed by the other(s). Pyramids are most effective when each toxin is expressed at a high dose and there is no cross-resistance between toxins12. Concentrations of Cry toxins expressed in Bt maize and cotton are high dose for some targeted lepidopteran pests  but not for H. zea, increasing the speed with which resistance is expected to develop12.Resistance management for Bt maize in cotton production regions requires planting a structured refuge of non-Bt maize equal to 20% of the total maize planted. In contrast, the refuge portion of the resistance management plan for Bt cotton relies on an unstructured natural refuge comprising non-Bt crop and non-crop host plants present in the refuge landscape18. Because the host range of H. zea encompasses many of the crops and non-crop plant species that are abundant in cotton production systems of the southeastern USA, it is assumed that the diversity and abundance non-Bt host plants in the natural refuge will produce enough Bt susceptible H. zea moths at the appropriate time to function effectively as a refuge. This assumption was critically examined by a Scientific Advisory Panel in 200619 and supported by studies that have shown H. zea populations developing on cotton were a relatively small proportion of the total population21. In 2018, a Scientific Advisory Panel18 recommended continued use of the natural refuge strategy for managing H. zea resistance to Bt toxins expressed in cotton.The US EPA-approved resistance management plan for 22, understanding factors influencing how the natural refuge functions for H. zea in cotton production systems is critical to inform development of resistance management strategies and regulatory policies relating to their implementation. Herein, we examine effects of varying abundance of two Bt crops (cotton and maize) and non-Bt soybean (Glycine max L.) within local landscapes in commercial field crop production systems on effectiveness of the natural refuge in suppressing resistance in H. zea populations to a Bt toxin (Cry1Ac). Soybean is an important non-Bt crop host of H. zea that varies greatly in abundance among locations.Because the speed of resistance evolution is inversely related to the amount of refugeHelicoverpa zea is a highly polyphagous, multivoltine pest that has numerous crop and non-crop hosts24. In the southeastern US, H. zea can complete at least four generations per year, with each generation potentially feeding on different crops at various phenological stages25. Adult moths that developed on maize ears disperse to infest other suitable crop and non-crop host plants. Included among these are bloom-stage cotton, soybean, peanut, and sorghum26. The importance of these crops as hosts following dispersal from maize varies greatly across the cotton production region, with soybean being particularly important in North Carolina26. Selection for resistance to Bt toxins occurs almost exclusively on Bt maize and cotton. However, maize also serves as an important source of H. zea that subsequently infest cotton, soybean and other non-Bt host plants comprising the natural refuge26. In cotton production areas, the non-Bt structured refuge required for Bt maize21 is a potentially important source of susceptible H. zea that subsequently infest cotton and the natural refuge for Bt cotton. However, compliance with the structured refuge requirement for maize by growers has been problematic27.Bt toxins, is currently expressed in all Bt cotton varieties; hence, populations developing on cotton are selected for resistance to Cry1Ac. Cry1Ac is not expressed in maize but the closely related Cry1Ab and Cry1A.105 toxins, also active against H. zea, are found in combination with other Cry toxins in commonly grown maize varieties. Cross resistance between Cry1Ac and Cry1Ab has been documented, so it is expected that indirect selection for resistance to Cry1Ac occurs in maize that expresses Cry1Ab29. Genetically modified soybean expressing Bt toxins is not registered for use in the US.Cry1Ac, in combination with one or more other H. zea larval populations that complete development in cotton and soybean subsequently overwinter as pupae in the soil. Previous research documented the importance of soybean as a late-season host for H. zea in North Carolina26. Based on this biology, we tested the assumption that underlies the natural refuge strategy for cotton; namely that the abundance and diversity of non-Bt crop and non-crop host plants in the local landscape are sufficient in practice to ensure the presence of a functional natural refuge. Specifically, we hypothesized that effectiveness of the natural refuge in suppressing Cry1Ac resistance in H. zea is dependent on the relative abundances of cotton and soybean in the local landscape. Because maize acts as a selection site for Cry-toxin resistance and a source of selected and non-selected populations  infesting both cotton and the natural refuge, we hypothesized that effects of the relative abundances of cotton and soybean on resistance of local H. zea populations are also dependent on the relative abundance of maize in the local landscape.A majority of H. zea, collected from non-Bt maize at 59 field locations in North and South Carolina, following exposure to a diagnostic concentration of the Cry1Ac toxin. Because resistance levels of H. zea to Cry1Ac have been shown previously to vary greatly among local populations of H. zea14, we expected that selection occurring locally and in the most recent past would have a strong influence on larval survival in the bioassay. We examined the relationships between the abundances of maize, cotton, and soybean within a 1-km radius of each collection site during the preceding year and effectiveness of the natural refuge as measured by variation in larval survival in the bioassay. Larval survival was fit to a binomial distribution with random effects intercepts for sample year using a generalized linear mixed model. Independent variables included proportional areas of each crop and their respective two-way interactions .To investigate these hypotheses, we measured survival of larval offspring of H. zea populations across field locations during 2017 and 2018, larval offspring of insects collected from non-Bt maize were subjected to a diet-overlay bioassay containing a diagnostic concentration of Cry1Ac (29 µg/cm2) corresponding to the mean LC95 of four Cry1Ac susceptible H. zea populations. Overall, larval survivorship varied significantly among years  among locations reveals high levels of spatial variation in resistance of local xin Fig. . BecauseBt toxins in H. zea occurs almost exclusively in maize and cotton, and selection is reduced at higher levels of relative abundance of non-Bt hosts in the landscape. The relationships are complex, reflecting how differences in the relative abundance of each of these crops affect H. zea populations and their associated inter-crop source-sink dynamics. These dynamics, in turn, influence the intensity of selection on the local populations.In our bioassay, higher survival indicates higher resistance to Cry1Ac. Selection for resistance to H. zea survival in the bioassay are highly significant  but neither the main effect of soybean nor the cotton * soybean interaction effect is significant . Importantly, the cotton * maize and the maize * soybean interaction effects are both highly significant  reveals considerable variation in abundances among years as well as among locations  to verify the plots were non-Bt maize.In 2017 and 2018, H. zea diet  was modified by adding casein to achieve a protein:carbohydrate ratio of 1.6:1 and supplemented with agar, anti-microbials and cellulose33. Pupae of each population were surface sterilized in a 1.3% bleach solution and placed in 1.8 L containers at a 3:1 female to male ratio (maximum 28 pupae per container). Containers were covered with cheesecloth to provide a substrate for oviposition and maintained at 25 °C, 50% RH, and natural photoperiod. Upon eclosion, moths were provided with 10% sucrose solution ad libitum. Eggs collected from the cheesecloth were transferred to 0.5-L containers where they hatched. Neonates less than 24 h old from each collection were used in a diet-based diagnostic-dose bioassay.Fifty to 120 larvae were collected from ears randomly selected from plants at least 5 m from the ends of the middle rows of each plot. Larvae were immediately placed on artificial diet in 30 mL plastic cups sealed with cardboard lids and held in coolers during transport to the laboratory where they were reared to pupation. The commercial 2, corresponding to the mean LC95 of four Cry1Ac susceptible H. zea colonies. Three colonies were started from field collections from Mississippi, North Carolina, and Louisiana in 2017, 2016, and 2016, respectively, and subsequently maintained in the laboratory at NC State University. The fourth was a laboratory colony obtained from Benzon Research, Inc. . In multiple bioassays of the Louisiana colony, this concentration resulted in a mean survivorship of 7% 34. Diet overlaid with 100 µL of aqueous Triton X-100 buffer in each of the remaining 16 cells per tray served as a control. Once the Cry1Ac solution dried, one neonate per well was added using a fine-tipped brush. The trays were then covered with a self-adhesive plate. Because colony size varied, not all assays had 112 larvae in the treated wells, but all had 16 larvae in the control wells. In 2017, bioassays were incubated in a growth chamber . In 2018, they were incubated at 25 °C and 50% RH to avoid condensation associated with a manufacturing change in cover plates. Bioassays were held for 7 days, after which mortality was assessed. Larvae that did not move after prodding with a brush were scored as dead. Proportion survival was corrected for control mortality using Abbott’s method35. Although our mortality measure did not include “functionally dead” larvae, we believe it provides a meaningful measure of variation in sensitivity to Cry1Ac among locations included in the study. We base this on the consistency of mortality among our reference populations and the large variation in survivorship we observed among the field collected populations in our study . This belief is further strengthened by our finding that variation in bioassay response is related to variation in relative abundances of maize, cotton, and soybean in a biologically meaningful way.Bioassays were prepared by adding 0.75 mL of diet to each well of a 128-well plastic tray, which was then covered and refrigerated until used. Diet trays were warmed to room temperature prior to overlaying the diet in each of 112 wells per tray. A 40 µL aliquot of a solution of Cry1Ac protein  dissolved in Triton X-100 (0.1%) buffer was applied to the diet surface to produce a Cry1Ac dose of 29 µg/cmBt maize plots to avoid confounding effects of resistance selection during the current year on survival. This allowed us to test for effects of maize, cotton and soybean abundance on resistance selection occurring during the prior year. Because no estimates of actual acreages of Bt maize and Bt cotton in landscapes surrounding each of the sample locations were available, our analysis was based on acreages of total maize, cotton, and soybean. Nationally, Bt varieties accounted for 88 and 82% of the cotton and maize, respectively, planted in the US during 20207. Landscape composition surrounding each sample site was determined using remotely sensed data from the USDA National Agricultural Statistics Service-Cropland Data Layer (CDL)36. Based on findings that a majority of marked H. zea moths emerging from maize fields were captured within 0.8 km of the source field37, we assumed that selection for resistance occurred locally on maize and cotton, and the abundance of these two crops would have the strongest effect on resistance levels observed in our samples. Therefore, we calculated proportional areas of maize, cotton, and soybean during the prior growing season within a 1-km buffer surrounding each collection location using ArcGIS .Larvae were collected from non-38. Proportional areas of cotton and soybean, and of cotton and maize, were not related. The proportional areas of maize and soybean were weakly but positively related; the regression accounted for only 7.2% of total variation . This model was selected over others that included the 3-way interaction because it had the lowest AIC value and allowed us to generate confidence intervals for predicted probability of survival. A Moran’s I test was conducted in R version 3.6.039 to test for spatial autocorrelation among sample sites40. Using survival in bioassays as the predictor, there was no evidence of autocorrelation among sample sites (P = 0.29), indicating that bioassay survival among sample sites was independent.To examine the relationships between the abundances of maize, cotton and soybean in the local landscape and effectiveness of the natural refuge as measured by variation in larval survival in the bioassay, we used a generalized linear mixed model with a binomial distribution and a logit link function in the GLIMMIX procedure of SAS version 9.4Supplementary Information.