ORCID Profile
0000-0002-8610-4016
Current Organisation
UNSW Sydney
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Oxford University Press (OUP)
Date: 2018
DOI: 10.1093/JAS/SKX044
Publisher: Springer Science and Business Media LLC
Date: 03-08-2023
Publisher: Cold Spring Harbor Laboratory
Date: 03-10-2023
Publisher: California Digital Library (CDL)
Date: 29-12-2019
Publisher: Wiley
Date: 06-06-2023
Abstract: Although meta‐analysis has become an essential tool in ecology and evolution, reporting of meta‐analytic results can still be much improved. To aid this, we have introduced the orchard plot, which presents not only overall estimates and their confidence intervals, but also shows corresponding heterogeneity (as prediction intervals) and in idual effect sizes. Here, we have added significant enhancements by integrating many new functionalities into orchaRd 2.0 . This updated version allows the visualisation of heteroscedasticity (different variances across levels of a categorical moderator), marginal estimates (e.g. marginalising out effects other than the one visualised), conditional estimates (i.e. estimates of different groups conditioned upon specific values of a continuous variable) and visualisations of all types of interactions between two categorical/continuous moderators. orchaRd 2.0 has additional functions which calculate key statistics from multilevel meta‐analytic models such as I 2 and R 2 . Importantly, orchaRd 2.0 contributes to better reporting by complying with PRISMA‐EcoEvo (preferred reporting items for systematic reviews and meta‐analyses in ecology and evolution). Taken together, orchaRd 2.0 can improve the presentation of meta‐analytic results and facilitate the exploration of previously neglected patterns. In addition, as a part of a literature survey, we found that graphical packages are rarely cited (~3%). We plea that researchers credit developers and maintainers of graphical packages, for ex le, by citations in a figure legend, acknowledging the use of relevant packages.
Publisher: Public Library of Science (PLoS)
Date: 13-08-2015
Publisher: Elsevier BV
Date: 06-2018
DOI: 10.3382/PS/PEY065
Abstract: Although many experiments have been conducted to clarify the response of broiler chickens to light-emitting diode (LED) light, those published results do not provide a solid scientific basis for quantifying the response of broiler chickens. This study used a meta-analysis to establish light spectral models of broiler chickens. The results indicated that 455 to 495 nm blue LED light produced the greatest positive response in body weight by 10.66% (BW P < 0.001) and 515 to 560 nm green LED light increased BW by 6.27% (P < 0.001) when compared with white light. Regression showed that the wavelength (455 to 660 nm) was negatively related to BW change of birds, with a decrease of about 4.9% BW for each 100 nm increase in wavelength (P = 0.002). Further analysis suggested that a combination of the two beneficial light sources caused a synergistic effect. BW was further increased in birds transferred either from green LED light to blue LED light (17.23% P < 0.001) or from blue LED light to green LED light (17.52% P < 0.001). Moreover, birds raised with a mixture of green and blue LED light showed a greater BW promotion (10.66% P 0.05). However, there was an interaction between the FCR response to monochromatic LED light with those covariant factors (P < 0.05). Additionally, green and yellow LED light played a role in affecting the meat color, quality, and nutrition of broiler chickens. The results indicate that the optimal ratio of green × blue of mixed LED light or shift to green-blue of combined LED light may produce the optimized production performance, whereas the optimal ratio of green/yellow of mixed or combined LED light may result in the optimized meat quality.
Publisher: California Digital Library (CDL)
Date: 06-06-2022
Publisher: American Society of Agricultural and Biological Engineers (ASABE)
Date: 2018
DOI: 10.13031/TRANS.12312
Abstract: The average weight and flock uniformity of broilers in group housing is important information that allows producers to know the flock growth conditions and determine the selling time. However, gathering weight information of chickens is not only labor-intensive for humans but also frightening for the birds. In this study, an image-assisted rod-platform weighing system was developed to automatically monitor the average weight and flock uniformity of broilers in chicken houses. This weighing system consists of a computer and several weighing scales. Each weighing scale contains a rod-platform weighing module and a surveillance camera module. The principle of the automated weighing system is to estimate population weight information using s les. The design of the rod-platform weighing module was based on the perching habit of birds to attract more broilers to stand on the rod platform and thus get more weight s les. The surveillance camera module is used to detect the number of broilers on the rod using image processing technology. A data processing method called PORWI, which includes elimination of redundant records and trim of non-redundant records, was designed to optimize the results of chicken number identification from images to improve the accuracy of the results. An experiment was done in two small groups of broilers with approximately 100 chickens and 8.58 m2 of area for each group. A weekly weighing was conducted, and three kinds of weight information were obtained, which included manual population weight information (MPWI), manual s le-based weight information (MSWI), and automated s ling weight information (ASWI). Each weight information set comprised the group average weight and flock uniformity, which were then used to evaluate accuracy. The perching rate of chickens using the rod platform reached an average of 60 times h-1, and the rate was retained with increasing age. Compared with the MPWI obtained by in idual weighing, the manual s le-based measurement method provided results with errors of 0% to +5%, while our automated weighing system achieved accuracies within ±2% for average weight and ±1.5% for flock uniformity. Keywords: Automatic weighing, Average weight, Broiler, Chicken detection, Uniformity.
Publisher: American Society of Agricultural and Biological Engineers (ASABE)
Date: 27-10-2016
Publisher: Center for Open Science
Date: 28-03-2023
Abstract: Power analysis currently dominates s le size determination, especially in grant and ethics applications. We plea for shifting away from this practice because such a focus could paradoxically result in a suboptimal study design. Also, undue focus on power increases disparities among scientists because only the wealthy can afford large experiments fulfilling the current power requirements. Our proposed paradigm shift involves better study designs with less focus on power, (pre-)registration and obligatory reporting, facilitating team science or multi-institutional collaboration that incorporates heterogenization, and prospective and living meta-analyses to reach generalization. Such changes would make science more effective and equitable, cultivating better collaborations.
Publisher: California Digital Library (CDL)
Date: 03-04-2021
Publisher: Springer Science and Business Media LLC
Date: 03-04-2023
DOI: 10.1186/S12915-022-01485-Y
Abstract: Collaborative efforts to directly replicate empirical studies in the medical and social sciences have revealed alarmingly low rates of replicability, a phenomenon dubbed the ‘replication crisis’. Poor replicability has spurred cultural changes targeted at improving reliability in these disciplines. Given the absence of equivalent replication projects in ecology and evolutionary biology, two inter-related indicators offer the opportunity to retrospectively assess replicability: publication bias and statistical power. This registered report assesses the prevalence and severity of small-study (i.e., smaller studies reporting larger effect sizes) and decline effects (i.e., effect sizes decreasing over time) across ecology and evolutionary biology using 87 meta-analyses comprising 4,250 primary studies and 17,638 effect sizes. Further, we estimate how publication bias might distort the estimation of effect sizes, statistical power, and errors in magnitude (Type M or exaggeration ratio) and sign (Type S). We show strong evidence for the pervasiveness of both small-study and decline effects in ecology and evolution. There was widespread prevalence of publication bias that resulted in meta-analytic means being over-estimated by (at least) 0.12 standard deviations. The prevalence of publication bias distorted confidence in meta-analytic results, with 66% of initially statistically significant meta-analytic means becoming non-significant after correcting for publication bias. Ecological and evolutionary studies consistently had low statistical power (15%) with a 4-fold exaggeration of effects on average (Type M error rates = 4.4). Notably, publication bias reduced power from 23% to 15% and increased type M error rates from 2.7 to 4.4 because it creates a non-random s le of effect size evidence. The sign errors of effect sizes (Type S error) increased from 5% to 8% because of publication bias. Our research provides clear evidence that many published ecological and evolutionary findings are inflated. Our results highlight the importance of designing high-power empirical studies (e.g., via collaborative team science), promoting and encouraging replication studies, testing and correcting for publication bias in meta-analyses, and adopting open and transparent research practices, such as (pre)registration, data- and code-sharing, and transparent reporting.
Publisher: California Digital Library (CDL)
Date: 29-10-2021
Publisher: Springer Science and Business Media LLC
Date: 14-01-2016
DOI: 10.1038/SREP19291
Abstract: A previous study demonstrated that birds that are exposed to light at night develop advanced reproductive systems. However, spectrum might also affect the photoperiodic response of birds. The present study was aimed to investigate the effects of spectral composition on the growth and reproductive physiology of female breeders, using pure light-emitting diode spectra. A total of 1,000 newly hatched female avian breeders ( Gallus gallus ) were equally allocated to white-, red-, yellow-, green- and blue-light treated groups. We found that blue-light treated birds had a greater and faster weight gain than did red- and yellow-light treated birds ( P = 0.02 and 0.05). The red light expedited the sexual maturation of the chicks, whose age at sexual maturity was 7 and 14 days earlier than that of the green- and blue-light treated birds, respectively. The accumulative egg production of the red-light treated birds was 9 and 8 eggs more than that of the blue- and green-light treated birds. The peak lay rate of the red-light treated groups was significantly greater than the blue-light treated birds ( P = 0.028). In conclusion, exposure to short-wavelength light appears to promote growth of female breeder birds, whereas exposure to long-wavelength light appears to accelerate reproductive performance.
Publisher: Springer Science and Business Media LLC
Date: 04-10-2022
DOI: 10.1038/S41597-022-01704-9
Abstract: Rising temperatures represent a significant threat to the survival of ectothermic animals. As such, upper thermal limits represent an important trait to assess the vulnerability of ectotherms to changing temperatures. For instance, one may use upper thermal limits to estimate current and future thermal safety margins (i.e., the proximity of upper thermal limits to experienced temperatures), use this trait together with other physiological traits in species distribution models, or investigate the plasticity and evolvability of these limits for buffering the impacts of changing temperatures. While datasets on thermal tolerance limits have been previously compiled, they sometimes report single estimates for a given species, do not present measures of data dispersion, and are biased towards certain parts of the globe. To overcome these limitations, we systematically searched the literature in seven languages to produce the most comprehensive dataset to date on hibian upper thermal limits, spanning 3,095 estimates across 616 species. This resource will represent a useful tool to evaluate the vulnerability of hibians, and ectotherms more generally, to changing temperatures.
Publisher: Wiley
Date: 11-06-2020
DOI: 10.1002/JRSM.1424
Publisher: International Journal of Agricultural and Biological Engineering (IJABE)
Date: 2019
Publisher: Springer Science and Business Media LLC
Date: 21-04-2016
DOI: 10.1038/SREP24808
Abstract: Long daylength artificial light exposure associates with disorders and a potential physiological mechanism has been proposed. However, previous studies have examined no more than three artificial light treatments and limited metabolic parameters, which have been insufficient to demonstrate mechanical responses. Here, comprehensive physiological response curves were established and the physiological mechanism was strengthened. Chicks were illuminated for 12, 14, 16, 18, 20, or 22 h periods each day. A quadratic relationship between abdominal adipose weight (AAW) and light period suggested that long-term or short-term light exposure could decrease the amount of AAW. Quantitative relationships between physiological parameters and daily light period were also established in this study. The relationships between triglycerides (TG), cholesterol (TC), glucose (GLU), phosphorus (P) levels and daily light period could be described by quadratic regression models. TG levels, AAW and BW positively correlated with each other, suggesting long-term light exposure significantly increased AAW by increasing TG thus resulting in greater BW. A positive correlation between blood triiodothyronine (T3) levels and BW suggested that daily long-term light exposure increased BW by thyroid hormone secretion. Though the molecular pathway remains unknown, these results suggest a comprehensive physiological mechanism through which light exposure affects growth.
Publisher: California Digital Library (CDL)
Date: 12-09-2022
Publisher: Public Library of Science (PLoS)
Date: 03-12-2014
Publisher: Elsevier BV
Date: 04-2015
Publisher: Wiley
Date: 10-12-2021
DOI: 10.1111/GCB.15972
Abstract: Field studies are essential to reliably quantify ecological responses to global change because they are exposed to realistic climate manipulations. Yet such studies are limited in replicates, resulting in less power and, therefore, potentially unreliable effect estimates. Furthermore, while manipulative field experiments are assumed to be more powerful than non‐manipulative observations, it has rarely been scrutinized using extensive data. Here, using 3847 field experiments that were designed to estimate the effect of environmental stressors on ecosystems, we systematically quantified their statistical power and magnitude (Type M) and sign (Type S) errors. Our investigations focused upon the reliability of field experiments to assess the effect of stressors on both ecosystem's response magnitude and variability. When controlling for publication bias, single experiments were underpowered to detect response magnitude (median power: 18%–38% depending on effect sizes). Single experiments also had much lower power to detect response variability (6%–12% depending on effect sizes) than response magnitude. Such underpowered studies could exaggerate estimates of response magnitude by 2–3 times (Type M errors) and variability by 4–10 times. Type S errors were comparatively rare. These observations indicate that low power, coupled with publication bias, inflates the estimates of anthropogenic impacts. Importantly, we found that meta‐analyses largely mitigated the issues of low power and exaggerated effect size estimates. Rather surprisingly, manipulative experiments and non‐manipulative observations had very similar results in terms of their power, Type M and S errors. Therefore, the previous assumption about the superiority of manipulative experiments in terms of power is overstated. These results call for highly powered field studies to reliably inform theory building and policymaking, via more collaboration and team science, and large‐scale ecosystem facilities. Future studies also require transparent reporting and open science practices to approach reproducible and reliable empirical work and evidence synthesis.
Publisher: Springer Science and Business Media LLC
Date: 03-04-2023
Publisher: Elsevier BV
Date: 06-2018
DOI: 10.1016/J.JPHOTOBIOL.2018.04.040
Abstract: Though previous study indicated that the 580 nm-yellow-LED-light showed an stimulating effect on growth of chickens, the low luminous efficiency of the yellow LED light cannot reflect the advantage of energy saving. In present study, the cool white LED chips and yellow LED chips have been combined to fabricate the white × yellow mixed LED light, with an enhanced luminous efficiency. A total 300 newly hatched chickens were reared under various mixed LED light. The results indicated that the white × yellow mixed LED light had "double-edged sword" effects on bird's body weight, bone development, adipose deposition, and body temperature, depending on variations in ratios of yellow component. Low yellow ratio of mixed LED light (Low group) inhibited body weight, whereas medium and high yellow ratio of mixed LED light (Medium and High groups) promoted body weight, compared with white LED light (White group). A progressive change in yellow component gave rise to consistent changes in body weight over the entire experiment. Moreover, a positive relationship was observed between yellow component and feed conversion ratio. High group-treated birds had greater relative abdominal adipose weight than Medium group-treated birds (P = 0.048), whereas Medium group-treated birds had greater relative abdominal adipose weight than Low group-treated birds (P = 0.044). We found that mixed light improved body weight by enhancing skeletal development (R
Publisher: Wiley
Date: 29-03-2021
DOI: 10.1111/BRV.12712
Abstract: Physical exercise not only helps to improve physical health but can also enhance brain development and cognition. Recent reports on parental (both maternal and paternal) effects raise the possibility that parental exercise may provide benefits to offspring through intergenerational inheritance. However, the general magnitude and consistency of parental exercise effects on offspring is still controversial. Additionally, empirical research has long overlooked an important aspect of exercise: its effects on variability in neurodevelopmental and cognitive traits. Here, we compiled data from 52 studies involving 4786 rodents (412 effect sizes) to quantify the intergenerational transmission of exercise effects on brain and cognition. Using a multilevel meta‐analytic approach, we found that, overall, parental exercise showed a tendency for increasing their offspring's brain structure by 12.7% (albeit statistically non‐significant) probably via significantly facilitating neurogenesis (16.5%). Such changes in neural anatomy go in hand with a significant 20.8% improvement in neurobehaviour (improved learning and memory, and reduced anxiety). Moreover, we found parental exercise significantly reduces inter‐in idual differences (i.e. reduced variance in the treatment group) in progeny's neurobehaviour by 10.2% (coefficient of variation ratio, lnCVR), suggesting the existence of an in idual by intervention interaction. The positive effects of exercise are modulated by several covariates (i.e. moderators), such as the exercised parent's sex, offspring's sex, and age, mode of exercise, and exercise timing. In particular, parental forced exercise is more efficient than voluntary exercise at significantly improving offspring neurobehaviour (26.0%) and reducing its variability (14.2%). We observed larger effects when parental exercise started before pregnancy. However, exercising only during pregnancy also had positive effects. Mechanistically, exercise significantly upregulated brain‐derived neurotrophic factor (BDNF) by 28.9%, vascular endothelial growth factor (VEGF) by 35.8%, and significantly decreased hippoc al DNA methylation by 3.5%, suggesting that brain growth factor cascades and epigenetic modifications can moderate the transmission of parental exercise effects. Collectively, by coupling mean with variance effects, our analyses draw a more integrated picture of the benefits that parental exercise has on offspring: not only does it improve offspring brain development and cognitive performance, but it also reduces inter‐in idual differences in cognition‐related traits. We advocate that meta‐analysis of variation together with the mean of a trait provides novel insights for old controversies as well as emerging new questions, opening up a new era for generating variance‐based hypotheses.
Publisher: Elsevier BV
Date: 03-2023
Publisher: Wiley
Date: 10-11-2022
Abstract: Publication bias threatens the validity of quantitative evidence from meta‐analyses as it results in some findings being overrepresented in meta‐analytic datasets because they are published more frequently or sooner (e.g. ‘positive’ results). Unfortunately, methods to test for the presence of publication bias, or assess its impact on meta‐analytic results, are unsuitable for datasets with high heterogeneity and non‐independence, as is common in ecology and evolutionary biology. We first review both classic and emerging publication bias tests (e.g. funnel plots, Egger's regression, cumulative meta‐analysis, fail‐safe N , trim‐and‐fill tests, p ‐curve and selection models), showing that some tests cannot handle heterogeneity, and, more importantly, none of the methods can deal with non‐independence. For each method, we estimate current usage in ecology and evolutionary biology, based on a representative s le of 102 meta‐analyses published in the last 10 years. Then, we propose a new method using multilevel meta‐regression, which can model both heterogeneity and non‐independence, by extending existing regression‐based methods (i.e. Egger's regression). We describe how our multilevel meta‐regression can test not only publication bias, but also time‐lag bias, and how it can be supplemented by residual funnel plots. Overall, we provide ecologists and evolutionary biologists with practical recommendations on which methods are appropriate to employ given independent and non‐independent effect sizes. No method is ideal, and more simulation studies are required to understand how Type 1 and Type 2 error rates are impacted by complex data structures. Still, the limitations of these methods do not justify ignoring publication bias in ecological and evolutionary meta‐analyses.
Publisher: Wiley
Date: 08-06-2023
DOI: 10.1002/ECY.4069
Publisher: Springer Science and Business Media LLC
Date: 12-05-2016
DOI: 10.1038/SREP25972
Abstract: Present study introduced a new method to manipulate broiler chicken growth and metabolism by mixing the growth-advantage LED. We found that the green/blue LED mixed light system (G-B and G × B) have the similar stimulatory effect on chick body weight with single green light and single blue light (G and B), compared with normal artificial light ( P = 0.028). Moreover, the percentage of carcass was significantly greater in the mixed light (G × B) when compared with the single light ( P = 0.003). Synchronized with body weight, the mixed light (G-B and G × B) had a significant improved influence on the feed conversion of birds compared with normal light ( P = 0.002). A significant improvement in feed conversion were found in mixed light (G × B) compared with single LED light ( P = 0.037). G group resulted in a greater high-density lipoprotein cholesterol level than B group ( P = 0.002), whereas B group resulted in a greater low-density lipoprotein cholesterol level than G group ( P = 0.017). The mixed light significantly increased the birds’ glucose level in comparison with the single light ( P = 0.003). This study might establish an effective strategy for maximizing growth of chickens by mixed LED technology.
Publisher: Springer Science and Business Media LLC
Date: 24-04-2023
DOI: 10.1186/S13750-023-00301-6
Abstract: Meta-analysis is a quantitative way of synthesizing results from multiple studies to obtain reliable evidence of an intervention or phenomenon. Indeed, an increasing number of meta-analyses are conducted in environmental sciences, and resulting meta-analytic evidence is often used in environmental policies and decision-making. We conducted a survey of recent meta-analyses in environmental sciences and found poor standards of current meta-analytic practice and reporting. For ex le, only ~ 40% of the 73 reviewed meta-analyses reported heterogeneity (variation among effect sizes beyond s ling error), and publication bias was assessed in fewer than half. Furthermore, although almost all the meta-analyses had multiple effect sizes originating from the same studies, non-independence among effect sizes was considered in only half of the meta-analyses. To improve the implementation of meta-analysis in environmental sciences, we here outline practical guidance for conducting a meta-analysis in environmental sciences. We describe the key concepts of effect size and meta-analysis and detail procedures for fitting multilevel meta-analysis and meta-regression models and performing associated publication bias tests. We demonstrate a clear need for environmental scientists to embrace multilevel meta-analytic models, which explicitly model dependence among effect sizes, rather than the commonly used random-effects models. Further, we discuss how reporting and visual presentations of meta-analytic results can be much improved by following reporting guidelines such as PRISMA-EcoEvo (Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Ecology and Evolutionary Biology). This paper, along with the accompanying online tutorial, serves as a practical guide on conducting a complete set of meta-analytic procedures (i.e., meta-analysis, heterogeneity quantification, meta-regression, publication bias tests and sensitivity analysis) and also as a gateway to more advanced, yet appropriate, methods.
Publisher: Oxford University Press (OUP)
Date: 02-2015
Abstract: This study aimed to establish response curves between broiler chicken growth parameters and artificial light periods, as opposed to optimizing a lighting regimen for broiler production. Medium-growing broiler chickens were illuminated for periods of 12, 14, 16, 18, 20, 22, or 24 h each day. The BW of the broilers were significantly influenced by light periods ( < 0.05). Moreover, BW responded to light periods in a linear fashion, suggesting that long light periods result in greater BW. In addition, a linear relationship was found between feed intake and light periods. However, the relationship between shank length and light period was quadratic. When the light period was too short (12 h) or too long (24 h), the light stimulus did not enhance shank growth in the broiler chickens ( < 0.05). In addition, a quadratic relationship between the quantity of abdominal adipose tissue and light period suggested that the quantity of abdominal adipose decreases when the period of the light stimulus was too short or too long ( < 0.05). Moreover, a broken-stick analysis suggested that the triiodothyronine (T3) concentration in the blood was minimally affected beyond 18 h ( = 0.267), although a quadratic relationship was found between the period (from 18 to 24 h) and T3 concentrations in the blood. The response curves established in the present study will be valuable for designing future lighting regimes for medium-growing broiler strains.
No related grants have been discovered for Yefeng Yang.