Differences in spatial versus temporal reaction norms for spring and autumn phenological events

For species to stay temporally tuned to their environment, they use cues such as the accumulation of degree-days. The relationships between the timing of a phenological event in a population and its environmental cue can be described by a population-level reaction norm. Variation in reaction norms along environmental gradients may either intensify the environmental effects on timing (cogradient variation) or attenuate the effects (countergradient variation). To resolve spatial and seasonal variation in species’ response, we use a unique dataset of 91 taxa and 178 phenological events observed across a network of 472 monitoring sites, spread across the nations of the former Soviet Union. We show that compared to local rates of advancement of phenological events with the advancement of temperature-related cues (i.e., variation within site over years), spatial variation in reaction norms tend to accentuate responses in spring (cogradient variation) and attenuate them in autumn (countergradient variation). As a result, among-population variation in the timing of events is greater in spring and less in autumn than if all populations followed the same reaction norm regardless of location. Despite such signs of local adaptation, overall phenotypic plasticity was not sufficient for phenological events to keep exact pace with their cues—the earlier the year, the more did the timing of the phenological event lag behind the timing of the cue. Overall, these patterns suggest that differences in the spatial versus temporal reaction norms will affect species’ response to climate change in opposite ways in spring and autumn.

To stay tuned to their environment, species need to respond to both short- and long-term variation in climatic conditions. In temperate regions, favorable abiotic conditions, key resources, and major enemies may all occur early in a warm year, whereas they may occur late in a cold year. Coinciding with such factors may thus come with pronounced effects on individual fitness and population-level performance (1–4). As phenological traits also show substantial variability within and among populations, they can be subject to selection in nature (5–7), potentially resulting in patterns of local adaptation (8–10).At present, the rapid rate of global change is causing shifts in species phenology across the globe (11–13). Of acute interest is the extent to which different events are shifting in unison or not, sometimes creating seasonal mismatches and functionally disruptive asynchrony (3, 14–16). If much of the temporal and spatial variation in seasonal timing is a product of phenotypic plasticity, then changes can be instant, and sustained synchrony among interaction partners will depend on the extent to which different species react similarly to short-term variation in climatic conditions. If geographic variation in phenology reflects local adaptive evolutionary differentiation, then, in the short term, as climate changes, phenological interactions may be disrupted due to the lag as adaptation tries to catch up (17–19). By assuming that space can substitute time, it is possible to make inference about the role that adaptation to climate may play. How well species stay in synchrony will then depend on the extent to which local selective forces act similarly or differently on different species and events.Local adaptation in phenology may take two forms. 1) The magnitude of phenological change might vary along environmental gradients in ways that intensify the environmental effects on phenological traits, a process known as cogradient variation (Fig. 1B). In such a case, the covariance between the genetic influences on phenological traits and the environmental influences is positive. Under this scenario, the effect of environmental variation over space and time will be larger than if all populations were to follow the same reaction norm regardless of location. 2) Genotypes might counteract environmental effects, thereby diminishing the change in mean trait expression across the environmental gradient. In such a case, the effect of environmental variation over space and time will be smaller than if all populations were to follow the same reaction norm regardless of location. This latter scenario, termed countergradient variation, occurs when genetic and environmental influences on phenotypic traits oppose one another (Fig. 1C) (20, 21).Open in a separate windowFig. 1.Schematic illustration showing slopes of phenology on temperature. Adapted with permission from ref. 30. A corresponds to phenological plasticity with respect to temperature and no local adaptation. B reveals phenological plasticity with respect to temperature plus cogradient local adaptation. C reveals phenological plasticity with respect to temperature plus countergradient local adaptation. For each scenario, we have included two examples of events showing this type of pattern in our data. For the exact climatic cues related to these biotic events, see SI Appendix, Table S1. In each plot, the red lines correspond to the within-population reaction norms through time (i.e., temporal slopes within locations), and the blue line corresponds to the between-population reaction norm (i.e., spatial slopes). If all populations respond alike, then the same reaction norm will apply across all locations, and individuals will respond in the same way to the cue no matter where they were, and no matter whether we examine responses within or between locations. If this was the case, then the reaction norm would be the same within (red lines) and between locations, and the blue and the red slopes would be parallel (i.e., their slopes identical). This scenario is depicted in A. What we use as our estimate of local adaptation is the difference between the two, i.e., whether the slope of reaction norms within populations differs from that across populations. If the temporal slopes are estimated at a relatively short time scale (as compared to the generation length of the focal organisms), then we can assume that within-location variation in the timing of the event reflects phenotypic responses alone, not evolutionary change over time. This component is then, per definition, due to phenotypic plasticity as such, i.e., to how individuals of a constant genetic makeup respond to annual variation in their environment. By comparison, the spatial slope (i.e., the blue line) is a sum of two parts: first, it reflects the mean of how individuals of a constant genetic makeup respond to annual variation in their environment, i.e., the temporal reaction norm defined above. These means are shown by the red dots in A–C. However, second, if populations differentiate across sites, then we will see variation in their response to long-term conditions, with an added element in the spatial slope reflecting mean plasticity plus local adaptation. Therefore, if the spatial slope differs from the temporal slope, this reveals local adaptation (see Materials and Methods for further details). Such local adaptation in phenological response may take two forms. 1) The magnitude of phenological change might vary along environmental gradients in ways that intensify the environmental effects on phenological traits, a process known as cogradient variation (Fig. 1B). In such a case, the covariance between the genetic influences on phenological traits and the environmental influences is positive. Under this scenario, variation in the environmental cue over space and time will cause larger variation in phenological timing than if all populations were to follow the same reaction norm regardless of location. 2) Genotypes might counteract environmental effects, thereby diminishing the change in mean trait expression across the environmental gradient. In such a case, the effect of variation in the environmental cue over space and time will be smaller than if all populations were to follow the same reaction norm regardless of location. This latter scenario, termed countergradient variation, occurs when genetic and environmental influences on phenotypic traits oppose one another (C).For phenology, the overall prevalence of co- versus countergradient patterns is crucial, as it will dictate the extent to which local adaptation will either accentuate or attenuate phenological responses to temporal shifts in climate (10). Across environmental gradients in space, the relative prevalence of counter- versus cogradient variation in spring versus autumn will critically modify how climatic variation affects the length of the activity period of the entire ecological community. Overall, geographic variation in the activity period will be maximized when events in autumn and spring differ in terms of whether they adhere to patterns of co- or countergradient variation.Although the study of individual species and local species communities has revealed fine-tuning of species to local conditions (22), and a wealth of studies report shifts in phenology worldwide (23), we still lack a general understanding of how the two tie together: how strong is local adaptation in the timing of events, and how do they vary across the season? Here, a major hurdle to progress has been a skew in the focus of past studies: our current understanding of climatic effects on phenology has been colored by springtime events (24–26), whereas events with a mean occurrence later in the season have been disproportionately neglected (27). To achieve satisfactory insight into how climate and its change affect the timing of biological activity across the season, we should thus ask how strongly phenology is influenced by climatic variation, what part of this response reflects phenotypic plasticity and what part evolutionary differentiation, and how the relative imprint of the two varies across the season. Addressing these pertinent questions is logistically challenging (e.g., ref. 28). Therefore, few studies have tackled them outside of the laboratory (29).Phillimore and coworkers (10, 30) proposed an elegant technique for identifying the relative roles of plasticity and local adaptation in generating spatiotemporal patterns of phenological variation. The rationale is to use a space versus time comparison (10, 30) (but see ref. 31 for criticism), drawing on the realization that at any one site, local conditions will vary between years. To be active at the right time, species will thus need to respond to temporal variation in climatic conditions. Let us assume that a focal species times some aspect of its annual activity (a species-specific “phenological event”) by reacting to a single environmental cue (e.g., the crossing of a given temperature sum). Now, if there were no differentiation between populations and all populations followed the same reaction norm, then with variation in the relative timing of the cue over time, all populations would react in the same way to the same cue regardless of spatial location (Fig. 1A). At the level of population means across space (blue line in Fig. 1A), we would then see a relationship between phenological event and cue timing identical to year-to-year variation within locations (red lines in Fig. 1A). However, if populations differentiate across sites, then we will see an added component in the spatial slope, reflecting the contribution of local adaptation to the mean phenology of the populations. By subtracting the within-population temporal slope from the spatial slope, we will thus achieve a direct measure of local adaptation (10), henceforth called Δb (30).Importantly, the temporal slope (i.e., the local phenological response to local year-to-year variation in the cue) can be either steeper or more shallow than the spatial slope (Fig. 1B vs. Fig. 1C)—the former being a sign of countergradient local adaptation, the latter of cogradient local adaptation (20, 21, 32). For a worked-through example of how this methodology is applied to the current data, see SI Appendix, Text S1.Here, we adopt temperature sums as widely used predictors of phenological events (33–35) and treat the difference between the spatial and temporal slopes of phenological events on such sums as our estimates of local adaptation in reaction norms (SI Appendix, Text S1). Pinpointing the relative roles of plasticity and microevolution from spatiotemporal observations in the absence of direct measures of fitness will, per necessity, rely on several assumptions (for a full discussion, see ref. 36). However, given the adequate precaution, such quantification allows a tractable way toward estimating local adaption on a large scale (8, 10, 30, 36–38).A key requirement for the successful application of this approach to resolving patterns across events of different relative timing is the existence of abundant data covering a large geographic area (30, 36). The extensive phenological data-collection scheme implemented at hundreds of nature reserves and other monitoring sites within the area of the former Soviet Union offers unique opportunities for addressing community-level phenology across a large space and long time (39). From this comprehensive dataset spanning 472 monitoring sites, 510,165 events and a time series of up to 118 y (Fig. 2 and ref. 39), we selected those 178 phenological events for which we have at least 100 data points that represent at least 10 locations (SI Appendix, Table S1). These events concerned 91 distinct taxa (SI Appendix, Table S1).Open in a separate windowFig. 2.Study sites and spatiotemporal patterns in climatic and phenological data. A shows the depth of the data and the spatial distribution of monitoring sites, with the size of the symbol proportional to the number of events scored locally. Since the selection of sites differed between events (39), in A, we have pooled sites located within 300 km from each other for illustration purposes. B shows the mean timing (day of year) of a phenological event: the onset of blooming in dandelion (Taraxacum officinale). C shows the mean timing (day of year) of a climatic event: the day of the year when the temperature sum providing the highest temporal slope for the onset of blooming in dandelion was first exceeded, computed as the mean over the years considered in B. For a worked-through example estimating reaction norms and metrics of local adaptation (Δb) for this species, see SI Appendix, Text S1.To express data on species phenology and abiotic conditions in the same currency, we related the dates of the phenological events (e.g., the first observation of an animal, or first flowering time of a plant species; SI Appendix, Fig. S1) to the dates when a given thermal sum (34, 35) was first exceeded. This choice of units has a convenient consequence in terms of the interpretation of slope values: if the date of phenology changes follows one-to-one the date of attaining a given temperature sum, then the slope will be one—an assumption frequently made but rarely tested in studies based on growth-degree days. The observed reaction norms can then be compared to this value. A value below 1 will signal undercompensation, i.e., that the earlier the cue, the larger the relative delay of the phenological event compared to its cue. By contrast, a value larger than 1 would signal overcompensation, i.e., that with an advancement of the cue, the timing of the phenological event will be advanced even more.Since thermal sums can be formed using a variety of thresholds, we used a generic approach and considered dates for exceeding a wide range of both heating and chilling degree-day sums (34, 35) (see Material and Methods for more information). As there is also evidence that sensitivity to temperature arises after a certain time point (13, 36), we calculated each heating and chilling degree-days sum for a range of starting dates. For each of the resulting 2,926 events, we then picked the variable that offered the highest temporal slope estimate, i.e., the largest within-location change in the timing of the event with a change in the timing of the cue (see Material and Methods for more information). Following the rationale outline above, this will be the most appropriate optimization criterion, since it selects the cue to which the phenological event responds the strongest to over time.     

Screening for VACTERL Anomalies in Children with Anorectal Malformations: Outcomes of a Standardized Approach

PurposeThe majority of patients with an anorectal malformation (ARM) have associated congenital anomalies. It is well established that all patients diagnosed with an ARM should undergo systematic screening, including renal, spinal, and cardiac imaging. This study aimed to evaluate the findings and completeness of screening, following local implementation of standardized protocols.MethodsA retrospective cohort study was performed assessing all patients with an ARM managed at our tertiary pediatric surgical center, following a standardized protocol implementation for VACTERL screening (January 2016–December 2021). Cohort demographics, medical characteristics, and screening investigations were analyzed. Findings were compared with our previously published data (2000–2015), conducted prior to protocol implementation.ResultsOne hundred twenty-seven (64 male, 50.4%) children were eligible for inclusion. Complete screening was performed in 107/127 (84.3%) children. Of these, one or more associated anomalies were diagnosed in 85/107 (79.4%), whilst the VACTERL association was demonstrated in 57/107 (53.3%). The proportion of children that underwent complete screening increased significantly in comparison with those assessed prior to protocol implementation (RR 0.43 [CI 0.27–0.66]; p < 0.001). Children with less complex ARM types were significantly less likely to receive complete screening (p = 0.028). Neither presence of an associated anomaly, nor prevalence of the VACTERL association, differed significantly by ARM type complexity.ConclusionScreening for associated VACTERL anomalies in children with ARM was significantly improved following standardized protocol implementation. The prevalence of associated anomalies in our cohort supports the value of routine VACTERL screening in all children with ARM, regardless of malformation type.Level of EvidenceII.     

An investigation into the reliability and methodology of the Linburg-Comstock anomaly clinical test

Study DesignThis is a cross-sectional study.IntroductionAn intertendinous connection between the flexor pollicis longus (FPL) and index flexor digitorum profundus (IFDP) tendons causes involuntary index flexion during active thumb flexion and has been named the Linburg-Comstock anomaly (LCA). It may become symptomatic or cause functional limitations. Literature has documented the prevalence to range from 13% to 70%. Cadaver studies have reported an anatomical connection in 5% to 25%.PurposeThis study aimed to examine the methodology and reliability of the LCA clinical diagnostic test and to explore the wide range of reported incidence and the discrepancy between cadaver and subject prevalence.MethodsTwo examiners observed for the presence of involuntary index flexion during 3 separate variations of thumb flexion in 67 subjects (134 limbs); results were considered positive if involuntary flexion occurred at either index interphalangeal joint. Intertester reliability was assessed using Cohen's kappa coefficient. The volar forearm and wrist of 53 cadavers (106 limbs) were dissected and assessed for an observable and mechanical tendinous connection between the FPL and IFDP tendons.ResultsPrevalence for subjects (5%-32%) was at the lower end of the range of previously reported values; results differed with altering thumb flexion motion. Observation for the presence of an intertendinous connection between the FPL and IFDP tendons in cadaver specimens (23%) fell within previously reported ranges. Intertester reliability coefficients ranged from no to weak agreement and varied according to specific thumb flexion motion performed during the test.ConclusionsThe identification of index finger flexion during thumb flexion varied both with thumb flexion motions and with whether flexion was assessed at the index proximal interphalangeal or distal interphalangeal joint. Intertester reliability was low for all variations of the LCA clinical test performed. The wide range in previously reported LCA incidence may be due to variability in testing procedure, and there is a need to establish a reliable and valid clinical test for this potentially symptomatic anatomic anomaly.     

New local hyperthermia using dextran magnetite complex (DM) for oral cavity: experimental study in normal hamster tongue

The possibility of dextran magnetite complex (DM) as a new hyperthermic material was examined in this study. DM suspension of 56 mg ml(-1) iron concentration was locally injected into the normal tongue of golden hamster. DM injected tongues were heated by 500 kHz alternating current (AC) magnetic field and its serial changes in temperature were recorded at 30-s intervals. The temperature of DM injected tongue was maintained at about 43.0-45.0 degrees C for 30 min by changing the AC magnetic field intensity. While temperature elevations of the contralateral tongue and the rectum were only of minor degree. In experiment on the extent of heating area, there was correlation between volume of black stain area and amount of the injected DM suspension (Y = - 18.1 + 1.94X, r = 0.931, P < 0.0001, n = 9 ). Histological examination after heating revealed brown uniform DM accumulation in the connective tissue between fibers of the tongue muscle. Except for vascular dilatations, no tissue damage was seen in the heated tongue. Thus, DM which has the possibility of selective and uniform heating in local hyperthermia might be useful for oral cancer therapy.     

安氏II类2分类错与先天性牙异常的关系

目的 :为了验证安氏II类 2分类错牙合与先天性牙异常如过小侧切牙、釉质发育不良、多生牙、易位牙、尖牙阻生和缺牙之间存在的关系。方法 :对 10 0例年龄 12～ 42岁未经历正畸治疗的II类 2分类错牙合患者的病史、口内、X片和牙模型进行检查 ,并进行样本百分比分析。结果 :结果显示牙异常者占 5 0 .0 0 %。 7.0 0 %的患者上侧切牙釉质发育不良 ,2 8.0 0 %过小侧切牙 ,4.0 0 %尖牙阻生 ,9.0 0 %下切牙缺失 ,易位牙为 2 .0 0 % ,无一例多生牙。 3 0 .0 0 %前牙Bolton比值不协调。结论 :安氏II类 2分类错牙合与过小侧切牙、釉质发育不良、先天缺牙密切相关。II类 2分类错牙合前牙Bolton比值不协调的主要因素是过小侧切牙和下切牙缺失     

上中切牙短根畸形患者骨性错[牙合]和轴倾度的临床分析

目的探讨昆明市人群中非综合征型短根畸形(short root anomaly,SRA)的患病率及与骨性错[牙合]和上中切牙轴倾度分布的关系,为SRA患者的正畸临床诊疗提供一定参考。方法回顾性分析2011年1月~2019年7月笔者所在医院收治患者CBCT数据库并随机抽样选取1000例,诊断出SRA患者27例(SRA组);对照组,为非SRA患者中随机选取的100例患者,根据其临床资料以及头影测量数据,将骨性错[牙合]分为I类骨性错,Ⅱ类骨性错[牙合],Ⅲ类骨性错[牙合]3个亚组,将中切牙轴倾度分为唇倾型、腭倾型和正常唇倾度型3个亚组,分析SRA组和对照组的性别、骨性错[牙合]以及上中切牙轴倾度分布情况。结果本研究所选人群中SRA的患病率为2.7%,女性的SRA患病率为3.67%(21/572),高于男性患病率1.4%(6/428),SRA患病率的性别差异具有统计学意义(χ^2=4.562,P=0.033)。SRA患者与对照组骨性错[牙合]构成比差异具有统计学意义(χ^2=8.710,P=0.013)。SRA患者骨性错以Ⅲ类骨性错[牙合]为主。SRA患者与对照组上中切牙轴倾度型构成比不同,差异具有统计学意义(χ^2=16.75,P<0.001)。SRA患者上中切牙轴倾度以腭倾型为主。结论SRA与Ⅲ类骨性错[牙合]及前牙腭倾型轴倾度有关,正畸治疗前需对此类患者的冠根比和根形进行评估。     

Regional odontodysplasia: Report of three cases

Regional odontodysplasia is a developmental anomaly of dental tissues with characteristic clinical, radiographic, and histologic appearances. It most commonly affects the maxillary anterior teeth of both the primary and permanent dentition, and occurs in females twice as often as in males. The pathogenesis is unknown. The clinical and histopathologic findings of regional odontodysplasia in three patients are discussed.     

Rare Presentation of Foot Postaxial Polydactyly

Polydactyly is a prevalent birth anomaly observed in the foot, and a number of classification systems have been suggested for this condition. Postaxial (fifth or little toe) polydactyly is the most common type. We encountered an exceedingly rare presentation of foot postaxial polydactyly that, to our inspection, had neither been previously classified nor described in published studies. In the present report, we have described an otherwise healthy 2-year-old female who had presented to our clinic with an isolated, extra little toe on her left foot. Foot radiographs revealed the presence of all 5 metatarsals; however, the fifth metatarsal was blocked and did not give rise to the fifth toe. Instead, the fifth (medial normal) and sixth (lateral extra) toes had originated from a single, separate accessory bud from the fourth metatarsal, and the main fourth metatarsal had given rise to the normal fourth toe. The lateral sixth toe was excised, and a periosteal sleeve of the excised extra toe was used for reconstruction of the lateral collateral ligament. We propose that this heretofore unmentioned presentation of postaxial polydactyly be added to the existing systems of classification of pedal polydactyly. A review of the published data pertaining to pedal polydactyly has also been presented.