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Scleractinian corals are colonial animals with a range of life history strategies, making up diverse species assemblages that define coral reefs. We tagged and tracked approximately 30 colonies from each of 11 species during seven trips spanning six years (2009-2015) in order to measure their vital rates and competitive interactions on the reef crest at Trimodal Reef, Lizard Island, Australia. Pairs of species were chosen from five growth forms where one species of the pair was locally rare (R) and the other common (C). The sampled growth forms were massive [Goniastrea pectinata (R) and G. retiformis (C)], digitate [Acropora humilis (R) and A. cf. digitifera (C)], corymbose [A. millepora (R) and A. nasuta (C)], tabular [A. cytherea (R) and A. hyacinthus (C)] and arborescent [A. robusta (R) and A. intermedia (C)]. An extra corymbose species with intermediate abundance, A. spathulata was included when it became apparent that A. millepora was too rare on the reef crest, making the 11 species in total. The tagged colonies were visited each year in the weeks prior to spawning. During visits, two or more observers each took 2-3 photographs of each tagged colony from directly above and on the horizontal plane with a scale plate to track planar area. Dead or missing colonies were recorded and new colonies tagged in order to maintain approximately 30 colonies per species throughout the six years of the study. In addition to tracking tagged corals, 30 fragments were collected from neighboring untagged colonies of each species for counting numbers of eggs per polyp (fecundity); and fragments of untagged colonies were brought into the laboratory where spawned eggs were collected for biomass and energy measurements. We also conducted surveys at the study site to generate size structure data for each species in several of the years. Each tagged colony photograph was digitized by at least two people. Therefore, we could examine sources of error in planar area for both photographers and outliners. Competitive interactions were recorded for a subset of species by measuring the margins of tagged colony outlines interacting with neighboring corals. The study was abruptly ended by Tropical Cyclone Nathan (Category 4) that killed all but nine of the over 300 tagged colonies in early 2015. Nonetheless, these data will be of use to other researchers interested in coral demography and coexistence, functional ecology, and parametrizing population, community and ecosystem models. The data set is not copyright restricted, and users should cite this paper when using the data. Publisher PDF

An all-inclusive and accurate prediction of outcomes for patients with acute ischemic stroke (AIS) is crucial for clinical decision-making. This study developed extreme gradient boosting (XGBoost)-based models using three simple factors—age, fasting glucose, and National Institutes of Health Stroke Scale (NIHSS) scores—to predict the three-month functional outcomes after AIS. We retrieved the medical records of 1848 patients diagnosed with AIS and managed at a single medical center between 2016 and 2020. We developed and validated the predictions and ranked the importance of each variable. The XGBoost model achieved notable performance, with an area under the curve of 0.8595. As predicted by the model, the patients with initial NIHSS score > 5, aged over 64 years, and fasting blood glucose > 86 mg/dL were associated with unfavorable prognoses. For patients receiving endovascular therapy, fasting glucose was the most important predictor. The NIHSS score at admission was the most significant predictor for those who received other treatments. Our proposed XGBoost model showed a reliable predictive power of AIS outcomes using readily available and simple predictors and also demonstrated the validity of the model for application in patients receiving different AIS treatments, providing clinical evidence for future optimization of AIS treatment strategies.

The International Classification of Functioning, Disability and Health (ICF) core set (CS) facilitates the standardization of functioning and impairment assessment for integration of holistic care.This study developed an ICF CS for interviewing pediatric brain tumor survivors in Taiwan to help healthcare professionals in implementing disability assessment and management measures.A group of 29 experts in 10 relevant fields with at least 5 years of experience working with children with brain tumors participated in this study. The first questionnaire contained 247 second-level ICF categories. The experts rated the significance of each category by using a 5-point Likert scale. Correlations between individual and group scores were calculated to determine consensus. Categories with an average rating of higher than 4 and for which greater than or equal to 80% (23) of the participants provided a rating of 4 or higher were included in the final CS.The final CS contained a total of 57 ICF categories: 20 from the Body Functions and Structures component, 36 from the Activities and Participation component, and 1 from the Environmental Factors component.The ICF CS for pediatric brain tumor survivors provides a framework for relevant healthcare professionals to deliver patient-centered care, ensuring that services focus on all areas of development.Patient ratings for this ICF CS may serve as a new practical and effective patient-reported information tool for acquiring patient input and for the systematic monitoring of pediatric brain tumor survivors in clinical practice. Further research should be conducted on this CS to verify our findings.

Ocean warming is increasing the incidence, scale, and severity of global-scale coral bleaching and mortality, culminating in the third global coral bleaching event that occurred during record marine heatwaves of 2014-2017. While local effects of these events have been widely reported, the global implications remain unknown. Analysis of 15,066 reef surveys during 2014-2017 revealed that 80% of surveyed reefs experienced significant coral bleaching and 35% experienced significant coral mortality. The global extent of significant coral bleaching and mortality was assessed by extrapolating results from reef surveys using comprehensive remote-sensing data of regional heat stress. This model predicted that 51% of the world’s coral reefs suffered significant bleaching and 15% significant mortality, surpassing damage from any prior global bleaching event. These observations demonstrate that global warming’s widespread damage to coral reefs is accelerating and underscores the threat anthropogenic climate change poses for the irreversible transformation of these essential ecosystems.

Polycyathus chaishanensis is a symbiotic caryophyllid coral described from a single population in a tidal pool off Chaishan, Kaohsiung, Taiwan. Due to its rarity, P. chaishanensis was declared a critically-endangered species under the Taiwan Wildlife Protection Act. In May 2017, a P. chaishanensis colony was discovered in the intertidal area of the Datan Algal Reef, Taoyuan, Taiwan. To determine whether this is a stable population in the algal reef, a demographic census—including data on occurrence, distribution, and colony size—was carried out in the algal reef in southern Taoyuan. Intertidal censuses and sediment collections were conducted at five different sections—Baiyu, Datan G1, Datan G2, Yongxing, and Yongan algal reefs—during the monthly spring low tide from July 2018 to January 2019. In total, 84 colonies—23 in Datan G1 and 61 in Datan G2—were recorded from a tidal range of − 160 to − 250 cm, according to the Taiwan Vertical Datum 2001 compiled by the Central Weather Bureau. No P. chaishanensis was found in Baiyu, Yongxing, or Yongan. The P. chaishanensis colony sizes ranged from 2.55 to 81.5 cm in diameter, with the larger P. chaishanensis present in the lower intertidal zone. Sediment was extremely high, with monthly site averages ranging from 3,818.26 to 29,166.88 mg cm−2 day−1, and there was a significant difference between sites and months, both of which affected the distribution of P. chaishanensis in the algal reef. Our study confirms the existence of a second population of P. chaishanensis in Taiwan, highlighting the importance of the Datan Algal Reef for the survival and protection of this critically-endangered caryophyllid coral and why it is so urgent that the reef should be conserved.

Comparative lists of species’ extinction risk are increasingly being used to prioritise conservation resources. Extinction risk is most rigorously assessed using quantitative data on species’ population trajectories, but in the absence of such data, assessments often rely on qualitative estimates based on expert opinion of species abundances, distributions and threats. For example, one-third of coral species are classified as threatened and another third as near threatened on the IUCN Red List, despite a lack of data at the population level for the vast majority of species. Since many taxa show a strong correlation between species traits and extinction risk, an alternate approach is to identify traits associated with extinction in other groups and apply them to the taxon of interest. Here, we examine whether life-history traits associated with stress tolerance, fecundity and habitat specialisation are correlated with Red List conservation status in reef corals. We found no relationship between conservation status and life-history traits, suggesting that either traits identified as important predictors of extinction risk in other taxa are not important in corals, or that conservation status does not accurately reflect species’ relative extinction risk. Therefore, using global-scale extinction risk assessments to inform conservation of coral reefs presents a high risk of ‘silent extinctions’ of undescribed species. We argue that the conservation status for the vast majority of coral species should be ‘data deficient’ and is likely to remain so for the foreseeable future, and that the status and trends of coral populations can only be reliably assessed at relatively small scales.

Introduction Assisted reproductive technology has been proposed for women with infertility. Moreover, in vitro fertilization (IVF) cycles are increasing. Factors contributing to successful pregnancy have been widely explored. In this study, we used machine learning algorithms to construct prediction models for clinical pregnancies in IVF. Materials and methods A total of 24,730 patients entered IVF and intracytoplasmic sperm injection cycles with clinical pregnancy outcomes at Taipei Medical University Hospital. Data used included patient characteristics and treatment. We used machine learning methods to develop prediction models for clinical pregnancy and explored how each variable affects the outcome of interest using partial dependence plots. Results Experimental results showed that the random forest algorithm outperforms logistic regression in terms of areas under the receiver operating characteristics curve. The ovarian stimulation protocol is the most important factor affecting pregnancy outcomes. Long and ultra-long protocols have shown positive effects on clinical pregnancy among all protocols. Furthermore, total frozen and transferred embryos are positive for a clinical pregnancy, but female age and duration of infertility have negative effects on clinical pregnancy. Conclusion Our findings show the importance of variables and propensity of each variable by random forest algorithm for clinical pregnancy in the assisted reproductive technology cycle. This study provides a ranking of variables affecting clinical pregnancy and explores the effects of each treatment on successful pregnancy. Our study has the potential to help clinicians evaluate the success of IVF in patients.

The integrity of coral reefs has increasingly been threatened by human development and climate change. As a result, the concept of ecological resilience – an ecosystem’s capability to resist and recover from environmental stressors – has become an important aspect of coral reef conservation. In this study, coral reef resilience was quantitatively scored in Kenting National Park (KNP), Taiwan, using four different assessment frameworks: the first uses the opinions of local reef experts, the second includes metrics specific to the local reef context, the third combines the previous two approaches, and the fourth relies solely on ecological metrics from biodiversity surveys. To evaluate the accuracy of each assessment, the resulting resilience scores were compared with historical coral recovery rates, which served as a proxy for resilience. While each approach to measuring resilience has its merits and drawbacks, the picture of resilience became clearest when a few key indicators were included to reflect core ecosystem processes. Trends in resilience scores varied depending on the makeup of the assessment's indicators, and there was little correlation between the baseline metrics measured using different data collection methods. However, all resilience assessment trends indicated that KNP’s Nanwan area is high in resilience. This is likely due to the effects of local tidally-induced upwelling, which significantly relieve the growing thermal stress placed on surrounding coral communities. Ultimately, the most successful assessments were those that empirically quantified ecological processes and local factors with only a few indicators, rather than broader approaches that measured many indicators. These findings are particularly relevant for reef managers to consider as they develop and employ resilience-based management strategies.

The discovery of multi-species synchronous spawning of scleractinian corals on the Great Barrier Reef in the 1980s stimulated an extraordinary effort to document spawning times in other parts of the globe. Unfortunately, most of these data remain unpublished which limits our understanding of regional and global reproductive patterns. The Coral Spawning Database (CSD) collates much of these disparate data into a single place. The CSD includes 6178 observations (3085 of which were unpublished) of the time or day of spawning for over 300 scleractinian species in 61 genera from 101 sites in the Indo-Pacific. The goal of the CSD is to provide open access to coral spawning data to accelerate our understanding of coral reproductive biology and to provide a baseline against which to evaluate any future changes in reproductive phenology., info:eu-repo/semantics/published

This study aimed to investigate the possible incidence of visual light perceptions (VLPs) during radiation therapy (RT). We analyzed whether VLPs could be affected by differences in the radiation energy, prescription doses, age, sex, or RT locations, and whether all VLPs were caused by radiation. From November 2016 to August 2018, a total of 101 patients who underwent head-and-neck or brain RT were screened. After receiving RT, questionnaires were completed, and the subjects were interviewed. Random forests (RF), a tree-based machine learning algorithm, and logistic regression (LR) analyses were compared by the area under the curve (AUC), and the algorithm that achieved the highest AUC was selected. The dataset sample was based on treatment with non-human units, and a total of 293 treatment fields from 78 patients were analyzed. VLPs were detected only in 122 of the 293 exposure portals (40.16%). The dataset was randomly divided into 80% and 20% as the training set and test set, respectively. In the test set, RF achieved an AUC of 0.888, whereas LR achieved an AUC of 0.773. In this study, the retina fraction dose was the most important continuous variable and had a positive effect on VLP. Age was the most important categorical variable. In conclusion, the visual light perception phenomenon by the human body during RT is induced by radiation rather than being a self-suggested hallucination or induced by phosphenes.

Introduction Conflicting results persist regarding the effectiveness of robotic-assisted gait training (RAGT) for functional gait recovery in post-stroke survivors. We used several machine learning algorithms to construct prediction models for the functional outcomes of robotic neurorehabilitation in adult patients. Methods and materials Data of 139 patients who underwent Lokomat training at Taipei Medical University Hospital were retrospectively collected. After screening for data completeness, records of 91 adult patients with acute or chronic neurological disorders were included in this study. Patient characteristics and quantitative data from Lokomat were incorporated as features to construct prediction models to explore early responses and factors associated with patient recovery. Results Experimental results using the random forest algorithm achieved the best area under the receiver operating characteristic curve of 0.9813 with data extracted from all sessions. Body weight (BW) support played a key role in influencing the progress of functional ambulation categories. The analysis identified negative correlations of BW support, guidance force, and days required to complete 12 Lokomat sessions with the occurrence of progress, while a positive correlation was observed with regard to speed. Conclusions We developed a predictive model for ambulatory outcomes based on patient characteristics and quantitative data on impairment reduction with early-stage robotic neurorehabilitation. RAGT is a customized approach for patients with different conditions to regain walking ability. To obtain a more-precise and clearer predictive model, collecting more RAGT training parameters and analyzing them for each individual disorder is a possible approach to help clinicians achieve a better understanding of the most efficient RAGT parameters for different patients. Trial registration: Retrospectively registered.

Symbiodiniaceae communities in some corals often shuffle or switch after severe bleaching events, one of the major threats to coral survival in a world with climate change. In this study we reciprocally transplanted five Leptoria phrygia colonies between two sites with significantly different temperature regimes and monitored them for 12 months. Our ITS2 amplicon deep sequencing demonstrated that L. phrygia acclimatized to maintain a strong and stable association with Durusdinium D17, D. trenchii, and D. glynnii, but also remained flexible and formed a short-term association with different Cladocopium. Most interestingly, two colonies shuffled between Durusdinium and Cladocopium without the occurrence of bleaching; one colony even switched its dominant Cladocopium after generic shuffling. Both dominant Cladocopium were originally rare with relative abundances as low as 0.024%. This is the first record of adult corals switching dominant symbiont without bleaching.

Coral reefs are under increasing threat from increasing warm temperature stress. Coral bleaching is caused by a combination of heat and light anomalies and therefore fewer corals should bleach in areas where either heat or light anomalies are ameliorated, such as in turbid waters or at depth. Here, we explore the overall response of the coral assemblage and of 16 individual taxa to a thermal anomaly along a depth gradient during the 2016 mass bleaching event at sites on the outer shelf of the northern Great Barrier Reef. Across all taxa, there was a curvilinear decline in the percentage of colonies bleached with depth that was consistent among sites and reflected the attenuation of light in the ocean. The percentage of colonies bleached was also higher on reefs with higher levels of temperature stress. In 10 taxa, including the abundant and ecologically significant Acropora, Pocillopora and Porites, the percentage of colonies bleached declined with depth. In 4 taxa, the percentage of colonies bleached peaked at intermediate depth. In 2 taxa, there was no effect of depth because bleaching was uniformly low. These data suggest that deeper areas of reef can provide a refuge from mass bleaching for many colonies of most taxa.

Corals are major contributors to a range of key ecosystem functions on tropical reefs, including calcification, photosynthesis, nutrient cycling, and the provision of habitat structure. The abundance of corals is declining at multiple scales, and the species composition of assemblages is responding to escalating human pressures, including anthropogenic global warming. An urgent challenge is to understand the functional consequences of these shifts in abundance and composition in different biogeographical contexts. While global patterns of coral species richness are well known, the biogeography of coral functions in provinces and domains with high and low redundancy is poorly understood. Here, we quantify the functional traits of all currently recognized zooxanthellate coral species (n = 821) in both the Indo-Pacific and Atlantic domains to examine the relationships between species richness and the diversity and redundancy of functional trait space. We find that trait diversity is remarkably conserved (>75% of the global total) along latitudinal and longitudinal gradients in species richness, falling away only in species-poor provinces (n < 200), such as the Persian Gulf (52% of the global total), Hawaii (37%), the Caribbean (26%), and the East-Pacific (20%), where redundancy is also diminished. In the more species-poor provinces, large and ecologically important areas of trait space are empty, or occupied by just a few, highly distinctive species. These striking biogeographical differences in redundancy could affect the resilience of critical reef functions and highlight the vulnerability of relatively depauperate, peripheral locations, which are often a low priority for targeted conservation efforts.

Colony morphological features is among the best predictor of the scleractinian coral’s function in reef ecosystems. However, morphological traits are categorical and to convert this information into a quantitative value as well as estimate their influence on ecosystem process remain a challenge. Here, we propose a trait-based approach to quantify morphological diversity and assess the structural complexity of the habitat provided by corals. We used a previously published dataset that is related to a bleaching event that affected the coral reef off Tikus Island in Indonesia in 1983. We found clear signs of recovery of the coral assemblage’s complexity toward pre El Niño conditions five years after the event. Independent of the change observed in species richness, this return in structural complexity was accompanied by a global decrease in species number associated with each particular morphological entity (Functional Redundancy) and an increase in the number of single-species entities (Functional Vulnerability). Together with species loss, we show an overall functional erosion of the coral assemblage and suggest that the role of the coral reef habitat could be strongly imperiled under repeated or synergistic disturbances. This approach offers an opportunity for a better understanding of coral responses to natural and anthropogenic disturbances.

BACKGROUND Predictions in pregnancy care are complex because of interactions among multiple factors. Hence, pregnancy outcomes are not easily predicted by a single predictor using only one algorithm or modeling method. OBJECTIVE This study aims to review and compare the predictive performances between logistic regression (LR) and other machine learning algorithms for developing or validating a multivariable prognostic prediction model for pregnancy care to inform clinicians’ decision making. METHODS Research articles from MEDLINE, Scopus, Web of Science, and Google Scholar were reviewed following several guidelines for a prognostic prediction study, including a risk of bias (ROB) assessment. We report the results based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Studies were primarily framed as PICOTS (population, index, comparator, outcomes, timing, and setting): Population: men or women in procreative management, pregnant women, and fetuses or newborns; Index: multivariable prognostic prediction models using non-LR algorithms for risk classification to inform clinicians’ decision making; Comparator: the models applying an LR; Outcomes: pregnancy-related outcomes of procreation or pregnancy outcomes for pregnant women and fetuses or newborns; Timing: pre-, inter-, and peripregnancy periods (predictors), at the pregnancy, delivery, and either puerperal or neonatal period (outcome), and either short- or long-term prognoses (time interval); and Setting: primary care or hospital. The results were synthesized by reporting study characteristics and ROBs and by random effects modeling of the difference of the logit area under the receiver operating characteristic curve of each non-LR model compared with the LR model for the same pregnancy outcomes. We also reported between-study heterogeneity by using τ2 and I2. RESULTS Of the 2093 records, we included 142 studies for the systematic review and 62 studies for a meta-analysis. Most prediction models used LR (92/142, 64.8%) and artificial neural networks (20/142, 14.1%) among non-LR algorithms. Only 16.9% (24/142) of studies had a low ROB. A total of 2 non-LR algorithms from low ROB studies significantly outperformed LR. The first algorithm was a random forest for preterm delivery (logit AUROC 2.51, 95% CI 1.49-3.53; I2=86%; τ2=0.77) and pre-eclampsia (logit AUROC 1.2, 95% CI 0.72-1.67; I2=75%; τ2=0.09). The second algorithm was gradient boosting for cesarean section (logit AUROC 2.26, 95% CI 1.39-3.13; I2=75%; τ2=0.43) and gestational diabetes (logit AUROC 1.03, 95% CI 0.69-1.37; I2=83%; τ2=0.07). CONCLUSIONS Prediction models with the best performances across studies were not necessarily those that used LR but also used random forest and gradient boosting that also performed well. We recommend a reanalysis of existing LR models for several pregnancy outcomes by comparing them with those algorithms that apply standard guidelines. CLINICALTRIAL PROSPERO (International Prospective Register of Systematic Reviews) CRD42019136106; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=136106

BackgroundPredictions in pregnancy care are complex because of interactions among multiple factors. Hence, pregnancy outcomes are not easily predicted by a single predictor using only one algorithm or modeling method.ObjectiveThis study aims to review and compare the predictive performances between logistic regression (LR) and other machine learning algorithms for developing or validating a multivariable prognostic prediction model for pregnancy care to inform clinicians’ decision making.MethodsResearch articles from MEDLINE, Scopus, Web of Science, and Google Scholar were reviewed following several guidelines for a prognostic prediction study, including a risk of bias (ROB) assessment. We report the results based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Studies were primarily framed as PICOTS (population, index, comparator, outcomes, timing, and setting): Population: men or women in procreative management, pregnant women, and fetuses or newborns; Index: multivariable prognostic prediction models using non-LR algorithms for risk classification to inform clinicians’ decision making; Comparator: the models applying an LR; Outcomes: pregnancy-related outcomes of procreation or pregnancy outcomes for pregnant women and fetuses or newborns; Timing: pre-, inter-, and peripregnancy periods (predictors), at the pregnancy, delivery, and either puerperal or neonatal period (outcome), and either short- or long-term prognoses (time interval); and Setting: primary care or hospital. The results were synthesized by reporting study characteristics and ROBs and by random effects modeling of the difference of the logit area under the receiver operating characteristic curve of each non-LR model compared with the LR model for the same pregnancy outcomes. We also reported between-study heterogeneity by using τ2 and I2.ResultsOf the 2093 records, we included 142 studies for the systematic review and 62 studies for a meta-analysis. Most prediction models used LR (92/142, 64.8%) and artificial neural networks (20/142, 14.1%) among non-LR algorithms. Only 16.9% (24/142) of studies had a low ROB. A total of 2 non-LR algorithms from low ROB studies significantly outperformed LR. The first algorithm was a random forest for preterm delivery (logit AUROC 2.51, 95% CI 1.49-3.53; I2=86%; τ2=0.77) and pre-eclampsia (logit AUROC 1.2, 95% CI 0.72-1.67; I2=75%; τ2=0.09). The second algorithm was gradient boosting for cesarean section (logit AUROC 2.26, 95% CI 1.39-3.13; I2=75%; τ2=0.43) and gestational diabetes (logit AUROC 1.03, 95% CI 0.69-1.37; I2=83%; τ2=0.07).ConclusionsPrediction models with the best performances across studies were not necessarily those that used LR but also used random forest and gradient boosting that also performed well. We recommend a reanalysis of existing LR models for several pregnancy outcomes by comparing them with those algorithms that apply standard guidelines.Trial RegistrationPROSPERO (International Prospective Register of Systematic Reviews) CRD42019136106; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=136106

Coral reefs in the Anthropocene are being subjected to unprecedented levels of stressors, including local disturbances—such as overfishing, habitat destruction, and pollution—and large-scale destruction related to the global impacts of climate change—such as typhoons and coral bleaching. Thus, the future of corals and coral reefs in any given community and coral-Symbiodiniaceae associations over time will depend on their level of resilience, from individual corals to entire ecosystems. Herein we review the environmental settings and long-term ecological research on coral reefs, based on both coral resilience and space, in Kenting National Park (KNP), Hengchun Peninsula, southern Taiwan, wherein fringing reefs have developed along the coast of both capes and a semi-closed bay, known as Nanwan, within the peninsula. These reefs are influenced by a branch of Kuroshio Current, the monsoon-induced South China Sea Surface Current, and a tide-induced upwelling that not only shapes coral communities, but also reduces the seawater temperature and creates fluctuating thermal environments which over time have favoured thermal-resistant corals, particularly those corals close to the thermal effluent of a nuclear power plant in the west Nanwan. Although living coral cover (LCC) has fluctuated through time in concordance with major typhoons and coral bleaching between 1986 and 2019, spatial heterogeneity in LCC recovery has been detected, suggesting that coral reef resilience is variable among subregions in KNP. In addition, corals exposed to progressively warmer and fluctuating thermal environments show not only a dominance of associated, thermally-tolerant Durusdinium spp. but also the ability to shuffle their symbiont communities in response to seasonal variations in seawater temperature without bleaching. We demonstrate that coral reefs in a small geographical range with unique environmental settings and ecological characteristics, such as the KNP reef, may be resilient to bleaching and deserve novel conservation efforts. Thus, this review calls for conservation efforts that use resilience-based management programs to reduce local stresses and meet the challenge of climate change.

Este artículo contiene 10 páginas, 5 figuras., Without drastic efforts to reduce carbon emissions and mitigate globalized stressors, tropical coral reefs are in jeopardy. Strategic conservation and management requires identification of the environmental and socioeconomic factors driving the persistence of scleractinian coral assemblages—the foundation species of coral reef ecosystems. Here, we compiled coral abundance data from 2,584 Indo-Pacific reefs to evaluate the influence of 21 climate, social and environmental drivers on the ecology of reef coral assemblages. Higher abundances of framework-building corals were typically associated with: weaker thermal disturbances and longer intervals for potential recovery; slower human population growth; reduced access by human settlements and markets; and less nearby agriculture. We therefore propose a framework of three management strategies (protect, recover or transform) by considering: (1) if reefs were above or below a proposed threshold of >10% cover of the coral taxa important for structural complexity and carbonate production; and (2) reef exposure to severe thermal stress during the 2014–2017 global coral bleaching event. Our findings can guide urgent management efforts for coral reefs, by identifying key threats across multiple scales and strategic policy priorities that might sustain a network of functioning reefs in the Indo-Pacific to avoid ecosystem collapse.

Without drastic efforts to reduce carbon emissions and mitigate globalized stressors, tropical coral reefs are in jeopardy. Strategic conservation and management requires identification of the environmental and socioeconomic factors driving the persistence of scleractinian coral assemblages-the foundation species of coral reef ecosystems. Here, we compiled coral abundance data from 2,584 Indo-Pacific reefs to evaluate the influence of 21 climate, social and environmental drivers on the ecology of reef coral assemblages. Higher abundances of framework-building corals were typically associated with: weaker thermal disturbances and longer intervals for potential recovery; slower human population growth; reduced access by human settlements and markets; and less nearby agriculture. We therefore propose a framework of three management strategies (protect, recover or transform) by considering: (1) if reefs were above or below a proposed threshold of >10% cover of the coral taxa important for structural complexity and carbonate production; and (2) reef exposure to severe thermal stress during the 2014-2017 global coral bleaching event. Our findings can guide urgent management efforts for coral reefs, by identifying key threats across multiple scales and strategic policy priorities that might sustain a network of functioning reefs in the Indo-Pacific to avoid ecosystem collapse.

This erratum is published as vendor overlooked corrections with misspelt scientific wording of family Siderastreidae.

Motivation The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. Main types of variables included The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. Spatial location and grain BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2). Time period and grain BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. Major taxa and level of measurement BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates. Software format .csv and .SQL., Global Ecology and Biogeography, 27 (7), ISSN:1466-822X, ISSN:1466-8238

Trait-based approaches advance ecological and evolutionary research because traits provide a strong link to an organism's function and fitness. Trait-based research might lead to a deeper understanding of the functions of, and services provided by, ecosystems, thereby improving management, which is vital in the current era of rapid environmental change. Coral reef scientists have long collected trait data for corals; however, these are difficult to access and often under-utilized in addressing large-scale questions. We present the Coral Trait Database initiative that aims to bring together physiological, morphological, ecological, phylogenetic and biogeographic trait information into a single repository. The database houses species- and individual-level data from published field and experimental studies alongside contextual data that provide important framing for analyses. In this data descriptor, we release data for 56 traits for 1547 species, and present a collaborative platform on which other trait data are being actively federated. Our overall goal is for the Coral Trait Database to become an open-source, community-led data clearinghouse that accelerates coral reef research.